Optical ray data processing device, optical ray data processing method, and optical ray data processing program

Abstract

This generates a ray dataset to determine the more accurate light distribution characteristics of the object. [Solution] The ray data processing device includes an acquisition unit that acquires multiple images obtained by imaging an object at multiple imaging angles and image data showing the correspondence between the images and the imaging angles, and a generation unit that generates a ray data set showing the starting point and vector of the light rays emitted from the object based on the image data. The generation unit generates a light distribution profile showing the light flux value at each of the imaging angles and the light flux value at an interpolated imaging angle different from the imaging angle, based on the image data, and generates the ray data set based on the light distribution profile.

Description

Technical Field

[0001] The present disclosure relates to a ray data processing device, a ray data processing method, and a ray data processing program.

Background Art

[0002] Conventionally, technologies for generating data used in calculating the light distribution characteristics of an object such as a light source have been developed. For example, Patent Document 1 (Japanese Unexamined Patent Application Publication No. 2015-132866) discloses the following ray model formation method. That is, the ray model formation method is a ray model formation method for converting from the near-field distribution of light from a light source to a ray model used in Monte Carlo simulation, measuring the light from the light source with a near-field measurement device to input near-field measurement data, and using a uniform sampling method for the input near-field measurement data with respect to the position of the light source, and using an importance sampling method for generating rays in the direction at that position, thereby generating a ray model used in the Monte Carlo simulation.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Beyond the technology described in Patent Document 1, a technology capable of generating a ray data set for obtaining more accurate light distribution characteristics of an object is desired.

[0005] The present disclosure has been made to solve the above problems, and an object thereof is to provide a ray data processing device, a ray data processing method, and a ray data processing program capable of generating a ray data set for obtaining more accurate light distribution characteristics of an object. [Means for solving the problem]

[0006] (1) A ray data processing device according to an embodiment of the present disclosure is a ray data processing device that generates a ray data set used for calculating the light distribution characteristics of an object, comprising: an acquisition unit that acquires a plurality of images obtained by imaging the object at a plurality of imaging angles and image data showing the correspondence between the images and the imaging angles; and a generation unit that generates a ray data set showing the starting point and vector of light rays emitted from the object based on the image data acquired by the acquisition unit, wherein the generation unit generates a light distribution profile showing the luminous flux value at each of the imaging angles and the luminous flux value at an interpolated imaging angle different from the imaging angle, and generates the ray data set based on the light distribution profile.

[0007] Thus, by generating a light distribution profile showing the luminous flux values ​​at the imaging angle and interpolated imaging angle, and then generating a ray dataset based on the light distribution profile, the resolution of the measurement points can be improved through computational processing without increasing the number of measurement points used to image the object, compared to a configuration that generates a ray dataset based on a light distribution profile showing the luminous flux values ​​at the imaging angle. Furthermore, the error in the spherical band coefficient used to calculate the luminous flux values ​​at each imaging angle can be reduced. For example, even when generating a ray dataset for an object with high luminosity in the polar axis direction, it is possible to suppress abnormal values ​​in the light distribution characteristics near the polar axis in the ray profile obtained using the ray dataset. Therefore, it is possible to generate a ray dataset for determining the more accurate light distribution characteristics of the object.

[0008] (2) In (1) above, the generation unit may determine a number of vectors having endpoints determined based on the interpolation imaging angle, the number of vectors corresponding to the luminous flux value at the interpolation imaging angle, and generate a ray dataset showing the determined vectors.

[0009] This configuration allows for improving the resolution of the endpoint of the ray vector through computation without increasing the number of measurement points. As a result, it is possible to reduce the occurrence of patterns in the ray profile obtained by calculations using the ray dataset, and to obtain a ray profile that exhibits smooth light distribution characteristics.

[0010] (3) In (1) or (2) above, the generation unit may generate an interpolated image which is an image of the object at the interpolated imaging angle based on the image data, determine the starting point based on the pixel position of the pixels in the interpolated image, and generate the ray dataset indicating the determined starting point.

[0011] This configuration allows for improved resolution of the light ray's starting point through computational processing without increasing the number of measurement points. Furthermore, the starting point of the light ray corresponding to the interpolated imaging angle can be determined more accurately based on the pixel position of the pixels in the interpolated image.

[0012] (4) A ray data processing device according to an embodiment of the present disclosure is a ray data processing device that generates a ray data set used for calculating the light distribution characteristics of an object, comprising: an acquisition unit that acquires a plurality of images obtained by imaging the object at a plurality of imaging angles and image data showing the correspondence between the imaging angles; and a generation unit that generates a ray data set showing the starting point and vector of light rays emitted from the object based on the image data acquired by the acquisition unit, wherein the generation unit generates an interpolated image which is an image of the object at an angle different from the imaging angle based on the image data, determines the starting point based on the pixel position of the pixels in the interpolated image, and generates a ray data set showing the determined starting point.

[0013] In this way, by generating an interpolated image of the object at a target angle different from the imaging angle, and determining the starting point of the light ray based on the pixel position of the pixels in the interpolated image, the resolution of the starting point of the light ray can be improved through computational processing without increasing the number of measurement points for imaging the object. Therefore, a light ray dataset can be generated to determine the more accurate light distribution characteristics of the object.

[0014] (5) In (4) above, the acquisition unit may acquire image data showing the correspondence between the plurality of images and the imaging angle represented using a first coordinate system defined in Japanese Industrial Standard (JIS C 8105-5), and the generation unit may generate the interpolated image at the target angle, represented using a second coordinate system different from the first coordinate system, as defined in Japanese Industrial Standard (JIS C 8105-5), based on the image data.

[0015] With this configuration, for example, when generating a ray dataset of an object with high luminosity in the polar axis direction of the first coordinate system, the ray dataset can be generated using an interpolated image at the target angle represented using the second coordinate system. Therefore, the influence of errors in the spheroid coefficient used to calculate the luminous flux value at each imaging angle can be reduced, and abnormal values ​​in the light distribution characteristics near the polar axis can be suppressed in the ray profile obtained using the ray dataset.

[0016] (6) In (4) above, the ray data processing device may further include a distribution unit that performs a distribution processing to randomly change at least one of the plurality of imaging angles in the image data, and the generation unit may generate the interpolated image at the target angle, which is the imaging angle after the distribution processing.

[0017] Thus, by using a configuration that performs distributed processing to randomly change the imaging angle, it is possible to reduce the regularity of the light distribution characteristics caused by the intervals between imaging angles in the ray profile obtained using the ray dataset. Furthermore, by using a configuration that generates an interpolated image at the imaging angle after distributed processing, the starting point of the light rays corresponding to the imaging angle after distributed processing can be determined more accurately based on the pixel positions of the pixels in the interpolated image. As a result, even when generating a ray dataset of an object with a narrow light distribution and high luminosity in the polar axis direction, the occurrence of concentric circular patterns with widths corresponding to the intervals between imaging angles can be suppressed in the ray profile.

[0018] (7) A ray data processing method according to an embodiment of the present disclosure is a ray data processing method in a ray data processing device that generates a ray data set used for calculating the light distribution characteristics of an object, comprising the steps of: acquiring image data showing the correspondence between a plurality of images obtained by imaging the object at a plurality of imaging angles and the imaging angles; and generating a ray data set showing the starting point and vector of light rays emitted from the object based on the acquired image data, wherein in the step of generating the ray data set, a light distribution profile showing the luminous flux value at each of the imaging angles and the luminous flux value at an interpolated imaging angle different from the imaging angle is generated based on the image data, and the ray data set is generated based on the light distribution profile.

[0019] Thus, by generating a light distribution profile showing the luminous flux values ​​at the imaging angle and interpolated imaging angle, and then generating a ray dataset based on the light distribution profile, the resolution of the measurement points can be improved through computational processing without increasing the number of measurement points used to image the object, compared to a configuration that generates a ray dataset based on a light distribution profile showing the luminous flux values ​​at the imaging angle. Furthermore, the error in the spherical band coefficient used to calculate the luminous flux values ​​at each imaging angle can be reduced. For example, even when generating a ray dataset for an object with high luminosity in the polar axis direction, it is possible to suppress abnormal values ​​in the light distribution characteristics near the polar axis in the ray profile obtained using the ray dataset. Therefore, it is possible to generate a ray dataset for determining the more accurate light distribution characteristics of the object.

[0020] (8) A ray data processing method according to an embodiment of the present disclosure is a ray data processing method in a ray data processing device that generates a ray data set used for calculating the light distribution characteristics of an object, comprising the steps of: acquiring a plurality of images obtained by imaging the object at a plurality of imaging angles and image data showing the correspondence between the imaging angles; and generating a ray data set showing the starting point and vector of light rays emitted from the object based on the acquired image data, wherein in the step of generating the ray data set, an interpolated image is generated based on the image data, which is an image of the object at an angle different from the imaging angle, the starting point is determined based on the pixel position of the pixels in the interpolated image, and a ray data set showing the determined starting point is generated.

[0021] In this way, by generating an interpolated image of the object at a target angle different from the imaging angle, and determining the starting point of the light ray based on the pixel position of the pixels in the interpolated image, the resolution of the starting point of the light ray can be improved through computational processing without increasing the number of measurement points for imaging the object. Therefore, a light ray dataset can be generated to determine the more accurate light distribution characteristics of the object.

[0022] (9) The ray data processing program according to the embodiment of the present disclosure is a ray data processing program used in a ray data processing device that generates a ray data set used for calculating the light distribution characteristics of an object, and is a program that causes a computer to function as an acquisition unit that acquires a plurality of images obtained by imaging the object at a plurality of imaging angles and image data showing the correspondence between the imaging angles, and a generation unit that generates the ray data set showing the starting point and vector of the light rays emitted from the object based on the image data acquired by the acquisition unit, wherein the generation unit generates a light distribution profile showing the luminous flux value at each of the imaging angles and the luminous flux value at an interpolated imaging angle different from the imaging angle, and generates the ray data set based on the light distribution profile.

[0023] Thus, by generating a light distribution profile showing the luminous flux values ​​at the imaging angle and interpolated imaging angle, and then generating a ray dataset based on the light distribution profile, the resolution of the measurement points can be improved through computational processing without increasing the number of measurement points used to image the object, compared to a configuration that generates a ray dataset based on a light distribution profile showing the luminous flux values ​​at the imaging angle. Furthermore, the error in the spherical band coefficient used to calculate the luminous flux values ​​at each imaging angle can be reduced. For example, even when generating a ray dataset for an object with high luminosity in the polar axis direction, it is possible to suppress abnormal values ​​in the light distribution characteristics near the polar axis in the ray profile obtained using the ray dataset. Therefore, it is possible to generate a ray dataset for determining the more accurate light distribution characteristics of the object.

[0024] (10) The ray data processing program according to an embodiment of the present disclosure is a ray data processing program used in a ray data processing device that generates a ray data set used for calculating the light distribution characteristics of an object. The program causes a computer to function as an acquisition unit that acquires a plurality of images obtained by imaging the object at a plurality of imaging angles and image data indicating the correspondence relationship between the imaging angles, and a generation unit that generates the ray data set indicating the starting point and vector of the ray emitted from the object based on the image data acquired by the acquisition unit. The generation unit generates an interpolation image that is an image of the object at a target angle different from the imaging angle based on the image data, determines the starting point based on the pixel position of the pixel in the interpolation image, and generates the ray data set indicating the determined starting point.

[0025] In this way, by generating an interpolation image of the object at a target angle different from the imaging angle and determining the starting point of the ray based on the pixel position of the pixel in the interpolation image, it is possible to improve the resolution of the starting point of the ray by calculation processing without increasing the measurement points for imaging the object. Therefore, it is possible to generate a ray data set for obtaining more accurate light distribution characteristics of the object.

Advantages of the Invention

[0026] According to the present disclosure, it is possible to generate a ray data set for obtaining more accurate light distribution characteristics of an object.

