Light ray data processing device, light ray data processing method, and light ray data processing program

Abstract

Generate a ray data set to determine more accurate light distribution characteristics of an object. [Solution] A ray data processing device includes an acquisition unit that acquires multiple images obtained by imaging an object at multiple imaging angles at a predetermined interval and image data showing the correspondence between the imaging angles; a generation unit that generates a ray data set that shows the starting points and vectors of light rays emanating from the object based on the image data; and a first distribution unit that performs a first distribution process that randomly changes at least one of the multiple imaging angles in the image data, and the generation unit determines the end points of the vectors based on the imaging angles after the first distribution process, and generates the ray data set that shows the determined vectors.

Description

[Technical Field]

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

[0002] Conventionally, technologies for generating data used to calculate the light distribution characteristics of an object such as a light source have been developed. For example, Patent Document 1 (JP 2015-132866 A) discloses the following light ray model generation method. That is, the light ray model generation method converts the near-field distribution of light from a light source into a light ray model used in a Monte Carlo simulation, in which light from the light source is measured with a near-field measurement device and near-field measurement data is input, and the input near-field measurement data is used to generate a light ray model used in the Monte Carlo simulation by using a uniform sampling method with respect to the position of the light source and an importance sampling method to generate light rays in the direction at that position. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2015-132866 Summary of the Invention [Problem to be solved by the invention]

[0004] There is a need for a technique that goes beyond the technique described in Patent Document 1 and that is capable of generating a light ray data set for determining a more accurate light distribution characteristic of an object.

[0005] The present disclosure has been made to solve the above-mentioned problems, and its purpose is to provide a ray data processing device, a ray data processing method, and a ray data processing program that are capable of generating a ray data set for determining 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 dataset used to calculate the light distribution characteristics of an object, and includes: an acquisition unit that acquires image data indicating a correspondence between a plurality of images obtained by imaging the object at a plurality of imaging angles at a predetermined interval and the imaging angles; a generation unit that generates the ray dataset indicating the starting point and vector of a ray of light emanating from the object based on the image data acquired by the acquisition unit; and a first distribution unit that performs a first distribution process that randomly changes at least one of the plurality of imaging angles in the image data, and the generation unit determines the end point of the vector based on the imaging angle after the first distribution process in the first distribution unit, and generates the ray dataset indicating the determined vector.

[0007] In this way, by randomly changing the imaging angle indicated by the image data and determining the end points of the ray vectors based on the changed imaging angle, it is possible to reduce the regularity in the intensity distribution of light emitted from the object that arises due to the intervals between imaging angles in the light distribution characteristic of the object obtained by calculation using the light ray dataset, thereby generating a light ray dataset for determining a more accurate light distribution characteristic of the object.

[0008] (2) In the above (1), the first distribution unit may randomly change the imaging angle within a range of ±½ of the predetermined interval centered on the imaging angle.

[0009] With this configuration, it is possible to reduce the regularity of the light distribution characteristic without significantly reducing the accuracy of the light distribution characteristic of the object obtained by calculation using the light ray data set.

[0010] (3) A ray data processing device according to an embodiment of the present disclosure is a ray data processing device that generates a ray dataset used to calculate the light distribution characteristics of an object, and includes: an acquisition unit that acquires image data indicating a correspondence between an image obtained by imaging the object at a predetermined imaging angle and the imaging angle; a generation unit that generates the ray dataset indicating the starting point and vector of a ray of light emitted from the object based on the image data acquired by the acquisition unit; and a second distribution unit that performs a second distribution process that randomly changes the pixel position of at least one of a plurality of pixels in the image of the image data, and the generation unit determines the starting point based on the pixel position of the pixel after the second distribution process, and generates the ray dataset indicating the determined starting point.

[0011] In this way, by randomly changing the pixel positions of pixels in an image and determining the starting points of light rays based on the changed pixel positions, it is possible to reduce the regularity in the intensity distribution of light emitted from an object that arises due to pixel pitch in the light distribution characteristics of the object obtained by calculation using a light ray dataset.As a result, it is possible to generate a light ray dataset for determining a more accurate light distribution characteristic of the object.

[0012] (4) In the above (3), the second distribution unit may randomly change the pixel position of the pixel within a range of ±½ of a pixel size centered on the pixel position of the pixel.

[0013] With this configuration, it is possible to reduce the regularity of the light distribution characteristic without significantly reducing the accuracy of the light distribution characteristic of the object obtained by calculation using the light ray data set.

[0014] (5) A ray data processing device according to an embodiment of the present disclosure is a ray data processing device that generates a ray dataset used to calculate the light distribution characteristics of an object, and includes: an acquisition unit that acquires an image obtained by imaging the object at a predetermined imaging angle and image data indicating a correspondence with the imaging angle; and a generation unit that generates the ray dataset indicating the starting points and vectors of rays of light emitted from the object based on the image data acquired by the acquisition unit. The generation unit creates a pixel number array in which pixel numbers of pixels in the image are arranged, and an accumulated accumulation array in which accumulated accumulated values ​​of the intensities of the pixels are arranged in accordance with the arrangement order of the pixel numbers in the pixel number array, determines the starting point based on the pixel position of the pixel corresponding to a value randomly determined in a numerical range between a plurality of the accumulated accumulated values ​​in the accumulated accumulation array, and generates the ray dataset indicating the determined starting point.

[0015] In this way, by determining the starting point of a ray based on the pixel position of a pixel corresponding to a randomly determined value within a numerical range between the multiple cumulative integrated values ​​in the cumulative integrated array, it is possible to determine the starting point of a ray from the pixel position of a pixel selected randomly while taking pixel intensity into consideration, compared to, for example, a configuration in which the starting point of a ray is determined from the pixel position of a pixel uniformly selected based on intensity from among multiple pixels included in an image. Therefore, in the light distribution characteristic of an object obtained by calculation using the light ray dataset, it is possible to prevent the boundary between areas where the intensity of light emitted from the object is high and areas where it is low from being unnaturally emphasized. Therefore, it is possible to generate a light ray dataset for determining the light distribution characteristic of an object more accurately.