Brief Description of the Drawings

[0027] [Figure 1] FIG. 1 is a diagram showing the configuration of a ray data generation system according to the first embodiment of the present disclosure. [Figure 2] FIG. 2 is a diagram showing an example of the measurement points of a detector in a light distribution measurement device according to the first embodiment of the present disclosure. [Figure 3] FIG. 3 is a schematic diagram showing an example of an image generated by a detector in a light distribution measurement device according to the first embodiment of the present disclosure. [Figure 4] Figure 4 shows another example of a measurement point of a detector in a light distribution measuring device according to the first embodiment of the present disclosure. [Figure 5] Figure 5 is a schematic diagram showing in two dimensions an example of a ray data set generated by a ray data processing device according to the first embodiment of this disclosure. [Figure 6] Figure 6 is a schematic diagram showing in two dimensions an example of a ray profile obtained using a ray dataset generated by a ray data processing device according to the first embodiment of this disclosure. [Figure 7] Figure 7 shows an example of a spherical band coefficient used in generating a ray dataset by a ray data processing device according to the first embodiment of this disclosure. [Figure 8] Figure 8 shows an example of a method for generating a ray dataset using a ray data processing device according to the first embodiment of this disclosure. [Figure 9] Figure 9 shows an example of a ray profile obtained using a ray data set generated by a ray data processing device according to a comparative example of the first embodiment of this disclosure. [Figure 10] Figure 10 shows the configuration of a ray data processing device according to the first embodiment of the present disclosure. [Figure 11] Figure 11 shows an example of image data acquired by the acquisition unit in the optical data processing device according to the first embodiment of this disclosure. [Figure 12] Figure 12 shows an example of a luminous intensity profile generated by the processing unit in the optical data processing device according to the first embodiment of the present disclosure. [Figure 13] Figure 13 shows an example of a high-definition optical distribution profile generated by the processing unit in the optical data processing device according to the first embodiment of the present disclosure. [Figure 14] Figure 14 shows a method for generating a high-definition optical distribution profile by a processing unit in an optical data processing device according to the first embodiment of the present disclosure. [Figure 15]Figure 15 shows an example of a ray extraction profile generated by the generation unit in the ray data processing device according to the first embodiment of this disclosure. [Figure 16] Figure 16 shows a method for generating an image by a processing unit in a light ray data processing device according to the first embodiment of the present disclosure. [Figure 17] Figure 17 shows an example of image data generated by the generation unit in the optical data processing device according to the first embodiment of the present disclosure. [Figure 18] Figure 18 shows an example of a ray profile obtained using a ray dataset generated by a ray data processing device according to the first embodiment of this disclosure. [Figure 19] Figure 19 is a flowchart illustrating an example of the operation procedure when a ray data processing device according to the first embodiment of this disclosure generates a ray data set. [Figure 20] Figure 20 shows the configuration of a ray data processing device according to a second embodiment of the present disclosure. [Figure 21] Figure 21 shows an example of image data generated by the generation unit in the optical data processing device according to the second embodiment of the present disclosure. [Figure 22] Figure 22 is a diagram showing the method for generating an image by the processing unit in the optical data processing device according to the second embodiment of the present disclosure. [Figure 23] Figure 23 shows an example of a light distribution profile generated by the generation unit in the light data processing device according to the second embodiment of the present disclosure. [Figure 24] Figure 24 shows an example of a ray extraction profile generated by the generation unit in the ray data processing device according to the second embodiment of this disclosure. [Figure 25] Figure 25 is a flowchart illustrating an example of the operation procedure when a ray data processing device according to the second embodiment of this disclosure generates a ray data set. [Figure 26] Figure 26 shows the configuration of a ray data processing device according to a third embodiment of the present disclosure. [Figure 27] Figure 27 shows an example of a light distribution profile generated by the generation unit in the light data processing device according to the third embodiment of the present disclosure. [Figure 28] Figure 28 shows an example of a ray extraction profile generated by the generation unit in the ray data processing device according to the third embodiment of this disclosure. [Figure 29] Figure 29 shows an example of distributed processing by a processing unit in a ray data processing device according to a third embodiment of the present disclosure. [Figure 30] Figure 30 shows a method for generating an image by a processing unit in a light ray data processing device according to a third embodiment of the present disclosure. [Figure 31] Figure 31 is a flowchart illustrating an example of the operation procedure when a ray data processing device according to the third embodiment of this disclosure generates a ray data set. [Figure 32] Figure 32 shows the configuration of a ray data generation system according to the fourth embodiment of this disclosure. [Figure 33] Figure 33 shows the configuration of a ray data processing device according to the fourth embodiment of this disclosure. [Figure 34] Figure 34 shows an example of image data acquired by the acquisition unit in the optical data processing device according to the fourth embodiment of the present disclosure. [Figure 35] Figure 35 shows an example of a method for generating a ray data set by a generation unit in a ray data processing device according to the fourth embodiment of the present disclosure. [Figure 36] Figure 36 shows an example of a light distribution profile generated by the generation unit in the ray data processing device according to the fourth embodiment of this disclosure. [Figure 37] Figure 37 shows an example of a ray extraction profile generated by the generation unit in the ray data processing device according to the fourth embodiment of this disclosure. [Figure 38]Figure 38 is a flowchart illustrating an example of the operation procedure when a ray data processing device according to the fourth embodiment of this disclosure generates a ray data set. [Modes for carrying out the invention]

[0028] Embodiments of this disclosure will be described below with reference to the drawings. In the drawings, the same or corresponding parts are denoted by the same reference numerals, and their descriptions will not be repeated. Furthermore, at least some of the embodiments described below may be combined in any way.

[0029] <First Embodiment> [Configuration and Basic Operation] Figure 1 is a diagram showing the configuration of a ray data generation system according to a first embodiment of the present disclosure. Referring to Figure 1, the ray data generation system 301 comprises a ray data processing device 101 and a light distribution measuring device 201. The light distribution measuring device 201 generates image data Dp that shows the correspondence between an image G1 obtained by imaging an object S at one or more measurement points Mp and the measurement points Mp. Based on the image data Dp generated by the light distribution measuring device 201, the ray data processing device 101 generates a ray data set Dst used for calculating the light distribution characteristics of the object S.

[0030] Object S is an object that emits light itself, such as lighting fixtures and display devices, or an object that reflects or transmits light from a light source. Specifically, Object S is a display such as a television, indoor lighting, outdoor lighting, automotive lighting, or film. The shape of Object S is not limited to a sphere as shown in Figure 1.

[0031] Here, in Figure 1, the axis parallel to the vertical direction is defined as the Y-axis. The axis parallel to the horizontal direction and parallel to the direction from the object S to the detector 51 when the detector 51 is in the position shown in Figure 1 is defined as the Z-axis. The axis parallel to the horizontal direction and perpendicular to the Z-axis is defined as the X-axis. The X-axis corresponds to the "auxiliary axis of the lighting fixture" as defined in the Japanese Industrial Standard (JIS C 8105-5). The Y-axis corresponds to the "third axis of the lighting fixture" as defined in the Japanese Industrial Standard (JIS C 8105-5). The Z-axis corresponds to the "reference axis of the lighting fixture" as defined in the Japanese Industrial Standard (JIS C 8105-5). Hereafter, the coordinate system represented using the X-axis, Y-axis, and Z-axis will also be referred to as a three-dimensional Cartesian coordinate system. The object S is placed at the origin of the three-dimensional Cartesian coordinate system.

[0032] (Light distribution measuring device) The light distribution measuring device 201 comprises a detector 51, a first arm 52, a second arm 53, a first motor 54, a second motor 55, and a support base 56. The support base 56 fixes the object S. The first motor 54 is rotatable in the direction of arrow E1 in the figure. The second motor 55 is rotatable in the direction of arrow E2 in the figure. The first arm 52 is connected to the first motor 54. The second arm 53 is connected to the first arm 52 via the second motor 55. The detector 51 is attached to the second arm 53. The detector 51 is a two-dimensional imaging device.

[0033] The light distribution measuring device 201 is a goniometer capable of changing the position of the detector 51 while maintaining the distance L between the object S and the principal point Cp of the detector 51, which will be described later, and measures the near-field light distribution of the object S. More specifically, the detector 51 rotates around the Y axis in the direction of arrow E1 as the first motor 54 rotates in the direction of arrow E1. Also, the detector 51 rotates around the X axis in the direction of arrow E2 as the second motor 55 rotates in the direction of arrow E2.

[0034] Figure 2 shows an example of a measurement point of a detector in a light distribution measuring device according to the first embodiment of the present disclosure. Referring to Figure 2, the principal point Cp of the detector 51 moves on a spherical surface Sp centered on the object S as the first motor 54 and the second motor 55 rotate. The detector 51 generates an image G1 of the object S by imaging the object S when the principal point Cp is located at the measurement point Mp on the spherical surface Sp.

[0035] For example, a measurement point Mp is represented using the θφ coordinate system defined in the Japanese Industrial Standard (JIS C 8105-5). More specifically, a measurement point Mp is represented using the Z-axis as the polar axis, the inclination angle θ relative to the polar axis, and the rotation angle φ with the polar axis as the center of rotation. The inclination angle θ is also called the vertical angle. The rotation angle φ is also called the horizontal angle. The inclination angle θ is a value of 0° or more and 180° or less. The rotation angle φ is a value of 0° or more and less than 360°. The θφ coordinate system is an example of the first coordinate system.

[0036] The optical distribution measuring device 201 receives a measurement control command indicating one or more measurement points Mp from a control device or optical ray data processing device 101 (not shown). The first motor 54 and the second motor 55 in the optical distribution measuring device 201 rotate according to the measurement control command. The detector 51 generates an image G1 by imaging the object S with an inclination angle θ and rotation angle φ corresponding to the measurement point Mp, when the principal point Cp is located at the measurement point Mp indicated by the measurement control command.

[0037] Figure 3 is a schematic diagram showing an example of an image generated by a detector in a light distribution measuring device according to the first embodiment of the present disclosure. In the image G1 shown in Figure 3, the black areas indicate low brightness regions, and the areas with low hatching density indicate high brightness regions. Referring to Figure 3, for example, the detector 51 generates an image G1 containing 160,000 pixels p arranged in a 400 × 400 matrix. Hereinafter, in image G1, the pixel p in the a column from the left and the b row from the top will also be referred to as pixel p(a,b). The pixel intensity pl of pixel p(a,b) will also be referred to as pixel intensity pl(a,b). Here, a and b are integers greater than or equal to 1 and less than or equal to 400.

[0038] For example, the detector 51 images the object S at multiple measurement points Mp in 2π space, which is half of the sphere Sp, with measurement intervals Wθ and Wφ specified by the user. The measurement interval Wθ is the measurement interval for the tilt angle θ, and the measurement interval Wφ is the measurement interval for the rotation angle φ. As an example, the detector 51 generates 32,760 images G1 by imaging the object S at 32,760 (91 × 360) measurement points Mp, which consist of a combination of a tilt angle θ at 1° intervals in the range from 0° to 90° and a rotation angle φ at 1° intervals in the range from 0° to 359°.

[0039] The detector 51 generates image data Dp that shows the correspondence between the generated image G1 and the measurement point Mp, which is expressed using the tilt angle θ and rotation angle φ. The detector 51 also generates measurement condition data Dm that shows the field of view Wa of image G1 and the distance L between the object S and the principal point Cp of the detector 51. The detector 51 transmits the generated image data Dp and measurement condition data Dm to the ray data processing device 101.

[0040] Figure 4 shows another example of a measurement point of a detector in a light distribution measuring device according to the first embodiment of the present disclosure. Referring to Figure 4, the detector 51 may generate image data Dp indicating a measurement point Mp represented using, for example, the αβ coordinate system defined in the Japanese Industrial Standard (JIS C 8105-5). In this case, the measurement point Mp is represented using an inclination angle α with respect to the polar axis and a rotation angle β with the polar axis as the center of rotation, with the X axis being the polar axis. The inclination angle α is also called the vertical angle. The rotation angle β is also called the horizontal angle. The inclination angle α is a value of -90° or more and 90° or less. The rotation angle β is a value of -180° or more and less than 180°. The αβ coordinate system is an example of a second coordinate system.

[0041] Furthermore, the detector 51 may generate image data Dp that indicates a measurement point Mp, represented using, for example, the XY coordinate system defined in the Japanese Industrial Standard (JIS C 8105-5). Alternatively, the detector 51 may image the object S at the measurement point Mp in the 4π space, which is the entirety of the spherical surface Sp.

[0042] (Light ray data processing device) Figure 5 is a schematic diagram showing in two dimensions an example of a ray data set generated by a ray data processing device according to the first embodiment of the present disclosure. Referring to Figure 5, the ray data processing device 101 generates a ray data set Dst based on image data Dp received from the optical distribution measuring device 201.

[0043] The ray dataset Dst includes ray data Dr, which shows information about the rays emitted from the object S. The ray data Dr is data that shows the starting point coordinates Ps(x,y,z) indicating the position of the starting point of the ray in a three-dimensional Cartesian coordinate system, the ray vector Vt indicating the direction of the ray, and the intensity Pw of the ray. The ray data processing device 101 generates a ray dataset Dst that includes ray data Dr for the number of rays N specified by the user.

[0044] The ray dataset Dst is used to calculate the light distribution characteristics of the object S. For example, a manufacturer of a lighting fixture that includes the object S as a component uses simulation software to evaluate the light distribution characteristics of the object S and designs the lighting fixture using the evaluation results. More specifically, the simulation software uses the ray dataset Dst generated by the ray data processing device 101 to calculate the illuminance Lx at a target Tg located at an arbitrary distance from the object S as the light distribution characteristic of the object S. The target Tg is, for example, a hemisphere positioned so that its concave surface faces the object S.

[0045] Figure 6 is a schematic diagram showing a two-dimensional example of a ray profile obtained using a ray dataset generated by a ray data processing device according to the first embodiment of this disclosure. In Figure 6, the horizontal axis is the tilt angle α in the αβ coordinate system, and the vertical axis is the rotation angle β in the αβ coordinate system. In the ray profile Lp shown in Figure 6, the black areas indicate regions with low illuminance Lx, and the areas with low hatching density indicate regions with high illuminance Lx.

[0046] Referring to Figure 6, the simulation software uses the ray dataset Dst to generate a ray profile Lp that shows the correspondence between the calculated position on the surface of the target Tg and the illuminance Lx. The manufacturer of a lighting fixture that includes the object S as a component designs the lighting fixture using the ray profile Lp generated by the simulation software.

[0047] Generally, the object S has the highest luminosity in the Z-axis direction in a three-dimensional polar coordinate system. Therefore, in the ray profile Lp, the illuminance Lx is high at the calculation position where the inclination angle α is zero° and the rotation angle β is zero° in the αβ coordinate system, i.e., the illuminance Lx is high at the calculation position where the inclination angle θ is zero° in the θφ coordinate system.

[0048] (Method for generating a ray dataset using a ray data processing device) Figure 7 shows an example of a spherical band coefficient used in generating a ray dataset by a ray data processing device according to the first embodiment of this disclosure. In Figure 7, the horizontal axis is the tilt angle θ, and the vertical axis is the spherical band coefficient. Referring to Figure 7, the spherical band coefficient is at its minimum value when the tilt angle θ is zero° and 180°.

[0049] The ray data processing device 101 calculates the sum of the pixel intensities pl of each pixel p in the image G1 corresponding to the measurement point Mp as the luminous intensity at that measurement point Mp, based on the image data Dp. The ray data processing device 101 calculates the luminous flux value for each measurement point Mp by multiplying the luminous intensity at each measurement point Mp by a quantized spheroid coefficient according to the measurement interval Wθ. The ray data processing device 101 normalizes the luminous flux value for each measurement point Mp to determine the number of extracted rays Ndr, which indicates the number of ray data Dr to be generated based on the corresponding image G1 for each measurement point Mp.

[0050] Figure 8 shows an example of a method for generating a ray data set using a ray data processing device according to the first embodiment of this disclosure. Figure 8 shows the positional relationship between the detector 51 and the imaging plane Is of the detector 51 in the XZ plane. The imaging plane Is is a plane perpendicular to the line passing through the object S and the principal point Cp.