[0016] (6) In the above (5), the generating unit may generate the pixel number array in which the pixel numbers are randomly arranged.

[0017] With this configuration, a cumulative integration array that has little correlation with pixel position can be generated, and the starting point corresponding to a randomly determined value can be determined by referring to the cumulative integration array.Therefore, in cases where there is a bias in the randomly determined values, the impact of the bias on the determination of the starting point can be reduced.

[0018] (7) In (5) or (6) above, the generation unit may divide the range between the minimum and maximum cumulative integrated values ​​in the cumulative integrated array into a plurality of numerical ranges, and determine the starting point based on the pixel position of the pixel corresponding to a randomly determined value in each of the numerical ranges.

[0019] With this configuration, the starting point can be determined for each numerical range based on randomly determined values, so that if there is a bias in the randomly determined values, the impact of that bias on the determination of the starting point can be reduced.

[0020] (8) A ray data processing device according to an embodiment of the present disclosure is a ray data processing device that generates a ray dataset used to calculate the light distribution characteristics of an object, and includes: an acquisition unit that acquires multiple images obtained by imaging the object at multiple imaging angles and image data indicating a correspondence between the imaging angles; and a generation unit that generates the ray dataset indicating the starting points and vectors of rays of light emitted from the object based on the image data acquired by the acquisition unit. The generation unit creates an imaging number array in which the angle numbers of the imaging angles are arranged, and an accumulated accumulation array in which the accumulated accumulated values ​​of the luminous flux values ​​at the imaging angles are arranged in the order in which the angle numbers are arranged in the imaging number array, determines the end point of the vector based on the imaging angle corresponding to a value randomly determined in a numerical range between the multiple accumulated accumulated values ​​in the accumulated accumulation array, and generates the ray dataset indicating the determined vector.

[0021] In this way, by determining the end point of a ray vector based on an imaging angle corresponding to a randomly determined value within a numerical range between the multiple cumulative integrated values ​​in the cumulative integrated array, compared to, for example, a configuration in which the end point is determined based on an imaging angle selected uniformly from multiple imaging angles according to the luminous flux value, it is possible to determine the end point based on an imaging angle that is irregularly selected while taking into account the luminous flux value at the imaging angle. Therefore, in the light distribution characteristic of an object obtained by calculation using the light ray dataset, it is possible to prevent band-like stripes from appearing in the distribution of the intensity of light emitted from the object. Therefore, it is possible to generate a light ray dataset for determining a more accurate light distribution characteristic of the object.

[0022] (9) In the above (8), the generating unit may generate the imaging number sequence in which the angle numbers are randomly arranged.

[0023] With this configuration, a cumulative integration array that has little correlation with the imaging angle can be generated, and the end point corresponding to a randomly determined value can be determined by referring to the cumulative integration array.Therefore, in the case where there is a bias in the randomly determined values, the impact of the bias on the determination of the end point can be reduced.

[0024] (10) In the above (8) or (9), the generation unit may divide the range between the minimum and maximum values ​​of the cumulative integrated values ​​in the cumulative integrated array into a plurality of numerical ranges, and determine the end point of the vector based on the imaging angle corresponding to a randomly determined value in each of the numerical ranges.

[0025] With this configuration, the endpoint can be determined for each numerical range based on randomly determined values, so that if there is a bias in the randomly determined values, the impact of that bias on the determination of the endpoint can be reduced.

[0026] (11) 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 to calculate the light distribution characteristics of an object, and includes an acquisition unit that acquires multiple images obtained by capturing images of the object at multiple imaging positions that are translated relative to the object, and image data that indicates a correspondence between the images and the imaging positions, and a generation unit that generates the ray data set that indicates the starting points and vectors of light rays emitted from the object based on the image data acquired by the acquisition unit.

[0027] In this way, by configuring a ray data set to be generated based on multiple images obtained at multiple imaging positions translated relative to the object, it is possible to generate a ray data set of an object with a narrow light distribution, such as a laser, with a simple configuration. Furthermore, compared to a configuration in which a ray data set is generated based on multiple images obtained by imaging the object at multiple imaging positions using, for example, a goniometer, it is possible to generate a ray data set based on images at imaging positions with higher accuracy. Therefore, it is possible to generate a ray data set for determining the light distribution characteristics of the object more accurately.

[0028] (12) 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 to calculate the light distribution characteristics of an object, the method including the steps of: acquiring image data indicating a correspondence between a plurality of images obtained by imaging the object at a plurality of imaging angles at a predetermined interval and the imaging angles; generating the ray data set indicating the start points and vectors of light rays emanating from the object based on the acquired image data; and performing a first distribution process that randomly changes at least one of the plurality of imaging angles in the image data; and in the step of generating the ray data set, determining an end point of the vector based on the imaging angle after the first distribution process, and generating the ray data set indicating the determined vector.

[0029] In this way, by randomly changing the imaging angle indicated by the image data and determining the end points of the ray vectors based on the changed imaging angle, it is possible to reduce the regularity in the intensity distribution of light emitted from the object that arises due to the intervals between imaging angles in the light distribution characteristic of the object obtained by calculation using the light ray dataset, thereby generating a light ray dataset for determining a more accurate light distribution characteristic of the object.

[0030] (13) 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 dataset used to calculate the light distribution characteristics of an object, and includes the steps of: acquiring image data indicating a correspondence between an image obtained by imaging the object at a predetermined imaging angle and the imaging angle; generating the ray dataset indicating a starting point and vector of a ray emitted from the object based on the acquired image data; and performing a second distribution process that randomly changes a pixel position of at least one pixel among a plurality of pixels in the image of the image data; and in the step of generating the ray dataset, determining the starting point based on the pixel position of the pixel after the second distribution process, and generating the ray dataset indicating the determined starting point.

[0031] In this way, by randomly changing the pixel positions of pixels in an image and determining the starting points of light rays based on the changed pixel positions, it is possible to reduce the regularity in the intensity distribution of light emitted from an object that arises due to pixel pitch in the light distribution characteristics of the object obtained by calculation using a light ray dataset.As a result, it is possible to generate a light ray dataset for determining a more accurate light distribution characteristic of the object.

[0032] (14) 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 to calculate the light distribution characteristics of an object, the method including the steps of: acquiring image data indicating a correspondence between an image obtained by imaging the object at a predetermined imaging angle and the imaging angle; and generating the ray data set indicating starting points and vectors of rays of light emitted from the object based on the acquired image data. The step of generating the ray data set includes creating a pixel number array in which pixel numbers of pixels in the image are arranged, and an accumulated accumulation array in which accumulated accumulated values ​​of the intensities of the pixels are arranged in accordance with the arrangement order of the pixel numbers in the pixel number array; determining the starting point based on the pixel position of the pixel corresponding to a value randomly determined in a numerical range between a plurality of the accumulated accumulated values ​​in the accumulated accumulation array; and generating the ray data set indicating the determined starting point.

[0033] In this way, by determining the starting point of a ray based on the pixel position of a pixel corresponding to a randomly determined value within a numerical range between the multiple cumulative integrated values ​​in the cumulative integrated array, it is possible to determine the starting point of a ray from the pixel position of a pixel selected randomly while taking pixel intensity into consideration, compared to, for example, a configuration in which the starting point of a ray is determined from the pixel position of a pixel uniformly selected based on intensity from among multiple pixels included in an image. Therefore, in the light distribution characteristic of an object obtained by calculation using the light ray dataset, it is possible to prevent the boundary between areas where the intensity of light emitted from the object is high and areas where it is low from being unnaturally emphasized. Therefore, it is possible to generate a light ray dataset for determining the light distribution characteristic of an object more accurately.

[0034] (15) 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 to calculate the light distribution characteristics of an object, the ray data processing method including the steps of: acquiring image data indicating a correspondence between a plurality of images obtained by imaging the object at a plurality of imaging angles and the imaging angles; and generating the ray data set indicating the start points and vectors of light rays emitted from the object based on the acquired image data. The step of generating the ray data set includes creating an imaging number array in which the angle numbers of the imaging angles are arranged, and an accumulated accumulation array in which accumulated accumulated values ​​of luminous flux values ​​at the imaging angles are arranged in the order of the angle numbers in the imaging number array; determining an end point of the vector based on the imaging angle corresponding to a value randomly determined in a numerical range between the plurality of accumulated accumulated values ​​in the accumulated accumulation array; and generating the ray data set indicating the determined vector.

[0035] In this way, by determining the end point of a ray vector based on an imaging angle corresponding to a randomly determined value within a numerical range between the multiple cumulative integrated values ​​in the cumulative integrated array, compared to, for example, a configuration in which the end point is determined based on an imaging angle selected uniformly from multiple imaging angles according to the luminous flux value, it is possible to determine the end point based on an imaging angle that is irregularly selected while taking into account the luminous flux value at the imaging angle. Therefore, in the light distribution characteristic of an object obtained by calculation using the light ray dataset, it is possible to prevent band-like stripes from appearing in the distribution of the intensity of light emitted from the object. Therefore, it is possible to generate a light ray dataset for determining a more accurate light distribution characteristic of the object.

[0036] (16) 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 to calculate the light distribution characteristics of an object, and includes the steps of acquiring image data indicating a correspondence between a plurality of images obtained by imaging the object at a plurality of imaging positions translated relative to the object and the imaging positions, and generating the ray data set indicating the starting points and vectors of light rays emitted from the object based on the acquired image data.

[0037] In this way, by configuring a ray data set to be generated based on multiple images obtained at multiple imaging positions translated relative to the object, it is possible to generate a ray data set of an object with a narrow light distribution, such as a laser, with a simple configuration. Furthermore, compared to a configuration in which a ray data set is generated based on multiple images obtained by imaging the object at multiple imaging positions using, for example, a goniometer, it is possible to generate a ray data set based on images at imaging positions with higher accuracy. Therefore, it is possible to generate a ray data set for determining the light distribution characteristics of the object more accurately.

[0038] (17) A 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 to calculate the light distribution characteristics of an object, and is a program that causes a computer to function as: an acquisition unit that acquires image data indicating a correspondence between multiple images obtained by imaging the object at multiple imaging angles at a predetermined interval and the imaging angles; a generation unit that generates the ray data set indicating the starting point and vector of a ray of light emanating from the object based on the image data acquired by the acquisition unit; and a first distribution unit that performs first distribution processing to randomly change at least one of the multiple imaging angles in the image data, and the generation unit determines the end point of the vector based on the imaging angle after the first distribution processing in the first distribution unit, and generates the ray data set indicating the determined vector.

[0039] In this way, by randomly changing the imaging angle indicated by the image data and determining the end points of the ray vectors based on the changed imaging angle, it is possible to reduce the regularity in the intensity distribution of light emitted from the object that arises due to the intervals between imaging angles in the light distribution characteristic of the object obtained by calculation using the light ray dataset, thereby generating a light ray dataset for determining a more accurate light distribution characteristic of the object.

[0040] (18) A 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 to calculate the light distribution characteristics of an object, and is a program that causes a computer to function as: an acquisition unit that acquires image data indicating a correspondence between an image obtained by imaging the object at a predetermined imaging angle and the imaging angle; a generation unit that generates the ray data set indicating the starting point and vector of a ray of light emanating from the object based on the image data acquired by the acquisition unit; and a second distribution unit that performs second distribution processing to randomly change the pixel position of at least one of a plurality of pixels in the image of the image data, and the generation unit determines the starting point based on the pixel position of the pixel after the second distribution processing, and generates the ray data set indicating the determined starting point.