[0051] Referring to Figure 8, the ray data processing device 101 determines, for each measurement point Mp, the starting pixel pps, which is the pixel p that should be the starting point of the ray, based on the pixel intensity pl and the number of extracted lines Ndr of each pixel p in the corresponding image G1. The ray data processing device 101 calculates the coordinates of the starting pixel pps in a three-dimensional polar coordinate system based on the field of view Wa indicated by the measurement condition data Dm in the storage unit 20. Based on the calculated coordinates of the starting pixel pps, the ray data processing device 101 determines the starting coordinates Ps(x,y,z). The starting coordinates Ps(x,y,z) are the coordinates on the imaging plane Is.

[0052] Furthermore, the ray data processing device 101 calculates the coordinates of the principal point Cp in a three-dimensional polar coordinate system based on the distance L indicated by the measurement point Mp and measurement condition data Dm corresponding to the image G1. Based on the calculated coordinates of the principal point Cp, the ray data processing device 101 determines the endpoint coordinates Pe(x,y,z). Then, the ray data processing device 101 determines the ray vector Vt as the vector pointing from the determined starting point coordinates Ps(x,y,z) to the determined endpoint coordinates Pe(x,y,z).

[0053] Furthermore, the ray data processing device 101 calculates the total luminous flux value TL of the object S based on all the images G1 shown by the image data Dp. The ray data processing device 101 calculates the luminous flux value per ray by dividing the calculated total luminous flux value TL by the number of rays N. The ray data processing device 101 determines the calculated luminous flux value per ray as the intensity Pw of the ray data Dr.

[0054] The ray data processing device 101 generates ray data Dr, which represents the determined starting point coordinates Ps(x,y,z), the determined ray vector Vt, and the determined intensity Pw. The ray data processing device 101 generates N ray data Drs and generates a ray dataset Dst containing the N ray data Drs.

[0055] Incidentally, when a ray dataset Dst generated using conventional technology is provided to simulation software, it may not be possible to obtain accurate light distribution characteristics of the object S.

[0056] Figure 9 shows an example of a ray profile obtained using a ray data set generated by a ray data processing device according to a comparative example of the first embodiment of this disclosure. Figure 9 shows the illuminance Lx when the rotation angle β in the ray profile Lp of Figure 6 is zero°. In Figure 9, the horizontal axis is the tilt angle α and the vertical axis is the illuminance Lx.

[0057] Referring to Figure 9, in the ray profile Lp, even though the light distribution characteristics of the object S are uniform, the illuminance Lx when the tilt angle α,θ is zero° can be significantly large. This is because the spheroid coefficient multiplied by the luminous intensity at each measurement point Mp contains an error corresponding to the measurement interval Wθ, and this error causes an excessively large number of ray data Dr generated based on the measurement point Mp near the polar axis and the image G1 corresponding to that measurement point Mp.

[0058] Furthermore, for example, if the spatial resolution setting for illuminance Lx in the simulation software is small compared to the spacing of the measurement points Mp, a tile-like pattern may appear in the ray profile Lp.

[0059] Furthermore, for example, if the object S has a narrow light distribution and a ray dataset Dst is generated using an image G1 captured at a measurement point Mp represented using the θφ coordinate system, a concentric circular pattern with a width corresponding to the measurement interval Wθ may appear in the ray profile Lp.

[0060] Therefore, the optical data processing device 101 according to the first embodiment of this disclosure solves the above problem with the following configuration.

[0061] (Configuration of optical data processing device) Figure 10 shows the configuration of a ray data processing device according to a first embodiment of the present disclosure. Referring to Figure 10, the ray data processing device 101 comprises an acquisition unit 10, a storage unit 20, and a processing unit 30. The processing unit 30 is an example of a generation unit. The processing unit 30 includes a light distribution information generation unit 31, an extraction information generation unit 32, an image synthesis processing unit 33, and a ray data generation unit 34. One or both of the acquisition unit 10 and the processing unit 30 are implemented by a processing circuit (Circuitry) including, for example, one or more processors. The storage unit 20 is, for example, a non-volatile memory included in the processing circuit.

[0062] Figure 11 shows an example of image data acquired by the acquisition unit in the optical data processing apparatus according to the first embodiment of the present disclosure. Referring to Figure 11, the acquisition unit 10 acquires image data Dp that shows the correspondence between multiple images G1 obtained by imaging an object S at multiple imaging angles A1 and the imaging angles A1. For example, the acquisition unit 10 acquires image data Dp that shows the correspondence between multiple images G1 and the imaging angles A1 expressed using the θφ coordinate system.

[0063] More specifically, the acquisition unit 10 receives image data Dp from the optical distribution measuring device 201, which shows the correspondence between a set of tilt angle θ and rotation angle φ, which is the imaging angle A1, and the image G1. For example, the image data Dp shows the correspondence between a set of tilt angle θ and rotation angle φ at 1° intervals and the image G1. Hereinafter, the imaging angle A1 in which the tilt angle θ is n° and the rotation angle φ is m° will also be referred to as imaging angle A1(n,m). Also, in the image data Dp, the image G1 corresponding to imaging angle A1(n,m) will also be referred to as image G1(n,m). Here, n is an integer greater than or equal to zero and less than or equal to 90. m is an integer greater than or equal to zero and less than or equal to 359.

[0064] Furthermore, the acquisition unit 10 receives measurement condition data Dm from the optical distribution measuring device 201. The acquisition unit 10 stores the received image data Dp and measurement condition data Dm in the storage unit 20.

[0065] The acquisition unit 10 may be configured to acquire multiple images G1 obtained by imaging the object S at multiple imaging angles A1 at irregular intervals, and image data Dp that shows the correspondence between these images and the imaging angles A1. Furthermore, the acquisition unit 10 may be configured to receive image data Dp from a device other than the light distribution measuring device 201.

[0066] The processing unit 30 generates a ray dataset Dst that shows the starting point and ray vector of the rays emitted from the object S, based on the image data Dp acquired by the acquisition unit 10. More specifically, the processing unit 30 accepts a user operation to specify the number of rays N. The processing unit 30 generates a ray dataset Dst that includes ray data Dr for the specified number of rays N, according to the accepted user operation. The number of rays N may be, for example, 100,000, 1,000,000, 10,000,000, or 100 million.

[0067] The processing unit 30 generates a high-resolution optical distribution profile Pr1 based on the image data Dp, which shows the luminous flux value at each imaging angle A1 and the luminous flux value at an imaging angle A2 different from imaging angle A1. Based on the high-resolution optical distribution profile Pr1, it generates a ray dataset Dst. Imaging angle A2 is an example of an interpolated imaging angle. The high-resolution optical distribution profile Pr1 is an example of an optical distribution profile. The details of the processing in the processing unit 30 are described below.

[0068] (Generation of luminosity profile PrA) In the processing unit 30, the light distribution information generation unit 31 acquires the image data Dp when the acquisition unit 10 stores the image data Dp in the storage unit 20.

[0069] The light distribution information generation unit 31 calculates the luminous intensity B at each imaging angle A1 indicated by the image data Dp. More specifically, the light distribution information generation unit 31 calculates the luminous intensity B at the imaging angle A1 as the sum of the pixel intensities pl of each pixel p in the image G1 corresponding to the imaging angle A1. The light distribution information generation unit 31 calculates the luminous intensity B for each imaging angle A1.

[0070] Figure 12 shows an example of an intensity profile generated by the processing unit in the optical ray data processing device according to the first embodiment of the present disclosure. Referring to Figure 12, the light distribution information generation unit 31 generates an intensity profile PrA that shows the correspondence between a set of tilt angle θ and rotation angle φ, which are the imaging angle A1, and the intensity B. The intensity profile PrA shows the correspondence between a set of tilt angle θ and rotation angle φ at 1° intervals and the intensity B. Hereinafter, in the intensity profile PrA, the intensity B corresponding to the imaging angle A1(n,m) will also be referred to as intensity B(n,m).

[0071] (Generation of high-definition light distribution profile Pr1) Figure 13 shows an example of a high-resolution optical distribution profile generated by a processing unit in a ray data processing device according to the first embodiment of the present disclosure. Referring to Figure 13, the optical distribution information generation unit 31 generates a high-resolution optical distribution profile Pr1 that shows the correspondence between imaging angle A1 and luminous flux value, based on the luminous intensity profile PrA. The optical distribution information generation unit 31 further generates a high-resolution optical distribution profile Pr1 that shows the correspondence between imaging angle A2, which has a smaller angular interval than imaging angle A1, and luminous flux value.

[0072] For example, imaging angle A2 is the angle obtained by interpolating between two adjacent imaging angles A1 with a tilt angle θ and a rotation angle φ at 0.1° intervals. Hereinafter, imaging angles A1 and A2 will also be referred to as imaging angle Ag. Furthermore, imaging angle Ag where the tilt angle θ is i° and the rotation angle φ is j° will also be referred to as imaging angle Ag(i,j), imaging angle Ag1 where the tilt angle θ is i° and the rotation angle φ is j° will also be referred to as imaging angle Ag1(i,j), and imaging angle Ag2 where the tilt angle θ is i° and the rotation angle φ is j° will also be referred to as imaging angle Ag2(i,j). Here, i is a value in 0.1 intervals from 0 to 90, and j is a value in 0.1 intervals from 0 to 359. In other words, the light distribution information generation unit 31 interpolates between all imaging angles A1 by imaging angle A2 and generates a high-definition light distribution profile Pr1 that shows the correspondence between 3,235,491 imaging angles Ag, which are combinations of 901 tilt angles θ and 3,591 rotation angles φ, and 3,235,491 light flux values.

[0073] Figure 14 is a diagram showing a method for generating a high-definition optical distribution profile by a processing unit in an optical data processing device according to a first embodiment of the present disclosure. Figure 14 shows the positional relationship between four measurement points Mp, Mp(n,m), Mp(n+1,m), Mp(n,m+1), Mp(n+1,m+1), which correspond to imaging angles A1(n,m), A1(n+1,m+1), respectively, and a point Px on the spherical surface Sp corresponding to the imaging angle Ag(i,j).

[0074] Referring to Figure 14, the light distribution information generation unit 31, for example, refers to the luminosity profile PrA and obtains the imaging angles A1(n,m), A1(n+1,m), A1(n,m+1), A1(n+1,m+1), which are the four imaging angles A1 closest to the imaging angle Ag(i,j), and the luminosity B(n,m), B(n+1,m), B(n,m+1), B(n+1,m+1).

[0075] The light distribution information generation unit 31 sets the contribution rates r(n,m), r(n+1,m), r(n,m+1), and r(n+1,m+1) respectively, which are the contribution rates r of the imaging angles A1(n,m), A1(n+1,m), A1(n,m+1), and A1(n+1,m+1) with respect to the imaging angle Ag(i,j), based on the distance Dx between the measurement points Mp(n,m), Mp(n+1,m), Mp(n,m+1), Mp(n+1,m+1) and point Px.

[0076] More specifically, the light distribution information generation unit 31 sets a contribution rate r for the imaging angle A1 that is proportional to the shortness of the distance Dx between the measurement point Mp and point Px corresponding to the imaging angle A1, and the sum of the contribution rates r(n,m), r(n+1,m), r(n,m+1), and r(n+1,m+1) is 1.

[0077] The light distribution information generation unit 31 calculates the luminosity B(i,j) at the imaging angle Ag(i,j) according to the following equation (1). B(i,j)=B(n,m)×r(n,m)+B(n+1,m)×r(n+1,m)+B(n,m+1)×r(n,m+1)+B(n+1,m+1)×r(n+1,m+1)...(1)

[0078] The light distribution information generation unit 31 calculates the luminous intensity B for each imaging angle Ag and generates a high-resolution luminous intensity profile PrB that shows the correspondence between the imaging angle Ag and the luminous intensity B.

[0079] The light distribution information generation unit 31 calculates the luminous flux value at the imaging angle Ag by multiplying the luminous intensity B at the imaging angle Ag shown in the high-definition luminous intensity profile PrB by a spherical band coefficient corresponding to the tilt angle θ shown in the imaging angle Ag. The light distribution information generation unit 31 calculates the luminous flux value for each imaging angle Ag and generates a high-definition light distribution profile Pr1 that shows the correspondence between the imaging angle Ag and the luminous flux value.

[0080] When the light distribution information generation unit 31 generates a high-definition light distribution profile Pr1, it calculates the total luminous flux value TL of the object S based on the luminous flux value at each imaging angle Ag, for example, in accordance with the Japanese Industrial Standard (JIS C 8105-5). The light distribution information generation unit 31 determines the intensity Pw as the value obtained by dividing the calculated total luminous flux value TL by the number of rays N.

[0081] Referring again to Figure 10, the light distribution information generation unit 31 outputs the high-resolution light distribution profile Pr1 and image data Dp to the extraction information generation unit 32. The light distribution information generation unit 31 also outputs intensity information indicating the determined intensity Pw to the ray data generation unit 34.

[0082] (Generation of ray extraction profile Pr2) Figure 15 shows an example of a ray extraction profile generated by the generation unit in the ray data processing device according to the first embodiment of the present disclosure. Referring to Figure 15, the extraction information generation unit 32 in the processing unit 30 determines the number of extracted rays Ndr for each imaging angle Ag based on the high-definition light distribution profile Pr1 received from the light distribution information generation unit 31. The extraction information generation unit 32 then generates a ray extraction profile Pr2 that shows the correspondence between the imaging angle Ag and the number of extracted rays Ndr. The number of extracted rays Ndr at the imaging angle Ag indicates the number of ray data Dr to be generated based on the image G1 corresponding to that imaging angle Ag.

[0083] For example, the extraction information generation unit 32 determines the number of extracted rays Ndr for each imaging angle Ag by normalizing the luminous flux values ​​for each imaging angle Ag shown in the high-definition optical distribution profile Pr1. More specifically, the extraction information generation unit 32 calculates the sum Fb of the luminous flux values ​​for each imaging angle Ag shown in the high-definition optical distribution profile Pr1. Then, the extraction information generation unit 32 determines the number of extracted rays Ndr for that imaging angle Ag by multiplying the luminous flux value for the imaging angle Ag shown in the high-definition optical distribution profile Pr1 by (number of rays N / sum Fb). The extraction information generation unit 32 determines the number of extracted rays Ndr for each imaging angle Ag and generates the ray extraction profile Pr2.

[0084] Referring again to Figure 10, the extraction information generation unit 32 outputs the image data Dp received from the light distribution information generation unit 31 and the generated ray extraction profile Pr2 to the image synthesis processing unit 33.

[0085] (Generating image G2) The image synthesis processing unit 33 generates an image G2 of the object S at imaging angle A2 based on the image data Dp. Image G2 is an example of an interpolated image.

[0086] More specifically, the image synthesis processing unit 33 receives image data Dp and a ray extraction profile Pr2 from the light distribution information generation unit 31, and uses the multiple images G1 indicated by the received image data Dp to generate an image G2 obtained when imaging is performed using the detector 51 at imaging angle A2. Hereinafter, each of images G1 and G2 will also be referred to as image Gg.

[0087] Figure 16 is a diagram showing the method of generating an image by the processing unit in the optical data processing device according to the first embodiment of the present disclosure. Figure 16 shows the positional relationship between the measurement points Mp(n,m), Mp(n+1,m), Mp(n,m+1), Mp(n+1,m+1), which are four measurement points Mp corresponding to imaging angles A1(n,m), A1(n+1,m), A1(n+1,m+1), respectively, and a point Px on the spherical surface Sp corresponding to imaging angle A2(i,j).

[0088] Referring to Figure 16, the image synthesis processing unit 33, for example, refers to the ray extraction profile Pr2 and the image data Dp to obtain the four imaging angles A1 closest to the imaging angle A2(i,j): imaging angles A1(n,m), A1(n+1,m), A1(n,m+1), A1(n+1,m+1), and images G1(n,m), G1(n+1,m), G1(n,m+1), G1(n+1,m+1).

[0089] The image synthesis processing unit 33, in the same manner as the light distribution information generation unit 31, sets the contribution rates r(n,m), r(n+1,m), r(n,m+1), r(n+1,m+1), and r(n+1,m+1) respectively, which are the contribution rates r of the imaging angles A1(n,m), A1(n+1,m), A1(n,m+1), A1(n+1,m+1) with respect to the imaging angle A2(i,j), based on the distance Dx between the measurement points Mp(n,m), Mp(n+1,m), Mp(n,m+1), Mp(n+1,m+1) and point Px.

[0090] The image synthesis processing unit 33 generates image G2 at imaging angle A2(i,j) by adding the pixel intensities pl(a,b) in image G1 for each pixel p according to the following equation (2). G2=G1(n,m)×r(n,m)+G1(n+1,m)×r(n+1,m)+G1(n,m+1)×r(n,m+1)+G1(n+1,m+1)×r(n+1,m+1)...(2)

[0091] Figure 17 shows an example of image data generated by the generation unit in the ray data processing device according to the first embodiment of the present disclosure. Referring to Figure 17, the image synthesis processing unit 33 generates an image G2 for each imaging angle A2 and generates image data Dpg that shows the correspondence between imaging angles Ag including imaging angles A1 and A2 and images Gg including images G1 and G2. Referring again to Figure 10, the image synthesis processing unit 33 outputs the generated image data Dpg and the ray extraction profile Pr2 received from the extraction information generation unit 32 to the ray data generation unit 34.

[0092] (Generation of ray dataset Dst) The ray data generation unit 34 receives image data Dpg and ray extraction profile Pr2 from the image synthesis processing unit 33, and generates a ray data set Dst based on the received image data Dpg and ray extraction profile Pr2.

[0093] For example, the ray data generation unit 34 determines a number of ray vectors Vt having endpoint coordinates Pe(x,y,z) determined based on the imaging angle A2 indicated by the ray extraction profile Pr2, corresponding to the luminous flux value at imaging angle A2, and generates a ray dataset Dst showing the determined ray vectors Vt. Alternatively, for example, the ray data generation unit 34 determines the starting coordinates Ps(x,y,z) based on the pixel position of pixel p in the image G2 indicated by the image data Dpg, and generates a ray dataset Dst showing the determined starting coordinates Ps(x,y,z).

[0094] More specifically, the ray data generation unit 34 refers to the ray extraction profile Pr2 and obtains an image Gg corresponding to the imaging angle Ag where the number of extracted rays Ndr is 1 or more from the image data Dpg.

[0095] The ray data generation unit 34 determines the starting pixel pps in the acquired image Gg by normalizing the pixel intensity pl of the pixel p included in the acquired image Gg. More specifically, the ray data generation unit 34 calculates the sum Fp of the pixel intensities pl of each pixel p in the acquired image Gg. Then, the ray data generation unit 34 determines the number of rays originating from pixel p by multiplying the pixel intensity pl of pixel p in the image Gg by (number of extracted rays Ndr / sum Fp). In other words, if the value obtained by multiplying the pixel intensity pl of pixel p by (number of extracted rays Ndr / sum Fp) is 1 or greater, the ray data generation unit 34 determines that pixel p to be the starting pixel pps.

[0096] The ray data generation unit 34 determines the starting pixel pps for each imaging angle Ag for all images Gg corresponding to imaging angles Ag where the number of extracted rays Ndr is 1 or more, following the procedure described above. Subsequently, the ray data generation unit 34 generates starting and ending point information that shows the correspondence between the imaging angle Ag and the determined starting pixel pps.

[0097] The ray data generation unit 34 generates ray data Dr for the number of rays N based on the generated start and end point information, the intensity information received from the light distribution information generation unit 31, and the measurement condition data Dm in the storage unit 20.

[0098] More specifically, the ray data generation unit 34 obtains the imaging angle Ag and one or more starting point pixels pps corresponding to the imaging angle Ag from the starting point and ending point information.

[0099] The ray data generation unit 34 calculates the coordinates of the principal point Cp in a three-dimensional polar coordinate system based on the acquired imaging angle Ag, which is the tilt angle θ and rotation angle φ, and the distance L indicated by the measurement condition data Dm. The ray data generation unit 34 determines the calculated coordinates of the principal point Cp as the endpoint coordinates Pe(x,y,z).

[0100] Furthermore, the ray data generation unit 34 calculates the coordinates of the starting pixel pps in a three-dimensional polar coordinate system based on the pixel position of the acquired starting pixel pps and the field of view Wa indicated by the measurement condition data Dm. The ray data generation unit 34 determines the calculated coordinates of the starting pixel pps as the starting coordinates Ps(x,y,z).

[0101] The ray data generation unit 34 determines the ray vector Vt as a vector pointing from the determined starting coordinates Ps(x,y,z) to the determined ending coordinates Pe(x,y,z). Then, the ray data generation unit 34 generates ray data Dr that shows the determined starting coordinates Ps(x,y,z), the determined ray vector Vt, and the intensity Pw indicated by the intensity information.

[0102] The ray data generation unit 34, when there are multiple starting point pixels pps corresponding to the imaging angle Ag, determines the starting point coordinates Ps(x,y,z) and the ray vector Vt for each starting point pixel pps, and generates ray data Dr.

[0103] The ray data generation unit 34 determines the starting coordinates Ps(x,y,z) and generates ray data Dr for all starting pixels pps corresponding to the imaging angle Ag. Then, it obtains a new imaging angle Ag and the starting pixels pps corresponding to that imaging angle Ag from the starting and ending point information, determines the starting coordinates Ps(x,y,z) and ray vector Vt, and generates ray data Dr.

[0104] The ray data generation unit 34 generates a ray dataset Dst containing the ray data Dr for all pairs of imaging angles Ag and starting pixels pps in the start and end point information, once it has finished generating the ray data Dr for the number of rays N. The ray data generation unit 34 stores the generated ray dataset Dst in the storage unit 20.

[0105] Figure 18 shows an example of a ray profile obtained using a ray dataset generated by a ray data processing device according to the first embodiment of this disclosure. Figure 18 shows the illuminance Lx when the rotation angle β in the ray profile Lp is zero°. In Figure 18, the horizontal axis is the tilt angle α and the vertical axis is the illuminance Lx.

[0106] The ray profile Lp obtained by providing the ray dataset Dst generated by the ray data generation unit 34 to the simulation software does not show a significant increase in illuminance Lx when the tilt angle α,θ is zero°, compared to the ray profile Lp shown in Figure 9. This is because a high-resolution optical distribution profile Pr1 is generated by multiplying the luminous intensity B at imaging angles Ag with intervals of 0.1°, which is smaller than the angular interval of imaging angle A1, by a spherical band coefficient corresponding to the tilt angle θ shown by the imaging angle Ag. This reduces the error in the spherical band coefficient and allows for the generation of a more accurate number of ray data Dr based on the imaging angle Ag near the polar axis.

[0107] [Operation Flow] Figure 19 is a flowchart illustrating an example of the operation procedure when a ray data processing device according to the first embodiment of this disclosure generates a ray data set.

[0108] Referring to Figure 19, first, the ray data processing device 101 receives image data Dp from the light distribution measuring device 201 (step S11).

[0109] Next, the ray data processing device 101 accepts a user operation to specify the number of rays N (step S12).

[0110] Next, the ray data processing device 101 calculates the luminosity B at each imaging angle A1 indicated by the image data Dp and generates a luminosity profile PrA that shows the correspondence between the imaging angle A1 and the luminosity B (step S13).

[0111] Next, the ray data processing device 101 calculates the luminosity B for each imaging angle Ag based on the luminosity profile PrA, and generates a high-resolution luminosity profile PrB that shows the correspondence between the imaging angle Ag and the luminosity B (step S14).

[0112] Next, the ray data processing device 101 generates a high-resolution optical distribution profile Pr1 that shows the correspondence between the imaging angle Ag and the luminous flux value by multiplying the luminous intensity B at each imaging angle Ag shown in the high-resolution luminous intensity profile PrB by a spherical band coefficient corresponding to the tilt angle θ (step S15).

[0113] Next, the ray data processing device 101 calculates the total luminous flux value TL based on the luminous flux value at each imaging angle Ag, and determines the intensity Pw by dividing the total luminous flux value TL by the number of rays N (step S16).

[0114] Next, the ray data processing device 101 determines the number of extracted rays Ndr for each imaging angle Ag based on the high-definition light distribution profile Pr1, and generates a ray extraction profile Pr2 that shows the correspondence between the imaging angle Ag and the number of extracted rays Ndr (step S17).

[0115] Next, the optical data processing device 101 generates image G2 for each imaging angle A2 using the multiple images G1 indicated by the image data Dp, and generates image data Dpg that shows the correspondence between the imaging angle Ag and the image Gg (step S18).

[0116] Next, the ray data processing device 101 determines the starting pixel pps for each imaging angle Ag based on the ray extraction profile Pr2 and the image data Dpg, and generates starting and ending point information that shows the correspondence between the imaging angle Ag and the starting pixel pps (step S19).

[0117] Next, the ray data processing device 101 generates a ray dataset Dst, which includes ray data Dr for the number of rays N, based on the start and end point information, intensity Pw, and measurement condition data Dm (step S20).

[0118] In the first embodiment of the present disclosure, the ray data generation system 301 is configured such that the light distribution measuring device 201 images the object S at multiple measurement points Mp by fixing the object S and changing the position of the detector 51. However, the present disclosure is not limited to this configuration. The light distribution measuring device 201 may also be configured such that the detector 51 is fixed and the object S is rotated around the origin of a three-dimensional Cartesian coordinate system to image the object S at multiple measurement points Mp.

[0119] Furthermore, in the first embodiment of the present disclosure, the ray data processing device 101 has a configuration in which the processing unit 30 includes an image synthesis processing unit 33, but the present disclosure is not limited to this. The processing unit 30 may also have a configuration in which the image synthesis processing unit 33 is not included. In this case, the extraction information generation unit 32 outputs the image data Dp and the ray extraction profile Pr2 to the ray data generation unit 34. The ray data generation unit 34 generates a ray data set Dst based on the image data Dp and the ray extraction profile Pr2 received from the extraction information generation unit 32.

[0120] More specifically, the ray data generation unit 34 refers to the ray extraction profile Pr2 to obtain an image G1 from the image data Dp corresponding to an imaging angle A1 where the number of extracted rays Ndr is 1 or more, and determines the starting pixel pps in the obtained image G1. The ray data generation unit 34 also refers to the ray extraction profile Pr2 to obtain an image G1 from the image data Dp corresponding to an imaging angle A1 closest to an imaging angle A2 where the number of extracted rays Ndr is 1 or more, and determines the starting pixel pps in the obtained image G1. The ray data generation unit 34 then generates start and end point information showing the correspondence between imaging angle A1 and the starting pixel pps in image G1, and the correspondence between imaging angle A2 and the starting pixel pps in image G1. Based on the generated start and end point information, intensity information, and measurement condition data Dm, the ray data generation unit 34 generates ray data Dr with a number of rays N.

[0121] Furthermore, in the first embodiment of the optical data processing device 101 of this disclosure, the optical distribution information generation unit 31 in the processing unit 30 is configured to interpolate between all imaging angles A1 with imaging angle A2, but it is not limited to this. The optical distribution information generation unit 31 may be configured to interpolate between a portion of the imaging angles A1 near the polar axis, which are among the imaging angles A1 indicated by the optical intensity profile PrA, with imaging angle A2. This can shorten the processing time in the processing unit 30.

[0122] Next, other embodiments of the present disclosure will be described with reference to the drawings. In the drawings, the same or corresponding parts are denoted by the same reference numerals, and their descriptions will not be repeated.

[0123] <Second Embodiment> [Configuration and Basic Operation] This embodiment relates to a light ray data processing device 102 that, compared to the light ray data processing device 101 according to the first embodiment, does not generate a high-definition light distribution profile Pr1, but instead generates an image G3 of an object S at an imaging angle A3 different from the imaging angle A1. Except for the contents described below, it is the same as the light ray data processing device 101 according to the first embodiment.