[0041] In this way, by randomly changing the pixel positions of pixels in an image and determining the starting points of light rays based on the changed pixel positions, it is possible to reduce the regularity in the intensity distribution of light emitted from an object that arises due to pixel pitch in the light distribution characteristics of the object obtained by calculation using a light ray dataset.As a result, it is possible to generate a light ray dataset for determining a more accurate light distribution characteristic of the object.

[0042] (19) A 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 to calculate the light distribution characteristics of an object, the program causing a computer to function as: an acquisition unit that acquires image data indicating a correspondence between an image obtained by imaging the object at a predetermined imaging angle and the imaging angle; and a generation unit that generates the ray data set indicating the starting points and vectors of light rays emitted from the object based on the image data acquired by the acquisition unit. The generation unit creates a pixel number array in which pixel numbers of pixels in the image are arranged, and an accumulated accumulation array in which accumulated accumulated values ​​of the intensities of the pixels are arranged in accordance with the arrangement order of the pixel numbers in the pixel number array, determines the starting point based on the pixel position of the pixel corresponding to a value randomly determined in a numerical range between a plurality of the accumulated accumulated values ​​in the accumulated accumulation array, and generates the ray data set indicating the determined starting point.

[0043] In this way, by determining the starting point of a ray based on the pixel position of a pixel corresponding to a randomly determined value within a numerical range between the multiple cumulative integrated values ​​in the cumulative integrated array, it is possible to determine the starting point of a ray from the pixel position of a pixel selected randomly while taking pixel intensity into consideration, compared to, for example, a configuration in which the starting point of a ray is determined from the pixel position of a pixel uniformly selected based on intensity from among multiple pixels included in an image. Therefore, in the light distribution characteristic of an object obtained by calculation using the light ray dataset, it is possible to prevent the boundary between areas where the intensity of light emitted from the object is high and areas where it is low from being unnaturally emphasized. Therefore, it is possible to generate a light ray dataset for determining the light distribution characteristic of an object more accurately.

[0044] (20) A 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 to calculate the light distribution characteristics of an object, the ray data processing program causing a computer to function as: an acquisition unit that acquires image data indicating a correspondence between multiple images obtained by imaging the object at multiple imaging angles and the imaging angles; and a generation unit that generates the ray data set indicating the start points and vectors of light rays emanating from the object based on the image data acquired by the acquisition unit, wherein the generation unit creates an imaging number array in which angle numbers of the imaging angles are arranged and an accumulated accumulation array in which accumulated accumulated values ​​of luminous flux values ​​at the imaging angles are arranged in accordance with the arrangement order of the angle numbers in the imaging number array, determines an end point of the vector based on the imaging angle corresponding to a value randomly determined in a numerical range between the multiple accumulated accumulated values ​​in the accumulated accumulation array, and generates the ray data set indicating the determined vector, the ray data processing program.

[0045] In this way, by determining the end point of a ray vector based on an imaging angle corresponding to a randomly determined value within a numerical range between the multiple cumulative integrated values ​​in the cumulative integrated array, compared to, for example, a configuration in which the end point is determined based on an imaging angle selected uniformly from multiple imaging angles according to the luminous flux value, it is possible to determine the end point based on an imaging angle that is irregularly selected while taking into account the luminous flux value at the imaging angle. Therefore, in the light distribution characteristic of an object obtained by calculation using the light ray dataset, it is possible to prevent band-like stripes from appearing in the distribution of the intensity of light emitted from the object. Therefore, it is possible to generate a light ray dataset for determining a more accurate light distribution characteristic of the object.

[0046] (21) A 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 to calculate the light distribution characteristics of an object, and is a program that causes a computer to function as: an acquisition unit that acquires image data indicating a correspondence between a plurality of images obtained by imaging the object at a plurality of imaging positions translated relative to the object and the imaging positions; and a generation unit that generates the ray data set indicating the starting points and vectors of light rays emitted from the object based on the image data acquired by the acquisition unit.

[0047] In this way, by configuring a ray data set to be generated based on multiple images obtained at multiple imaging positions translated relative to the object, it is possible to generate a ray data set of an object with a narrow light distribution, such as a laser, with a simple configuration. Furthermore, compared to a configuration in which a ray data set is generated based on multiple images obtained by imaging the object at multiple imaging positions using, for example, a goniometer, it is possible to generate a ray data set based on images at imaging positions with higher accuracy. Therefore, it is possible to generate a ray data set for determining the light distribution characteristics of the object more accurately. [Effects of the Invention]

[0048] According to the present disclosure, it is possible to generate a light ray data set for determining a more accurate light distribution characteristic of an object. [Brief explanation of the drawings]

[0049] [Figure 1] FIG. 1 is a diagram illustrating a configuration of a ray data generating system according to a first embodiment of the present disclosure. [Figure 2] FIG. 2 is a diagram showing measurement points of a detector in the 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 the light distribution measurement device according to the first embodiment of the present disclosure. [Figure 4] FIG. 4 is a schematic diagram showing, in two dimensions, an example of a ray data set generated by the ray data processing device according to the first embodiment of the present disclosure. [Figure 5] FIG. 5 is a diagram illustrating a configuration of a light data processing device according to the first embodiment of the present disclosure. [Figure 6] FIG. 6 is a diagram illustrating an example of image data acquired by an acquisition unit in the light ray data processing device according to the first embodiment of the present disclosure. [Figure 7] FIG. 7 is a diagram illustrating an example of a method for generating a ray data set by a processing unit in the ray data processing device according to the first embodiment of the present disclosure. [Figure 8] FIG. 8 is a diagram illustrating an example of a light distribution profile generated by a processing unit in the light data processing device according to the first embodiment of the present disclosure. [Figure 9] FIG. 9 is a diagram illustrating an example of a light ray extraction profile generated by a processing unit in the light ray data processing device according to the first embodiment of the present disclosure. [Figure 10] FIG. 10 is a diagram illustrating an example of angle numbers assigned to imaging angles by a processing unit in the light data processing device according to the first embodiment of the present disclosure. [Figure 11] FIG. 11 is a diagram illustrating an example of an imaging number array and an accumulated integration array generated by a processing unit in the light ray data processing device according to the first embodiment of the present disclosure. [Figure 12] FIG. 12 is a graph showing an example of an accumulated integrated value generated by a processing unit in the light data processing device according to the first embodiment of the present disclosure. [Figure 13] FIG. 13 is a diagram illustrating an example of a procedure for determining the number of rays to be extracted by the processing unit in the light ray data processing device according to the first embodiment of the present disclosure. [Figure 14] FIG. 14 is a diagram illustrating an example of pixel numbers assigned to pixels by a processing unit in the light data processing device according to the first embodiment of the present disclosure. [Figure 15]FIG. 15 is a diagram illustrating an example of a pixel number array and an accumulated integration array generated by a processing unit in the light data processing device according to the first embodiment of the present disclosure. [Figure 16] FIG. 16 is a graph showing an example of an accumulated integrated value generated by a processing unit in the light data processing device according to the first embodiment of the present disclosure. [Figure 17] FIG. 17 is a diagram illustrating an example of a procedure for determining a start pixel by the processing unit in the light ray data processing device according to the first embodiment of the present disclosure. [Figure 18] FIG. 18 is a diagram illustrating a start pixel determined by a processing unit in the light data processing device according to the first embodiment of the present disclosure. [Figure 19] FIG. 19 is a diagram illustrating an example of an end point distribution process performed by a processing unit in the light data processing device according to the first embodiment of the present disclosure. [Figure 20] FIG. 20 is a diagram illustrating an example of a starting point distribution process performed by a processing unit in the light data processing device according to the first embodiment of the present disclosure. [Figure 21] FIG. 21 is a flowchart defining an example of an operation procedure when the ray data processing device according to the first embodiment of the present disclosure generates a ray data set. [Figure 22] FIG. 22 is a diagram illustrating a configuration of a ray data generating system according to the second embodiment of the present disclosure. [Figure 23] FIG. 23 is a diagram illustrating a configuration of a light data processing device according to the second embodiment of the present disclosure. [Figure 24] FIG. 24 is a diagram illustrating an example of image data acquired by an acquisition unit in the light ray data processing device according to the second embodiment of the present disclosure. [Figure 25] FIG. 25 is a diagram illustrating an example of a method for generating a ray data set by a processing unit in a ray data processing device according to the second embodiment of the present disclosure. [Figure 26] FIG. 26 is a diagram illustrating an example of a light distribution profile generated by a processing unit in the light data processing device according to the second embodiment of the present disclosure. [Figure 27] FIG. 27 is a diagram illustrating an example of a light ray extraction profile generated by a processing unit in the light ray data processing device according to the second embodiment of the present disclosure. [Figure 28] FIG. 28 is a flowchart defining an example of an operation procedure when a ray data processing device according to the second embodiment of the present disclosure generates a ray data set. DETAILED DESCRIPTION OF THE INVENTION

[0050] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. In the drawings, identical or corresponding parts are designated by the same reference numerals, and their description will not be repeated. Furthermore, at least some of the embodiments described below may be combined in any manner.

[0051] First Embodiment [Configuration and basic operation] Fig. 1 is a diagram showing the configuration of a light ray data generation system according to a first embodiment of the present disclosure. Referring to Fig. 1, the light ray data generation system 301 includes a light ray data processing device 101 and a light distribution measurement device 201. The light distribution measurement device 201 generates image data Dp indicating the correspondence between an image Im obtained by capturing an image of an object S at one or more measurement points Mp and the measurement points Mp. The light ray data processing device 101 generates a light ray dataset Dst used to calculate the light distribution characteristic of the object S, based on the image data Dp generated by the light distribution measurement device 201.

[0052] The object S is an object that emits light by itself, such as a lighting fixture or a display device, or an object that reflects or transmits light from a light source. Specifically, the object S is a display such as a television, indoor lighting, outdoor lighting, automotive lighting, or film. The shape of the object S is not limited to a sphere as shown in FIG. 1.

[0053] In FIG. 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 located as shown in FIG. 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" defined in the Japanese Industrial Standard (JIS C 8105-5). The Y-axis corresponds to the "third axis of the lighting fixture" defined in the Japanese Industrial Standard (JIS C 8105-5). The Z-axis corresponds to the "reference axis of the lighting fixture" defined in the Japanese Industrial Standard (JIS C 8105-5). Hereinafter, a 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 located at the origin of the three-dimensional Cartesian coordinate system.

[0054] (Light distribution measuring device) Light distribution measurement device 201 includes detector 51, first arm 52, second arm 53, first motor 54, second motor 55, and support base 56. Support base 56 fixes object S. First motor 54 is rotatable in the direction of arrow E1 in the figure. Second motor 55 is rotatable in the direction of arrow E2 in the figure. First arm 52 is connected to first motor 54. Second arm 53 is connected to first arm 52 via second motor 55. Detector 51 is attached to second arm 53. Detector 51 is a two-dimensional imaging device.

[0055] Light distribution measurement device 201 is a goniometer that can change the position of detector 51 while maintaining distance L between object S and principal point Cp of detector 51 (described later), and measures the near-field light distribution of object S. More specifically, first motor 54 rotates in the direction of arrow E1, causing detector 51 to rotate around the Y-axis in the direction of arrow E1. Furthermore, second motor 55 rotates in the direction of arrow E2, causing detector 51 to rotate around the X-axis in the direction of arrow E2.