[0124] Figure 20 shows the configuration of a ray data processing device according to a second embodiment of the present disclosure. Referring to Figure 20, the ray data processing device 102 includes a processing unit 40 instead of a processing unit 30, compared to the ray data processing device 101. The processing unit 40 is an example of a generation unit. Compared to the processing unit 30, the processing unit 40 includes a light distribution information generation unit 41 instead of a light distribution information generation unit 31, an extraction information generation unit 42 instead of an extraction information generation unit 32, and an image synthesis processing unit 43 instead of an image synthesis processing unit 33. One or both of the acquisition unit 10 and the processing unit 40 are implemented by a processing circuit (Circuitry) including, for example, one or more processors. The storage unit 20 is, for example, a non-volatile memory included in the processing circuit.

[0125] The processing unit 40 generates image G3, which is an image of the object S at an imaging angle A3 different from imaging angle A1, based on the image data Dp acquired by the acquisition unit 10. For example, the processing unit 40 generates image G3 at imaging angle A3, which is represented using the αβ coordinate system, based on the image data Dp. Imaging angle A3 is an example of a target angle. Image G3 is an example of an interpolated image.

[0126] The processing unit 40 determines the starting coordinates Ps(x,y,z) based on the pixel position of pixel p in the generated image G3, and generates a ray dataset Dst that represents the determined starting coordinates Ps(x,y,z). The details of the processing in the processing unit 40 are described below.

[0127] (Generating image G3) In the processing unit 40, the image synthesis processing unit 43 acquires the image data Dp when the acquisition unit 10 stores the image data Dp in the storage unit 20.

[0128] Figure 21 shows an example of image data generated by the generation unit in the optical ray data processing device according to the second embodiment of the present disclosure. Referring to Figure 21, the image synthesis processing unit 43 generates image data Dpx that shows the correspondence between the imaging angle A3, expressed using the αβ coordinate system, and the image G3, based on the image data Dp. More specifically, the image synthesis processing unit 43 generates image data Dpx that shows the correspondence between the set of tilt angle α and rotation angle β, which are the imaging angle A3, and the image G3.

[0129] For example, the image synthesis processing unit 43 generates image data Dpx that shows the correspondence between 32,761 (181 × 181) imaging angles A3, which consist of combinations of tilt angles α at 1° intervals in the range from -90° to 90° and rotation angles β at 1° intervals in the range from -90° to 90°, and 32,761 images G3. Hereinafter, an imaging angle A3 where the tilt angle α is u° and the rotation angle β is v° will also be referred to as imaging angle A3(u,v). Here, u and v are integers greater than or equal to -90 and less than or equal to 90.

[0130] Figure 22 is a diagram showing the method of generating an image by the processing unit in the optical data processing device according to the second embodiment of the present disclosure. Figure 22 shows the positional relationship between the measurement points Mp(n,m), Mp(n+1,m), Mp(n,m+1), Mp(n+1,m+1), which are four measurement points Mp corresponding to imaging angles A1(n,m), A1(n+1,m), A1(n,m+1), and A1(n+1,m+1), respectively, and the point Py on the spherical surface Sp corresponding to imaging angle A3(u,v).

[0131] Referring to Figure 22, the image synthesis processing unit 43, for example, refers to the image data Dp and obtains the four imaging angles A1 closest to the imaging angle A3(u,v), namely imaging angles A1(n,m), A1(n+1,m), A1(n,m+1), and A1(n+1,m+1), as well as the images G1(n,m), G1(n+1,m), G1(n,m+1), and G1(n+1,m+1).

[0132] The image synthesis processing unit 43, in the same manner as the image synthesis processing unit 33, sets the contribution rates r(n,m), r(n+1,m), r(n,m+1), and r(n+1,m+1) respectively, which are the contribution rates r of the imaging angles A1(n,m), A1(n+1,m), A1(n,m+1), A1(n+1,m+1) with respect to the imaging angle A3(u,v), based on the distance Dy between the measurement points Mp(n,m), Mp(n+1,m), Mp(n,m+1), Mp(n+1,m+1) and point Py.

[0133] More specifically, the image synthesis processing unit 43 sets a contribution rate r for the imaging angle A1 that is proportional to the shortness of the distance Dy between the measurement point Mp and point Py corresponding to the imaging angle A1, and the sum of the contribution rates r(n,m), r(n+1,m), r(n,m+1), and r(n+1,m+1) is 1.

[0134] The image synthesis processing unit 43 generates image G3 at imaging angle A3(u,v) by adding the pixel intensities pl(a,b) in image G1 for each pixel p according to the following equation (3). G3=G1(n,m)×r(n,m)+G1(n+1,m)×r(n+1,m)+G1(n,m+1)×r(n,m+1)+G1(n+1,m+1)×r(n+1,m+1)...(3)

[0135] The image synthesis processing unit 43 generates an image G3 for each imaging angle A3 and generates image data Dpx that shows the correspondence between the imaging angle A3 and the image G3. Referring again to Figure 20, the image synthesis processing unit 43 outputs the generated image data Dpx to the light distribution information generation unit 41.

[0136] (Generation of light distribution profile Pr3) The light distribution information generation unit 41 receives image data Dpx from the image synthesis processing unit 43 and calculates the luminous intensity B at each imaging angle A3 indicated by the received image data Dpx. More specifically, the light distribution information generation unit 41 calculates the luminous intensity B at the imaging angle A3 by summing the pixel intensities pl of each pixel p in the image G3 corresponding to the imaging angle A3. The light distribution information generation unit 41 calculates the luminous intensity B for each imaging angle A3.

[0137] The light distribution information generation unit 41 calculates the luminous flux value at imaging angle A3 by multiplying the luminous intensity B at imaging angle A3 by a predetermined spherical band coefficient, for example, in accordance with the Japanese Industrial Standard (JIS C 8105-5). The light distribution information generation unit 41 calculates the luminous flux value for each imaging angle A3.

[0138] Figure 23 shows an example of a light distribution profile generated by the generation unit in the light ray data processing device according to the second embodiment of the present disclosure. Referring to Figure 23, the light distribution information generation unit 41 calculates the luminous flux value for each imaging angle A3 and generates a light distribution profile Pr3 that shows the correspondence between the tilt angle α and rotation angle β representing the imaging angle A3 and the luminous flux value.

[0139] Furthermore, the light distribution information generation unit 41 calculates the total luminous flux value TL of the object S based on the luminous flux value at each imaging angle A3, for example, in accordance with the Japanese Industrial Standard (JIS C 8105-5). The light distribution information generation unit 41 determines the intensity Pw as the value obtained by dividing the calculated total luminous flux value TL by the number of rays N.

[0140] Referring again to Figure 20, the light distribution information generation unit 41 outputs the light distribution profile Pr3 and image data Dpx to the extraction information generation unit 42. The light distribution information generation unit 41 also outputs intensity information indicating the determined intensity Pw to the ray data generation unit 34.

[0141] (Generation of ray extraction profile Pr4) Figure 24 shows an example of a ray extraction profile generated by the generation unit in the ray data processing device according to the second embodiment of the present disclosure. Referring to Figure 24, the extraction information generation unit 42 determines the number of extracted rays Ndr for each imaging angle A3 based on the light distribution profile Pr3 received from the light distribution information generation unit 41. For example, the extraction information generation unit 42 determines the number of extracted rays Ndr for each imaging angle A3 by normalizing the light flux value for each imaging angle A3 indicated by the light distribution profile Pr3. The extraction information generation unit 42 then generates a ray extraction profile Pr4 that shows the correspondence between the imaging angle A3 and the number of extracted rays Ndr. The number of extracted rays Ndr at imaging angle A3 indicates the number of ray data Dr to be generated based on the image G3 corresponding to that imaging angle A3.

[0142] Referring again to Figure 20, the extraction information generation unit 42 outputs the image data Dpx received from the light distribution information generation unit 41 and the generated ray extraction profile Pr4 to the ray data generation unit 34.

[0143] (Generation of ray dataset Dst) The ray data generation unit 34 receives image data Dpx and ray extraction profile Pr4 from the extraction information generation unit 42, and generates a ray dataset Dst based on the received image data Dpx and ray extraction profile Pr4.

[0144] More specifically, the ray data generation unit 34 refers to the ray extraction profile Pr4 and obtains an image G3 from the image data Dpx that corresponds to the imaging angle A3 where the number of extracted rays Ndr is 1 or more. The ray data generation unit 34 determines the starting pixel pps in the image G3 by normalizing the pixel intensity pl of the pixels p included in the acquired image G3.

[0145] The ray data generation unit 34 determines the starting pixel pps for each imaging angle A3 for all images G3 corresponding to imaging angle A3 where the number of extracted rays Ndr is 1 or more, following the procedure described above. Subsequently, the ray data generation unit 34 generates starting and ending point information that shows the correspondence between the imaging angle A3 and the determined starting pixel pps.

[0146] As described above, the ray data generation unit 34 generates ray data Dr for a number of rays N based on the generated start and end point information, the intensity information received from the light distribution information generation unit 41, and the measurement condition data Dm in the storage unit 20. The ray data generation unit 34 generates a ray dataset Dst containing the ray data Dr for a number of rays N, and stores the generated ray dataset Dst in the storage unit 20.

[0147] [Operation Flow] Figure 25 is a flowchart illustrating an example of the operation procedure when a ray data processing device according to the second embodiment of this disclosure generates a ray data set.

[0148] Referring to Figure 25, first, the ray data processing device 102 receives image data Dp from the light distribution measuring device 201 (step S21).

[0149] Next, the ray data processing device 102 accepts a user operation to specify the number of rays N (step S22).

[0150] Next, the optical data processing device 102 generates an image G3 for each imaging angle A3 using the multiple images G1 indicated by the image data Dp, and generates image data Dpx that shows the correspondence between the imaging angle A3 and the image G3 (step S23).

[0151] Next, the ray data processing device 102 calculates the luminous flux value for each imaging angle A3 based on the image data Dpx, and generates a light distribution profile Pr3 that shows the correspondence between the tilt angle α and rotation angle β indicated by the imaging angle A3 and the luminous flux value (step S24).

[0152] Next, the ray data processing device 102 calculates the total luminous flux value TL based on the luminous flux value at each imaging angle A3, and determines the intensity Pw by dividing the total luminous flux value TL by the number of rays N (step S25).

[0153] Next, the ray data processing device 102 determines the number of extracted rays Ndr for each imaging angle A3 based on the light distribution profile Pr3, and generates a ray extraction profile Pr4 that shows the correspondence between the imaging angle A3 and the number of extracted rays Ndr (step S26).

[0154] Next, the ray data processing device 102 determines the starting pixel pps for each imaging angle A3 based on the ray extraction profile Pr4 and the image data Dpx, and generates start and end point information showing the correspondence between the imaging angle A3 and the starting pixel pps (step S27).

[0155] Next, the ray data processing device 102 generates a ray dataset Dst, which includes ray data Dr for the number of rays N, based on the start and end point information, intensity Pw, and measurement condition data Dm (step S28).

[0156] In the optical data processing device 102 according to the second embodiment of this disclosure, the image synthesis processing unit 43 in the processing unit 40 is configured to generate image data Dpx showing the correspondence between imaging angles A3, which consist of a combination of tilt angles α and rotation angles β at 1° intervals, and image G3. However, the invention is not limited to this configuration. The image synthesis processing unit 43 may be configured to generate image data Dpx showing the correspondence between imaging angles A3 with angular intervals smaller than the angular intervals of imaging angles A1 shown by the image data Dp and image G3. Alternatively, the image synthesis processing unit 43 may be configured to generate image data Dpx showing the correspondence between imaging angles A3 with angular intervals larger than the angular intervals of imaging angles A1 shown by the image data Dp and image G3.

[0157] Next, other embodiments of the present disclosure will be described with reference to the drawings. In the drawings, the same or corresponding parts are denoted by the same reference numerals, and their descriptions will not be repeated.

[0158] <Third Embodiment> [Configuration and Basic Operation] This embodiment relates to a ray data processing device 103 that, compared to the ray data processing device 101 according to the first embodiment, does not generate a high-definition light distribution profile Pr1, but instead performs endpoint dispersion processing to randomly change the imaging angle A1, and generates an image G4 of the object S at the imaging angle A1 after the starting point dispersion processing. Except for the contents described below, it is the same as the ray data processing device 101 according to the first embodiment.

[0159] Figure 26 shows the configuration of a ray data processing device according to a third embodiment of the present disclosure. Referring to Figure 26, the ray data processing device 103, compared to the ray data processing device 101, includes a processing unit 70 instead of a processing unit 30. The processing unit 70 is an example of a generation unit and an example of a distribution unit. Compared to the processing unit 30, the processing unit 70 includes a light distribution information generation unit 71 instead of a light distribution information generation unit 31, an extraction information generation unit 72 instead of an extraction information generation unit 32, an image synthesis processing unit 73 instead of an image synthesis processing unit 33, and further includes a distributed processing unit 74. One or both of the acquisition unit 10 and the processing unit 70 are implemented by a processing circuit (Circuitry) including, for example, one or more processors. The storage unit 20 is, for example, a non-volatile memory included in the processing circuit.

[0160] The processing unit 70 generates image G4, which is an image of the object S at an imaging angle A4 different from imaging angle A1, based on the image data Dp acquired by the acquisition unit 10. For example, the processing unit 70 performs a distributed processing to randomly change at least one of the multiple imaging angles A1 in the image data Dp, and generates image G4 at imaging angle A4, which is the imaging angle A1 after the distributed processing. Image angle A4 is an example of a target angle. Image G4 is an example of an interpolated image.

[0161] The processing unit 70 determines the starting coordinates Ps(x,y,z) based on the pixel position of pixel p in the generated image G4, and generates a ray dataset Dst that represents the determined starting coordinates Ps(x,y,z). The details of the processing in the processing unit 70 are described below.