[0056] Fig. 2 is a diagram showing measurement points of a detector in a light distribution measurement device according to a first embodiment of the present disclosure. Referring to Fig. 2, principal point Cp of detector 51 moves on a spherical surface Sp centered on object S as first motor 54 and second motor 55 rotate. Detector 51 generates an image Im of object S by capturing an image of object S in a state in which principal point Cp is located at one or more measurement points Mp on spherical surface Sp.

[0057] For example, the measurement point Mp is represented using the αβ coordinate system defined in the Japanese Industrial Standards (JIS C 8105-5). More specifically, the measurement point Mp is represented using the X-axis as the polar axis, an inclination angle α relative to the polar axis, and a rotation angle β around the polar axis as the center of rotation. The inclination angle α is also referred to as the vertical angle. The rotation angle β is also referred to as the horizontal angle. The inclination angle α is greater than or equal to -90° and less than or equal to 90°. The rotation angle β is greater than or equal to -180° and less than 180°.

[0058] Light distribution measurement device 201 receives a measurement control command indicating one or more measurement points Mp from a control device (not shown) or light ray data processing device 101. First motor 54 and second motor 55 in light distribution measurement device 201 rotate in accordance with the measurement control command. Detector 51 generates an image Im by capturing an image of object S at an inclination angle α and a rotation angle β that correspond to measurement point Mp, with principal point Cp positioned at measurement point Mp indicated by the measurement control command.

[0059] Fig. 3 is a schematic diagram showing an example of an image generated by a detector in the light distribution measurement device according to the first embodiment of the present disclosure. In image Im shown in Fig. 3, black portions indicate areas of low brightness, and areas with low density of hatched lines indicate areas of high brightness. With reference to Fig. 3, for example, detector 51 generates image Im including 160,000 pixels p arranged in a 400 x 400 matrix. Hereinafter, pixel p in the a-th column from the left and the b-th row from the top in image Im will also be referred to as pixel p(a, b). Here, a and b are integers greater than or equal to 1 and less than or equal to 400.

[0060] For example, the detector 51 captures images of the object S at a plurality of measurement points Mp in 2π space, which is half of the spherical surface Sp, at measurement intervals Wα and Wβ specified by the user. The measurement interval Wα is the measurement interval for the tilt angle α, and the measurement interval Wβ is the measurement interval for the rotation angle β. As an example, the detector 51 generates 32761 images Im by capturing images of the object S at 32761 (181 × 181) measurement points Mp, which are combinations of tilt angles α at 1-degree intervals in the range from -90° to 90° and rotation angles β at 1-degree intervals in the range from -90° to 90°.

[0061] The detector 51 generates image data Dp indicating the correspondence between the generated image Im and measurement points Mp expressed using the tilt angle α and rotation angle β. The detector 51 also generates measurement condition data Dm indicating the angle of view Wa of the image Im 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 light ray data processing device 101.

[0062] The detector 51 may generate image data Dp indicating the measurement point Mp expressed using, for example, an XY coordinate system or a θφ coordinate system defined in Japanese Industrial Standards (JIS C 8105-5). The detector 51 may also capture an image of the object S at the measurement point Mp in a 4π space, which is the entire spherical surface Sp.

[0063] (Light Data Processing Device) 4 is a two-dimensional schematic diagram showing an example of a light ray data set generated by a light ray data processing device according to the first embodiment of the present disclosure. Referring to FIG. 4, the light ray data processing device 101 generates a light ray data set Dst based on image data Dp received from the light distribution measurement device 201.

[0064] The ray data set Dst includes ray data Dr indicating information about rays emitted from the target S. The ray data Dr is data indicating start coordinates Ps(x, y, z) indicating the position of the start point of the ray in a three-dimensional orthogonal coordinate system, a 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 data set Dst including ray data Dr for the number N of rays specified by the user.

[0065] The light ray dataset Dst is used to calculate the light distribution characteristic 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 characteristic of the object S and designs the lighting fixture using the evaluation results. More specifically, the simulation software uses the light ray dataset Dst generated by the light ray data processing device 101 to calculate the illuminance Lx on the surface of a hemisphere installed at a position a given distance away from the object S, as the light distribution characteristic of the object S. A manufacturer of a lighting fixture that includes the object S as a component uses the calculation result of the illuminance Lx obtained by the simulation software to design the lighting fixture.

[0066] However, when a ray data set Dst generated using conventional technology is input to simulation software, calculation results may be obtained that show a regular distribution of illuminance Lx, even though the light distribution characteristics of the object S are uniform. Specifically, for example, if the set value of the spatial resolution of illuminance Lx in the simulation software is small compared to the measurement intervals Wα and Wβ and the pixel pitch in the image Im, areas of high illuminance Lx may appear in a grid pattern in the ray profile showing the distribution of illuminance Lx. Furthermore, for example, if the number of ray data Dr included in the ray data set Dst is small, a band-like striped pattern may appear in the distribution of illuminance Lx in the ray profile. Furthermore, for example, the boundary between areas of high illuminance Lx and areas of low illuminance Lx may be unnaturally emphasized in the ray profile.

[0067] Therefore, the light ray data processing device 101 according to the first embodiment of the present disclosure solves the above problem by having the following configuration: The processing in the light ray data processing device 101 will be described in detail below.

[0068] (Configuration of the light data processing device) FIG. 5 is a diagram illustrating a configuration of a light ray data processing device according to a first embodiment of the present disclosure. Referring to FIG. 5, the light ray data processing device 101 includes an acquisition unit 10, a storage unit 20, and a processing unit 30. The processing unit 30 is an example of a first distribution unit, an example of a second distribution unit, and an example of a generation unit. The processing unit 30 includes a light distribution information generation unit 31, an extraction information generation unit 32, a start pixel determination unit 33, an end point distribution processing unit 34, a start point distribution processing unit 35, and a light ray data generation unit 36. One or both of the acquisition unit 10 and the processing unit 30 are realized, for example, by a processing circuit including one or more processors. The storage unit 20 is, for example, a non-volatile memory included in the processing circuit.