[0162] (Generation of the light distribution profile Pr5) In the processing unit 70, the light distribution information generation unit 71 acquires the image data Dp when it is stored in the storage unit 20 by the acquisition unit 10. The light distribution information generation unit 71 calculates the luminosity B at each imaging angle A1 indicated by the image data Dp. More specifically, the light distribution information generation unit 71 calculates the luminosity B at the imaging angle A1 as the sum of the pixel intensities pl of each pixel p of the image G1 corresponding to the imaging angle A1. The light distribution information generation unit 71 calculates the luminosity B for each imaging angle A1.

[0163] The light distribution information generation unit 71 calculates the luminous flux value at imaging angle A1 by multiplying the luminous intensity B at imaging angle A1 by a predetermined spherical band coefficient, for example, in accordance with the Japanese Industrial Standard (JIS C 8105-5). The light distribution information generation unit 71 calculates the luminous flux value for each imaging angle A1.

[0164] Figure 27 shows an example of a light distribution profile generated by the generation unit in the light ray data processing device according to the third embodiment of the present disclosure. Referring to Figure 27, the light distribution information generation unit 71 calculates the luminous flux value for each imaging angle A1 and generates a light distribution profile Pr5 that shows the correspondence between the tilt angle θ and rotation angle φ representing the imaging angle A1 and the luminous flux value.

[0165] Furthermore, the light distribution information generation unit 71 calculates the total luminous flux value TL of the object S based on the luminous flux value at each imaging angle A1, for example, in accordance with the Japanese Industrial Standard (JIS C 8105-5). The light distribution information generation unit 71 determines the intensity Pw as the value obtained by dividing the calculated total luminous flux value TL by the number of rays N.

[0166] Referring again to Figure 26, the light distribution information generation unit 71 outputs the light distribution profile Pr5 and image data Dp to the extraction information generation unit 72. The light distribution information generation unit 71 also outputs intensity information indicating the determined intensity Pw to the ray data generation unit 34.

[0167] (Generation of ray extraction profile Pr6) Figure 28 shows an example of a ray extraction profile generated by the generation unit in the ray data processing device according to the third embodiment of the present disclosure. Referring to Figure 28, the extraction information generation unit 72 determines the number of extracted rays Ndr for each imaging angle A1 based on the light distribution profile Pr5 received from the light distribution information generation unit 71. For example, the extraction information generation unit 72 determines the number of extracted rays Ndr for each imaging angle A1 by normalizing the light flux value for each imaging angle A1 shown in the light distribution profile Pr5. The extraction information generation unit 72 then generates a ray extraction profile Pr6 that shows the correspondence between the imaging angle A1 and the number of extracted rays Ndr. The number of extracted rays Ndr at imaging angle A1 indicates the number of ray data Dr to be generated based on the image G1 corresponding to that imaging angle A1.

[0168] Referring again to Figure 26, the extraction information generation unit 72 outputs the generated ray extraction profile Pr6 to the distribution processing unit 74. The extraction information generation unit 72 also outputs the image data Dp received from the light distribution information generation unit 71 to the image synthesis processing unit 73.

[0169] (Distributed processing) The distributed processing unit 74 receives the ray extraction profile Pr6 from the extraction information generation unit 72 and performs distributed processing to randomly change the imaging angle A1 indicated by the received ray extraction profile Pr6.

[0170] Figure 29 is a diagram showing an example of dispersion processing by a processing unit in a ray data processing device according to a third embodiment of the present disclosure. Figure 29 shows some measurement points Mp on a spherical surface Sp. Referring to Figure 29, the dispersion processing unit 74 randomly changes the imaging angle A1 indicated by the measurement point Mp within a dispersion range Dmp of ±1 / 2 of the measurement intervals Wθ, Wφ.

[0171] More specifically, the distributed processing unit 74 obtains a random number Rθφ from a predetermined random function. The distributed processing unit 74 updates the imaging angle A1 to an imaging angle A4 determined according to the random number Rθφ in the distributed range Dmp, according to a predetermined algorithm.

[0172] The dispersion processing unit 74 performs dispersion processing for each imaging angle A1 indicated by the ray extraction profile Pr6. The dispersion processing unit 74 generates a dispersed ray extraction profile Pr7 that shows the correspondence between the imaging angle A4 after dispersion processing for imaging angle A1 and the number of extracted rays Ndr at said imaging angle A1. Hereinafter, the imaging angle A4 where the tilt angle α is p° and the rotation angle β is q° will also be referred to as imaging angle A4(p,q).

[0173] Referring again to Figure 26, the dispersion processing unit 74 outputs the generated dispersion ray extraction profile Pr7 to the image synthesis processing unit 73.

[0174] (Generating image G4) The image synthesis processing unit 73 uses multiple images G1 indicated by the image data Dp received from the extraction information generation unit 72 to generate an image G4 obtained when imaging is performed using the detector 51 at the imaging angle A4 indicated by the dispersed ray extraction profile Pr7 received from the distributed processing unit 74.

[0175] Figure 30 is a diagram showing the method of generating an image by the processing unit in the optical data processing device according to the third embodiment of the present disclosure. Figure 30 shows the positional relationship between the measurement points Mp(n,m), Mp(n+1,m), Mp(n,m+1), Mp(n+1,m+1), which are four measurement points Mp corresponding to imaging angles A1(n,m), A1(n+1,m), A1(n+1,m+1), respectively, and a point Pz on the spherical surface Sp corresponding to imaging angle A4(p,q).

[0176] Referring to Figure 30, the image synthesis processing unit 73, for example, refers to the dispersed ray extraction profile Pr7 and the image data Dp to obtain the four imaging angles A1 closest to the imaging angle A4(p,q), namely imaging angles A1(n,m), A1(n+1,m), A1(n,m+1), and A1(n+1,m+1), as well as the images G1(n,m), G1(n+1,m), G1(n,m+1), and G1(n+1,m+1).

[0177] The image synthesis processing unit 73, in the same manner as the image synthesis processing unit 33, sets the contribution rates r(n,m), r(n+1,m), r(n,m+1), r(n+1,m+1), and r(n+1,m+1) respectively, which are the contribution rates r of the imaging angles A1(n,m), A1(n+1,m), A1(n,m+1), A1(n+1,m+1) with respect to the imaging angle A4(p,q), based on the distance Dz between the measurement points Mp(n,m), Mp(n+1,m), Mp(n,m+1), Mp(n+1,m+1) and point Pz.

[0178] More specifically, the image synthesis processing unit 73 sets a contribution rate r for the imaging angle A1 that is proportional to the shortness of the distance Dz between the measurement point Mp and point Pz corresponding to the imaging angle A1, and the sum of the contribution rates r(n,m), r(n+1,m), r(n,m+1), and r(n+1,m+1) is 1.

[0179] The image synthesis processing unit 93 generates image G4 at imaging angle A4(p,q) by adding the pixel intensity pl(a,b) in image G1 for each pixel p according to the following equation (4). G4=G1(n,m)×r(n,m)+G1(n+1,m)×r(n+1,m)+G1(n,m+1)×r(n,m+1)+G1(n+1,m+1)×r(n+1,m+1)...(4)

[0180] The image synthesis processing unit 73 generates an image G4 for each imaging angle A4 and generates image data Dpy that shows the correspondence between the imaging angle A4 and the image G4. Referring again to Figure 26, the image synthesis processing unit 73 outputs the generated image data Dpy and the dispersed ray extraction profile Pr7 received from the dispersion processing unit 74 to the ray data generation unit 34.

[0181] (Generation of ray dataset Dst) The ray data generation unit 34 receives image data Dpy and dispersed ray extraction profile Pr7 from the image synthesis processing unit 73, and generates a ray data set Dst based on the received image data Dpy and dispersed ray extraction profile Pr7.

[0182] More specifically, the ray data generation unit 34 obtains an image G4 from the image data Dpy that corresponds to imaging angle A4, where the number of extracted rays Ndr is 1 or more, by referring to the dispersed ray extraction profile Pr7. The ray data generation unit 34 determines the starting pixel pps in the image G4 by normalizing the pixel intensity pl of the pixels p included in the acquired image G4.

[0183] The ray data generation unit 34 determines the starting pixel pps for each imaging angle A4 for all images G4 corresponding to imaging angle A4 where the number of extracted rays Ndr is 1 or more, following the procedure described above. Subsequently, the ray data generation unit 34 generates starting and ending point information that shows the correspondence between imaging angle A4 and the determined starting pixel pps.

[0184] As described above, the ray data generation unit 34 generates ray data Dr for a number of rays N based on the generated start and end point information, the intensity information received from the light distribution information generation unit 71, and the measurement condition data Dm in the storage unit 20. The ray data generation unit 34 generates a ray dataset Dst containing the ray data Dr for a number of rays N, and stores the generated ray dataset Dst in the storage unit 20.

[0185] [Operation Flow] Figure 31 is a flowchart illustrating an example of the operation procedure when a ray data processing device according to the third embodiment of this disclosure generates a ray data set.

[0186] Referring to Figure 31, first, the ray data processing device 103 receives image data Dp from the light distribution measuring device 201 (step S31).

[0187] Next, the ray data processing device 103 accepts a user operation to specify the number of rays N (step S32).

[0188] Next, the ray data processing device 103 calculates the luminous flux value for each imaging angle A1 based on the image data Dp, and generates a light distribution profile Pr5 that shows the correspondence between the tilt angle α and rotation angle β indicated by the imaging angle A1 and the luminous flux value (step S33).

[0189] Next, the ray data processing device 103 calculates the total luminous flux value TL based on the luminous flux value at each imaging angle A1, and determines the intensity Pw by dividing the total luminous flux value TL by the number of rays N (step S34).

[0190] Next, the ray data processing device 103 determines the number of extracted rays Ndr for each imaging angle A1 based on the light distribution profile Pr5, and generates a ray extraction profile Pr6 that shows the correspondence between the imaging angle A1 and the number of extracted rays Ndr (step S35).

[0191] Next, the ray data processing device 103 performs dispersion processing on each imaging angle A1 indicated by the ray extraction profile Pr6 to generate a dispersed ray extraction profile Pr7 that shows the correspondence between the imaging angle A4 and the number of extracted rays Ndr (step S36).

[0192] Next, the optical data processing device 103 generates an image G4 for each imaging angle A4 using the multiple images G1 indicated by the image data Dp, and generates image data Dpy that shows the correspondence between the imaging angle A4 and the image G4 (step S37).

[0193] Next, the ray data processing device 103 determines the starting pixel pps for each imaging angle A4 based on the dispersed ray extraction profile Pr7 and the image data Dpy, and generates starting and ending point information that shows the correspondence between the imaging angle A4 and the starting pixel pps (step S38).

[0194] Next, the ray data processing device 103 generates a ray dataset Dst, which includes ray data Dr for N rays, based on the start and end point information, intensity Pw, and measurement condition data Dm (step S39).

[0195] Next, other embodiments of the present disclosure will be described with reference to the drawings. In the drawings, the same or corresponding parts are denoted by the same reference numerals, and their descriptions will not be repeated.

[0196] <Fourth Embodiment> [Configuration and Basic Operation] This embodiment relates to a ray data generation system 304 that generates a ray data set Dst using multiple images G5 obtained by imaging the object S at multiple imaging positions that are relatively parallel to the object S, compared to the ray data generation system 301 according to the first embodiment. Except for the contents described below, it is the same as the ray data generation system 301 according to the first embodiment.

[0197] Figure 32 is a diagram showing the configuration of a ray data generation system according to a fourth embodiment of the present disclosure. Referring to Figure 32, the ray data generation system 302, compared to the ray data generation system 301, includes a ray data processing device 104 instead of a ray data processing device 101, and includes a light distribution measuring device 202 instead of a light distribution measuring device 201.

[0198] (Light distribution measuring device) The light distribution measuring device 202 comprises a detector 51, an X-stage 61, a Y-stage 63, and a support base 56. The X-stage 61 includes a table 62 that is movable in a direction parallel to the X-axis. The Y-stage 63 includes a table 64 that is movable in a direction parallel to the Y-axis. The Y-stage 63 is connected to the table 62 of the X-stage 61. The detector 51 is mounted on the table 64 of the Y-stage 63.

[0199] The light distribution measuring device 202 is capable of translating the position of the detector 51 relative to the object S while maintaining the distance L between the object S and the principal point Cp of the detector 51, thereby measuring the near-field light distribution of the object S. More specifically, as the table 62 of the X stage 61 moves in a direction parallel to the X axis, the detector 51 moves in a direction parallel to the X axis. As the table 64 of the Y stage 63 moves in a direction parallel to the Y axis, the detector 51 moves in a direction parallel to the Y axis. In other words, the light distribution measuring device 202 translates the detector 51 in the XY plane. The detector 51 generates an image G5 of the object S by imaging the object S when its principal point Cp is located at one or more measurement points MQ in the XY plane.

[0200] The optical distribution measuring device 202 receives a measurement control command indicating one or more measurement points MQ from a control device or optical ray data processing device 102 (not shown). The X stage 61 and Y stage 63 in the optical distribution measuring device 202 operate according to the measurement control command. The detector 51 generates an image G5 by imaging the object S when its principal point Cp is located at the measurement point MQ indicated by the measurement control command.

[0201] For example, the detector 51 images the object S at multiple measurement points MQ with measurement intervals Wx and Wy specified by the user. The measurement interval Wx is the measurement interval in the X-axis direction, and the measurement interval Wy is the measurement interval in the Y-axis direction. As an example, the detector 51 generates 2601 images G5 by imaging the object S at 2601 (51 × 51) measurement points MQ, which consist of a combination of X coordinates at 0.2 mm intervals in the range from -5 mm to 5 mm and Y coordinates at 0.2 mm intervals in the range from -5 mm to 5 mm.

[0202] The detector 51 generates image data Dq that shows the correspondence between the generated image G5 and the measurement point MQ, which is represented using the X and Y coordinates. The detector 51 also generates measurement condition data Dm that shows the field of view Wa of the image G5 and the distance L between the object S and the principal point Cp of the detector 51. The detector 51 transmits the generated image data Dq and measurement condition data Dm to the ray data processing device 104.

[0203] (Configuration of optical data processing device) Figure 33 shows the configuration of a ray data processing device according to a fourth embodiment of the present disclosure. Referring to Figure 33, the ray data processing device 104, compared to the ray data processing device 101, includes an acquisition unit 80 instead of an acquisition unit 10, and a processing unit 90 instead of a processing unit 30. One or both of the acquisition unit 80 and the processing unit 90 are implemented, for example, by a processing circuit (Circuitry) including one or more processors. The storage unit 20 is, for example, a non-volatile memory included in the above-mentioned processing circuit.

[0204] Figure 34 shows an example of image data acquired by the acquisition unit in the optical ray data processing device according to the fourth embodiment of the present disclosure. Referring to Figure 34, the acquisition unit 80 acquires multiple images G5 obtained by imaging the object S at multiple imaging positions that are relatively translated relative to the object S, and image data Dq that shows the correspondence between the imaging positions. More specifically, the acquisition unit 80 receives the X and Y coordinates indicating the measurement point MQ and the image data Dq that shows the correspondence between the image G5 from the optical distribution measuring device 202. The acquisition unit 80 also receives measurement condition data Dm from the optical distribution measuring device 202. The acquisition unit 80 stores the received image data Dq and measurement condition data Dm in the storage unit 20.

[0205] The processing unit 90 generates a ray dataset Dst, which shows the starting point and vector of the rays emitted from the object S, based on the image data Dq acquired by the acquisition unit 80. More specifically, the processing unit 90 accepts a user operation to specify the number of rays N. The processing unit 90 generates a ray dataset Dst, which includes the specified number of rays N, in accordance with the accepted user operation.

[0206] Figure 35 shows an example of a method for generating a ray data set by a generation unit in a ray data processing device according to a fourth embodiment of the present disclosure. Figure 35 shows the positional relationship between the detector 51 in the XZ plane and the imaging plane Is of the detector 51. The imaging plane Is is a plane on the XY plane that is perpendicular to the line passing through the object S and the principal point Cp.

[0207] Referring to Figure 35, the processing unit 90 determines the starting pixel pps, which is the pixel p that should be the starting point of the light ray, based on the number of light rays N and the intensity of each pixel p in the multiple images G5. The processing unit 90 calculates the coordinates of the starting pixel pps in a three-dimensional polar coordinate system based on the field of view Wa indicated by the measurement condition data Dm in the storage unit 20. The processing unit 90 determines the starting coordinates Ps(x,y,z) based on the calculated coordinates of the starting pixel pps. The starting coordinates Ps(x,y,z) are the coordinates on the imaging plane Is.

[0208] Furthermore, the processing unit 90 calculates the coordinates of the principal point Cp in the three-dimensional polar coordinate system based on the distance L indicated by the measurement point MQ and measurement condition data Dm corresponding to the image G5. Based on the calculated coordinates of the principal point Cp, the processing unit 90 determines the endpoint coordinates Pe(x,y,z). Then, the processing unit 30 determines the ray vector Vt as the vector pointing from the determined starting point coordinates Ps(x,y,z) to the determined endpoint coordinates Pe(x,y,z).

[0209] Furthermore, the processing unit 90 calculates the total luminous flux value TL of the object S based on all the images G5 indicated by the image data Dq. The processing unit 90 calculates the luminous flux value per ray by dividing the calculated total luminous flux value TL by the number of rays N. The processing unit 90 determines the calculated luminous flux value per ray as the intensity Pw of the ray data Dr.

[0210] The processing unit 90 generates ray data Dr, which represents the determined starting point coordinates Ps(x,y,z), the determined ray vector Vt, and the determined intensity. The processing unit 90 generates N ray data Drs and generates a ray dataset Dst containing the N ray data Drs. The details of the processing in the processing unit 90 are described below.

[0211] (Generating the Pr8 light distribution profile) When the image data Dq is stored in the storage unit 20 by the acquisition unit 80, the processing unit 90 acquires the image data Dq. The processing unit 90 calculates the luminosity at each measurement point Mq indicated by the image data Dq. More specifically, the processing unit 90 calculates the sum of the intensities of each pixel p in the image G5 corresponding to the measurement point Mq as the luminosity at that measurement point Mq. The processing unit 90 calculates the luminosity for each measurement point Mq.

[0212] The processing unit 90 calculates the luminous flux value for each measurement point MQ, for example, in accordance with the Japanese Industrial Standard (JIS C 8105-5). Since the measurement point MQ is located on a plane, the processing unit 90 calculates the luminous flux value for the measurement point MQ without multiplying the luminous intensity at the measurement point MQ by the spherical coefficient.

[0213] Figure 36 shows an example of a light distribution profile generated by the generation unit in the ray data processing device according to the fourth embodiment of the present disclosure. Referring to Figure 36, the processing unit 90 calculates the luminous flux value for each measurement point MQ and generates a light distribution profile Pr8 that shows the correspondence between the X and Y coordinates representing the measurement point MQ and the luminous flux value.

[0214] Furthermore, the processing unit 90 calculates the total luminous flux value TL of the object S based on the luminous flux value at each measurement point MQ, for example, in accordance with the Japanese Industrial Standard (JIS C 8105-5). The processing unit 90 determines the intensity Pw as the value obtained by dividing the calculated total luminous flux value TL by the number of rays N.

[0215] (Generation of ray extraction profile Pr9) Figure 37 shows an example of a ray extraction profile generated by the generation unit in the ray data processing device according to the fourth embodiment of the present disclosure. Referring to Figure 37, the processing unit 90 determines the number of extracted rays Ndr for each measurement point MQ based on the optical distribution profile Pr8.

[0216] For example, the processing unit 90 determines the number of rays extracted Ndr for each measurement point MQ by normalizing the luminous flux value of each measurement point MQ shown in the optical distribution profile Pr8. More specifically, the processing unit 90 calculates the sum Fc of the luminous flux values ​​of each measurement point MQ shown in the optical distribution profile Pr8. Then, the processing unit 90 determines the number of rays extracted Ndr for that measurement point MQ by multiplying the luminous flux value of the measurement point MQ shown in the optical distribution profile Pr8 by (number of rays N / sum Fc).

[0217] The processing unit 90 determines the number of extracted rays Ndr for each measurement point MQ and generates a ray extraction profile Pr9 that shows the correspondence between the measurement point MQ and the number of extracted rays Ndr.

[0218] (Generating start and end point information) The processing unit 90 determines the starting pixel pps for each measurement point MQ based on the image data Dq and the ray extraction profile Pr9.

[0219] For example, the processing unit 90 determines the starting pixel pps in image G5 by normalizing the intensity of each pixel p contained in the image G5. More specifically, the processing unit 90 calculates the sum Fq of the intensities of each pixel p in image G5 corresponding to the measurement point MQ. Then, the processing unit 90 determines the number of rays originating from pixel p as the value obtained by multiplying the intensity of pixel p in image G5 by (number of extracted rays Ndr / sum Fq). In other words, if the value obtained by multiplying the intensity of pixel p by (number of extracted rays Ndr / sum Fq) is 1 or greater, the processing unit 90 determines that pixel p to be the starting pixel pps.

[0220] The processing unit 90 generates start-end point information that shows the correspondence between the identifier of the measurement point MQ and the identifier of the determined start point pixel pps.

[0221] (Generation of ray dataset Dst) The processing unit 90 generates ray data Dr for the number of rays N based on the start and end point information, intensity information, and measurement condition data Dm in the storage unit 20.

[0222] More specifically, the processing unit 90 obtains an identifier for the measurement point MQ and identifiers for one or more starting point pixels pps corresponding to the measurement point MQ from the start and end point information.

[0223] The processing unit 90 calculates the coordinates of the principal point Cp in the 3D polar coordinate system based on the X and Y coordinates indicated by the acquired measurement point MQ, and the distance L indicated by the measurement condition data Dm. The processing unit 30 determines the calculated coordinates of the principal point Cp as the endpoint coordinates Pe(x,y,z).

[0224] Furthermore, the processing unit 90 calculates the coordinates of the starting pixel pps in a three-dimensional polar coordinate system based on the pixel position of the acquired starting pixel pps and the field of view Wa indicated by the measurement condition data Dm. The processing unit 90 determines the calculated coordinates of the starting pixel pps as the starting coordinates Ps(x,y,z).

[0225] The processing unit 90 determines the ray vector Vt as a vector pointing from the determined starting coordinates Ps(x,y,z) to the determined ending coordinates Pe(x,y,z). Then, the processing unit 90 generates ray data Dr that shows the determined starting coordinates Ps(x,y,z), the determined ray vector Vt, and the intensity Pw indicated by the intensity information.

[0226] If there are multiple starting point pixels pps corresponding to the measurement point MQ, the processing unit 90 determines the starting point coordinates Ps(x,y,z) and the ray vector Vt for each starting point pixel pps, and generates ray data Dr.

[0227] The processing unit 90 determines the starting coordinates Ps(x,y,z) and generates ray data Dr for all starting pixels pps corresponding to the measurement point MQ. Then, it obtains a new identifier for the measurement point MQ and a new identifier for the starting pixels pps from the starting and ending point information, determines the starting coordinates Ps(x,y,z) and ray vector Vt, and generates ray data Dr.

[0228] Once the processing unit 90 has finished generating ray data Dr for all pairs of measurement points MQ and starting point pixels pps in the start-end point information, it generates a ray dataset Dst containing the ray data Dr for the number of rays N. The processing unit 90 then stores the generated ray dataset Dst in the storage unit 20.

[0229] [Operation Flow] Figure 38 is a flowchart illustrating an example of the operation procedure when a ray data processing device according to the fourth embodiment of this disclosure generates a ray data set.

[0230] Referring to Figure 38, first, the ray data processing device 104 receives image data Dq from the light distribution measuring device 202 (step S41).

[0231] Next, the ray data processing device 104 accepts a user operation to specify the number of rays N (step S42).

[0232] Next, the ray data processing device 104 calculates the luminous flux value for each measurement point MQ based on the image data Dq, and generates a light distribution profile Pr8 that shows the correspondence between the X and Y coordinates indicated by the measurement point MQ and the luminous flux value (step S43).

[0233] Next, the ray data processing device 104 calculates the total luminous flux value TL based on the luminous flux value at each measurement point MQ, and determines the intensity Pw by dividing the total luminous flux value TL by the number of rays N (step S24).

[0234] Next, the ray data processing device 104 determines the number of extracted rays Ndr for each measurement point MQ based on the light distribution profile Pr8, and generates a ray extraction profile Pr9 that shows the correspondence between the measurement point MQ and the number of extracted rays Ndr (step S45).

[0235] Next, the ray data processing device 104 determines the starting pixel pps for each measurement point MQ based on the ray extraction profile Pr9, and generates start and end point information showing the correspondence between the measurement point MQ and the starting pixel pps (step S46).

[0236] Next, the ray data processing device 104 generates a ray dataset Dst containing ray data Dr for a number of rays N, based on the start and end point information and intensity Pw (step S47).

[0237] In the fourth embodiment of the present disclosure, the ray data generation system 302 is configured such that the light distribution measuring device 202 images the object S at multiple measurement points Mq by translating the detector 51 in the XY plane, but it is not limited to this configuration. The light distribution measuring device 202 may also be configured such that the detector 51 is fixed and the object S is translated in the XY plane to image the object S at multiple measurement points Mq. In this case, the ray data processing device 104 converts the amount of movement of the object S in the XY plane into the amount of relative movement of the detector 51 with respect to the object S, and then determines the endpoint coordinates Pe(x,y,z) and the starting point coordinates Ps(x,y,z).

[0238] Furthermore, in the ray data processing device 104 according to the fourth embodiment of this disclosure, the processing unit 90 may, in the same manner as the processing unit 30, generate a high-resolution optical distribution profile based on the optical distribution profile Pr8, showing the luminous flux value at measurement point MQ and the luminous flux value at measurement points where the measurement intervals Wx and Wy are smaller than those at measurement point MQ, and generate a ray data set Dst based on the high-resolution optical distribution profile.

[0239] Furthermore, in the optical data processing device 104 according to the fourth embodiment of this disclosure, the processing unit 90 may be configured to generate an image of the object S at a measurement point different from the measurement point MQ based on the image data Dq, in the same manner as the processing units 30, 40, and 70, and to determine the starting point coordinates Ps(x,y,z) based on the pixel positions of the generated image.

[0240] The embodiments described above should be considered in all respects to be illustrative and not restrictive. The scope of the present invention is indicated by the claims rather than the above description, and all modifications within the meaning and scope equivalent to the claims are intended to be included.

[0241] Each process (each function) of the above-described embodiment is implemented by a processing circuit (Circuitry) including one or more processors. The processing circuit may consist of one or more memories, various analog circuits, various digital circuits, etc., in addition to the one or more processors, as well as an integrated circuit. The one or more memories store programs (instructions) that cause the one or more processors to execute each of the above processes. The one or more processors may execute each of the above processes according to the programs read from the one or more memories, or they may execute each of the above processes according to logic circuits that have been pre-designed to execute each of the above processes. The processors may be various processors suitable for computer control, such as a CPU (Central Processing Unit), GPU (Graphics Processing Unit), DSP (Digital Signal Processor), FPGA (Field Programmable Gate Array), and ASIC (Application Specific Integrated Circuit). Furthermore, the physically separated multiple processors may cooperate with each other to execute each of the above processes. For example, the processors installed in each of several physically separated computers may cooperate with each other via a network such as a LAN (Local Area Network), WAN (Wide Area Network), and the Internet to perform the above processes. The program may be installed in the memory via the network from an external server device, or it may be distributed on a recording medium such as a CD-ROM (Compact Disc Read Only Memory), DVD-ROM (Digital Versatile Disk Read Only Memory), and semiconductor memory, and then installed in the memory from the recording medium. [Explanation of Symbols]

[0242] 10,80 Acquisition Department 20 Memory section 30, 40, 70, 90 Processing Unit 31, 41, 71 Light Distribution Information Generation Unit 32, 42, 72 Extracted Information Generation Unit 33, 43, 73 Image Composition Processing Unit 34 Ray Data Generation Unit 74 Dispersion Processing Unit 51 Detector 52 First Arm 53 Second Arm 54 First Motor 55 Second Motor 56 Support Stand 61 X Stage 62, 64 Table 63 Y Stage 101, 102, 103, 104 Ray Data Processing Device 201, 202 Light Distribution Measurement Device<​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​

Claims

1. A ray data processing device that generates a ray data set used for calculating the light distribution characteristics of an object, An acquisition unit acquires multiple images obtained by imaging the object at multiple imaging angles and image data showing the correspondence between the imaging angles, The system comprises a generation unit that generates a ray dataset showing the starting point and vector of the light rays emitted from the object, based on the image data acquired by the acquisition unit, The generation unit generates a light distribution profile based on the image data, showing the light flux value at each of the imaging angles and the light flux value at an interpolated imaging angle different from the imaging angle, and generates the ray dataset based on the light distribution profile. The generating unit determines a number of the vectors having endpoints determined based on the interpolated imaging angle, the number of vectors corresponding to the light flux value at the interpolated imaging angle, and generates the ray data set representing the determined vectors.