[0069] FIG. 6 is a diagram illustrating an example of image data acquired by an acquisition unit in a light ray data processing device according to the first embodiment of the present disclosure. Referring to FIG. 6, acquisition unit 10 acquires image data Dp indicating a correspondence between a plurality of images Im obtained by capturing images of object S at a plurality of imaging angles with predetermined measurement intervals Wα and Wβ and the imaging angles. More specifically, acquisition unit 10 receives image data Dp indicating a correspondence between an inclination angle α and a rotation angle β indicating measurement point Mp and the image Im from light distribution measurement device 201. Furthermore, acquisition unit 10 further receives measurement condition data Dm from light distribution measurement device 201. Acquisition unit 10 stores the received image data Dp and measurement condition data Dm in storage unit 20. As an example, the inclination angle α of the nth row in image data Dp is (−91+n)°, and the rotation angle β of the mth column in image data Dp is (−91+m)°. Here, n and m are integers greater than or equal to 1 and less than or equal to 181.

[0070] Acquiring unit 10 may be configured to acquire one image Im obtained by imaging object S at a predetermined imaging angle and image data Dp indicating the correspondence between the imaging angle, or may be configured to acquire multiple images Im obtained by imaging object S at multiple imaging angles at irregular intervals and image data Dp indicating the correspondence between the imaging angles. Furthermore, acquiring unit 10 may be configured to receive image data Dp from a device other than light distribution measurement device 201.

[0071] The processing unit 30 generates a ray data set Dst indicating the starting points and vectors of rays emanating 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 specifying the number of rays N. The processing unit 30 generates a ray data set Dst including ray data Dr for the specified number of rays N in accordance with the accepted user operation. The number of rays N may be, for example, 100,000, 1 million, 10 million, or 100 million.

[0072] 7 is a diagram illustrating an example of a method for generating a ray data set by a processing unit in a ray data processing device according to the first embodiment of the present disclosure. Fig. 7 illustrates the positional relationship between a detector 51 and an imaging plane Is of the detector 51 on the XZ plane. The imaging plane Is is a plane perpendicular to a line passing through the object S and the principal point Cp.

[0073] 7, the processing unit 30 determines a start pixel pps, which is a pixel p that should be the start point of a light ray, based on the number N of light rays and the intensity of each pixel p in multiple images Im. The processing unit 30 calculates the coordinates of the start pixel pps in a three-dimensional polar coordinate system based on the angle of view Wa indicated by the measurement condition data Dm in the storage unit 20. The processing unit 30 determines start coordinates Ps(x, y, z) based on the calculated coordinates of the start pixel pps. The start coordinates Ps(x, y, z) are coordinates on the imaging plane Is.

[0074] The processing unit 30 also calculates the coordinates of the principal point Cp in a three-dimensional polar coordinate system based on the measurement point Mp corresponding to the image Im and the distance L indicated by the measurement condition data Dm. The processing unit 30 determines the end point coordinate Pe(x,y,z) based on the calculated coordinates of the principal point Cp. The processing unit 30 then determines the vector extending from the determined start point coordinate Ps(x,y,z) to the determined end point coordinate Pe(x,y,z) as the ray vector Vt.

[0075] Furthermore, the processing unit 30 calculates a total luminous flux value TL of the object S based on all images Im indicated by the image data Dp. The processing unit 30 calculates a luminous flux value per light ray by dividing the calculated total luminous flux value TL by the number of light rays N. The processing unit 30 determines the calculated luminous flux value per light ray as the value of the intensity Pw of the light ray data Dr.

[0076] The processing unit 30 generates ray data Dr indicating the determined start point coordinates Ps(x, y, z), the determined ray vector Vt, and the determined intensity Pw. The processing unit 30 generates N pieces of ray data Dr, and generates a ray data set Dst including the N pieces of ray data Dr.

[0077] In addition to the basic method for generating the light ray data Dr described above, the processing unit 30 performs the following characteristic processing. Specifically, the processing unit 30 creates an imaging number array LA1 in which the angle numbers An of the imaging angles are arranged, and an accumulation array LA2 in which the accumulated integrated values ​​Sum1 of the luminous flux values ​​at the imaging angles are arranged in the order of the angle numbers An in the imaging number array LA1. The processing unit 30 determines the end point coordinates Pe(x, y, z) of the light ray vector Vt based on the imaging angle corresponding to a value randomly determined within a numerical range between the multiple accumulated integrated values ​​Sum1 in the accumulation array LA2. For example, the extraction information generation unit 32 in the processing unit 30 determines, for each measurement point Mp, the number of light ray data Dr for which the end point coordinates Pe(x, y, z) are to be determined based on the measurement point Mp, based on the value randomly determined within the numerical range in the accumulation array LA2. Details of the processing by the extraction information generation unit 32 will be described later.

[0078] Furthermore, the processing unit 30 performs an end point distribution process that randomly changes at least one of the multiple imaging angles in the image data Dp. The processing unit 30 determines the end point coordinate Pe(x, y, z) of the light vector Vt based on the imaging angle after the end point distribution process. The end point distribution process is an example of a first distribution process. For example, the end point distribution processing unit 34 in the processing unit 30 performs an end point distribution process that randomly changes the tilt angle α and rotation angle β used to calculate the end point coordinate Pe(x, y, z). Details of the processing by the end point distribution processing unit 34 will be described later.

[0079] The processing unit 30 also creates a pixel number array LB1 in which pixel numbers Bn of pixels p in an image Im are arranged, and an accumulation array LB2 in which accumulated intensity values ​​Sum2 of pixels p are arranged in the same order as the pixel numbers Bn in the pixel number array LB1. The processing unit 30 determines start coordinates Ps(x, y, z) based on the pixel position of pixel p corresponding to a value randomly determined within a range of values ​​between the accumulated intensity values ​​Sum2 in the accumulation array LB2. For example, a start pixel determination unit 33 in the processing unit 30 determines, for each image Im, a start pixel pps from among the pixels p included in the image Im, based on a value randomly determined within the range of values ​​in the accumulation array LB2. Details of the processing by the start pixel determination unit 33 will be described later.