2. A ray data processing device that generates a ray data set used for calculating the light distribution characteristics of an object, An acquisition unit acquires multiple images obtained by imaging the object at multiple imaging angles and image data showing the correspondence between the imaging angles, The system comprises a generation unit that generates a ray dataset showing the starting point and vector of the light rays emitted from the object, based on the image data acquired by the acquisition unit, The generation unit generates a light distribution profile based on the image data, showing the light flux value at each of the imaging angles and the light flux value at an interpolated imaging angle different from the imaging angle, and generates the ray dataset based on the light distribution profile. The generation unit generates an interpolated image which is an image of the object at the interpolated imaging angle based on the image data, determines the starting point based on the pixel position of the pixels in the interpolated image, and generates the ray data set indicating the determined starting point, in a ray data processing device.

3. A ray data processing device that generates a ray dataset used for calculating the light distribution characteristics of an object, An acquisition unit acquires multiple images obtained by imaging the object at multiple imaging angles and image data showing the correspondence between the imaging angles, The system comprises a generation unit that generates a ray dataset showing the starting point and vector of the light rays emitted from the object, based on the image data acquired by the acquisition unit, The generation unit generates an interpolated image, which is an image of the object at a target angle different from the imaging angle, based on the image data, determines the starting point based on the pixel position of the pixels in the interpolated image, and generates the ray dataset indicating the determined starting point. The generation unit obtains from the image data a plurality of calculation imaging angles, which are the plurality of imaging angles that are closest to the target angle among the plurality of imaging angles, and a plurality of calculation images, which are the plurality of images corresponding to each of the plurality of calculation imaging angles. The generating unit generates the interpolated image by multiplying the pixel intensity in the calculation image by a coefficient corresponding to the distance between the imaging position corresponding to the calculation imaging angle and the imaging position corresponding to the target angle, and adding the pixel intensities of the plurality of calculation images multiplied by the coefficient for each pixel.

4. A ray data processing device that generates a ray data set used for calculating the light distribution characteristics of an object, An acquisition unit acquires multiple images obtained by imaging the object at multiple imaging angles and image data showing the correspondence between the imaging angles, The system comprises a generation unit that generates a ray dataset showing the starting point and vector of the light rays emitted from the object, based on the image data acquired by the acquisition unit, The generation unit generates an interpolated image, which is an image of the object at a target angle different from the imaging angle, based on the image data, determines the starting point based on the pixel position of the pixels in the interpolated image, and generates the ray dataset indicating the determined starting point. The acquisition unit acquires the image data that shows the correspondence between the plurality of images and the imaging angle represented using a first coordinate system defined in Japanese Industrial Standards (JIS C 8105-5), The generation unit generates the interpolated image at the target angle, which is represented using a second coordinate system different from the first coordinate system, as defined in the Japanese Industrial Standard (JIS C 8105-5), based on the image data.

5. A ray data processing device that generates a ray data set used for calculating the light distribution characteristics of an object, An acquisition unit acquires multiple images obtained by imaging the object at multiple imaging angles and image data showing the correspondence between the imaging angles, The system comprises a generation unit that generates a ray dataset showing the starting point and vector of the light rays emitted from the object, based on the image data acquired by the acquisition unit, The generation unit generates an interpolated image, which is an image of the object at a target angle different from the imaging angle, based on the image data, determines the starting point based on the pixel position of the pixels in the interpolated image, and generates the ray dataset indicating the determined starting point. The aforementioned optical data processing device further, The system includes a distribution unit that performs a distributed processing to randomly change at least one of the plurality of imaging angles in the image data, The generation unit is a ray data processing device that generates the interpolated image at the target angle, which is the imaging angle after the distributed processing.

6. A method for processing light data in a light data processing device that generates a light data set used for calculating the light distribution characteristics of an object, The steps include acquiring image data that shows the correspondence between multiple images obtained by imaging the object at multiple imaging angles and the imaging angles, The process includes the step of generating a ray dataset that shows the starting point and vector of the light rays emitted from the object, based on the acquired image data, In the step of generating the ray dataset, a light distribution profile is generated based on the image data, showing the luminous flux value at each imaging angle and the luminous flux value at an interpolated imaging angle different from the imaging angle, and the ray dataset is generated based on the light distribution profile. A ray data processing method comprising the step of generating the ray dataset, which involves determining a number of vectors having endpoints determined based on the interpolation imaging angle, the number of vectors corresponding to the luminous flux value at the interpolation imaging angle, and generating the ray dataset showing the determined vectors.

7. A method for processing ray data in a ray data processing device that generates a ray data set used for calculating the light distribution characteristics of an object, The steps include acquiring image data that shows the correspondence between multiple images obtained by imaging the object at multiple imaging angles and the imaging angles, The process includes the step of generating a ray dataset that shows the starting point and vector of the light rays emitted from the object, based on the acquired image data, In the step of generating the ray dataset, a light distribution profile is generated based on the image data, showing the luminous flux value at each imaging angle and the luminous flux value at an interpolated imaging angle different from the imaging angle, and the ray dataset is generated based on the light distribution profile. A ray data processing method comprising the steps of generating the ray dataset, generating an interpolated image which is an image of the object at the interpolated imaging angle based on the image data, determining the starting point based on the pixel position of the pixels in the interpolated image, and generating the ray dataset indicating the determined starting point.

8. A method for processing light data in a light data processing device that generates a light data set used for calculating the light distribution characteristics of an object, The steps include acquiring image data that shows the correspondence between multiple images obtained by imaging the object at multiple imaging angles and the imaging angles, The process includes the step of generating a ray dataset that shows the starting point and vector of the light rays emitted from the object, based on the acquired image data, In the step of generating the ray dataset, an interpolated image is generated based on the image data, which is an image of the object at a target angle different from the imaging angle; the starting point is determined based on the pixel position of the pixels in the interpolated image; and the ray dataset indicating the determined starting point is generated. In the step of generating the ray dataset, from the image data, a plurality of calculation imaging angles are obtained, which are a plurality of imaging angles that are closest to the target angle among the plurality of imaging angles, and a plurality of calculation images are a plurality of images that correspond to each of the plurality of calculation imaging angles. A ray data processing method comprising the step of generating the ray data set, wherein the pixel intensity in the calculation image is multiplied by a coefficient corresponding to the distance between the imaging position corresponding to the calculation imaging angle and the imaging position corresponding to the target angle, and the pixel intensities of the plurality of calculation images multiplied by the coefficient are added pixel by pixel to generate the interpolated image.

9. A method for processing ray data in a ray data processing device that generates a ray data set used for calculating the light distribution characteristics of an object, The steps include acquiring image data that shows the correspondence between multiple images obtained by imaging the object at multiple imaging angles and the imaging angles, The process includes the step of generating a ray dataset that shows the starting point and vector of the light rays emitted from the object, based on the acquired image data, In the step of generating the ray dataset, an interpolated image is generated based on the image data, which is an image of the object at a target angle different from the imaging angle; the starting point is determined based on the pixel position of the pixels in the interpolated image; and the ray dataset indicating the determined starting point is generated. In the step of acquiring the image data, the image data is acquired that shows the correspondence between the plurality of images and the imaging angle represented using a first coordinate system defined in the Japanese Industrial Standard (JIS C 8105-5). A ray data processing method comprising the step of generating the ray data set, wherein, based on the image data, an interpolated image at the target angle is generated using a second coordinate system different from the first coordinate system as defined in the Japanese Industrial Standard (JIS C 8105-5).

10. A method for processing light data in a light data processing device that generates a light data set used for calculating the light distribution characteristics of an object, The steps include acquiring image data that shows the correspondence between multiple images obtained by imaging the object at multiple imaging angles and the imaging angles, The process includes the step of generating a ray dataset that shows the starting point and vector of the light rays emitted from the object, based on the acquired image data, In the step of generating the ray dataset, an interpolated image is generated based on the image data, which is an image of the object at a target angle different from the imaging angle; the starting point is determined based on the pixel position of the pixels in the interpolated image; and the ray dataset indicating the determined starting point is generated. The aforementioned optical data processing method further includes: The process includes a step of performing a distributed processing to randomly change at least one of the plurality of imaging angles in the image data, A ray data processing method comprising the step of generating the ray dataset, which generates the interpolated image at the target angle, which is the imaging angle after the dispersion processing.

11. A ray data processing program used in a ray data processing device that generates a ray dataset used for calculating the light distribution characteristics of an object, Computers, An acquisition unit acquires multiple images obtained by imaging the object at multiple imaging angles and image data showing the correspondence between the imaging angles, Based on the image data acquired by the acquisition unit, a generation unit generates a ray dataset indicating the starting point and vector of the light rays emitted from the object. It is a program designed to function as such. The generation unit generates a light distribution profile based on the image data, showing the light flux value at each of the imaging angles and the light flux value at an interpolated imaging angle different from the imaging angle, and generates the ray dataset based on the light distribution profile. The generation unit is a ray data processing program that determines a number of the vectors having endpoints determined based on the interpolation imaging angle, the number of vectors corresponding to the luminous flux value at the interpolation imaging angle, and generates a ray dataset showing the determined vectors.

12. A ray data processing program used in a ray data processing device that generates a ray data set used for calculating the light distribution characteristics of an object, Computers, An acquisition unit acquires multiple images obtained by imaging the object at multiple imaging angles and image data showing the correspondence between the imaging angles, Based on the image data acquired by the acquisition unit, a generation unit generates a ray dataset indicating the starting point and vector of the light rays emitted from the object. It is a program designed to function as such. The generation unit generates a light distribution profile based on the image data, showing the light flux value at each of the imaging angles and the light flux value at an interpolated imaging angle different from the imaging angle, and generates the ray dataset based on the light distribution profile. The generation unit is a ray data processing program that generates an interpolated image, which is an image of the object at the interpolated imaging angle, based on the image data, determines the starting point based on the pixel position of the pixels in the interpolated image, and generates a ray data set indicating the determined starting point.

13. A ray data processing program used in a ray data processing device that generates a ray dataset used for calculating the light distribution characteristics of an object, Computers, An acquisition unit acquires multiple images obtained by imaging the object at multiple imaging angles and image data showing the correspondence between the imaging angles, Based on the image data acquired by the acquisition unit, a generation unit generates a ray dataset indicating the starting point and vector of the light rays emitted from the object. It is a program designed to function as such. The generation unit generates an interpolated image, which is an image of the object at a target angle different from the imaging angle, based on the image data, determines the starting point based on the pixel position of the pixels in the interpolated image, and generates the ray dataset indicating the determined starting point. The generation unit obtains from the image data a plurality of calculation imaging angles, which are the plurality of imaging angles that are closest to the target angle among the plurality of imaging angles, and a plurality of calculation images, which are the plurality of images corresponding to each of the plurality of calculation imaging angles. The generation unit is a ray data processing program that generates the interpolated image by multiplying the pixel intensity in the calculation image by a coefficient corresponding to the distance between the imaging position corresponding to the calculation imaging angle and the imaging position corresponding to the target angle, and adding the pixel intensities of the plurality of calculation images multiplied by the coefficient for each pixel.

14. A ray data processing program used in a ray data processing device that generates a ray data set used for calculating the light distribution characteristics of an object, Computers, An acquisition unit acquires multiple images obtained by imaging the object at multiple imaging angles and image data showing the correspondence between the imaging angles, Based on the image data acquired by the acquisition unit, a generation unit generates a ray dataset indicating the starting point and vector of the light rays emitted from the object. It is a program designed to function as such. The generation unit generates an interpolated image, which is an image of the object at a target angle different from the imaging angle, based on the image data, determines the starting point based on the pixel position of the pixels in the interpolated image, and generates the ray dataset indicating the determined starting point. The acquisition unit acquires the image data that shows the correspondence between the plurality of images and the imaging angle represented using a first coordinate system defined in Japanese Industrial Standards (JIS C 8105-5), The generation unit is a ray data processing program that generates the interpolated image at the target angle, based on the image data, using a second coordinate system different from the first coordinate system as defined in the Japanese Industrial Standard (JIS C 8105-5).

15. A ray data processing program used in a ray data processing device that generates a ray data set used for calculating the light distribution characteristics of an object, Computers, An acquisition unit acquires multiple images obtained by imaging the object at multiple imaging angles and image data showing the correspondence between the imaging angles, Based on the image data acquired by the acquisition unit, a generation unit generates a ray dataset indicating the starting point and vector of the light rays emitted from the object. It is a program designed to function as such. The generation unit generates an interpolated image, which is an image of the object at a target angle different from the imaging angle, based on the image data, determines the starting point based on the pixel position of the pixels in the interpolated image, and generates the ray dataset indicating the determined starting point. The aforementioned optical data processing program further, Computers, A distribution unit performs a distributed processing that randomly changes at least one of the plurality of imaging angles in the image data. It is a program designed to function as such. The generation unit is a ray data processing program that generates the interpolated image at the target angle, which is the imaging angle after the distributed processing.

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