[0080] Furthermore, the processing unit 30 performs a start point distribution process that randomly changes the pixel position of at least one pixel p among multiple pixels p in the image Im. The processing unit 30 determines the start point coordinate Ps(x, y, z) based on the pixel position of the pixel p after the start point distribution process. The start point distribution process is an example of a second distribution process. For example, the start point distribution processing unit 35 in the processing unit 30 performs a start point distribution process that randomly changes the pixel position of the start point pixel pps used to calculate the start point coordinate Ps(x, y, z). Details of the processing in the start point distribution processing unit 35 will be described later.

[0081] (Generation of light distribution profile Pr1) When image data Dp is stored in storage unit 20 by acquisition unit 10, light distribution information generation unit 31 in processing unit 30 acquires the image data Dp.

[0082] The light distribution information generator 31 calculates the luminous intensity at each measurement point Mp indicated by the image data Dp. More specifically, the light distribution information generator 31 calculates the sum of the intensities of each pixel p of the image Im corresponding to the measurement point Mp as the luminous intensity at that measurement point Mp. The light distribution information generator 31 calculates the luminous intensity for each measurement point Mp.

[0083] The light distribution information generating unit 31 calculates the luminous flux value at the measurement point Mp by multiplying the luminous intensity at the measurement point Mp by a predetermined spherical zonal coefficient, for example, in accordance with Japanese Industrial Standards (JIS C 8105-5). The light distribution information generating unit 31 calculates the luminous flux value for each measurement point Mp.

[0084] 8 is a diagram showing an example of a light distribution profile generated by a processing unit in the light ray data processing device according to the first embodiment of the present disclosure. Referring to Fig. 8, the light distribution information generating unit 31 calculates a luminous flux value for each measurement point Mp and generates a light distribution profile Pr1 indicating a correspondence between the luminous flux value and the tilt angle α and rotation angle β indicating the measurement point Mp. As an example, similar to image data Dp, the tilt angle α of the nth row in light distribution profile Pr1 is (-91+n)°, and the rotation angle β of the mth column in light distribution profile Pr1 is (-91+m)°.

[0085] Furthermore, light distribution information generation unit 31 calculates a total luminous flux value TL of object S based on the luminous flux value at each measurement point Mp, for example, in accordance with Japanese Industrial Standards (JIS C 8105-5). Light distribution information generation unit 31 outputs light distribution profile Pr1 and image data Dp to extraction information generation unit 32. Light distribution information generation unit 31 also determines the value obtained by dividing the calculated total luminous flux value TL by the number of light rays N as the value of intensity Pw, and outputs intensity information indicating the determined intensity Pw to light ray data generation unit 36.

[0086] (Generation of ray extraction profile Pr2) 9 is a diagram showing an example of a ray extraction profile generated by a processing unit in the light ray data processing device according to the first embodiment of the present disclosure. Referring to Fig. 9, extraction information generation unit 32 in processing unit 30 uses a random determination method to determine the number of extracted rays Ndr for each measurement point Mp, based on the light distribution profile Pr1 received from light distribution information generation unit 31. Then, extraction information generation unit 32 generates a ray extraction profile Pr2 indicating the correspondence between the tilt angle α and rotation angle β indicating each measurement point Mp and the number of extracted rays Ndr at that measurement point Mp.

[0087] The number of extracted rays Ndr at a measurement point Mp indicates the number of ray data Dr to be generated based on the image Im corresponding to the measurement point Mp. As an example, similar to the light distribution profile Pr1, the tilt angle α of the nth row in the ray extraction profile Pr2 is (-91+n)°, and the rotation angle β of the mth column in the ray extraction profile Pr2 is (-91+m)°. Below, a detailed procedure for generating the ray extraction profile Pr2 using the random determination method will be described.

[0088] 10 is a diagram showing an example of angle numbers assigned to imaging angles by a processing unit in the light ray data processing device according to the first embodiment of the present disclosure. Referring to Fig. 10, the extraction information generation unit 32 assigns an angle number An ranging from 1 to 32761 to each combination of tilt angle α and rotation angle β in the light distribution profile Pr1, and generates an imaging number array LA1 in which the angle numbers An are arranged in ascending order. For example, the extraction information generation unit 32 assigns angle numbers An ranging from (181 × n - 180) to (181 × n) to the combinations of tilt angle α and rotation angle β in the nth row and the first column to the 181st column in the light distribution profile Rr1.

[0089] Specifically, the extraction information generation unit 32 assigns angle numbers An ranging from 1 to 181 to the pairs of tilt angles α and rotation angles β in the first row and the first column to the 181st column in the light distribution profile Rr1. The extraction information generation unit 32 also assigns angle numbers An ranging from 182 to 362 to the pairs of tilt angles α and rotation angles β in the second row and the first column to the 181st column in the light distribution profile Rr1. The extraction information generation unit 32 also assigns angle numbers An ranging from 32581 to 32761 to the pairs of tilt angles α and rotation angles β in the 181st row and the first column to the 181st column in the light distribution profile Rr1.

[0090] 11 is a diagram illustrating an example of an imaging number array and an accumulated integration array generated by a processing unit in a light ray data processing device according to the first embodiment of the present disclosure. Referring to FIG. 11, for example, the extraction information generation unit 32 generates an imaging number array LA1 in which angle numbers An are randomly arranged. More specifically, the extraction information generation unit 32 performs random processing to randomly shuffle the angle numbers An in the imaging number array LA1 according to a predetermined algorithm. The imaging number array LA1 after the random processing includes, as array elements, angle numbers An whose element numbers Li range from 1 to 32761.

[0091] The extracted information generator 32 calculates the cumulative integrated value Sum1 of the luminous flux value for each angle number An in the randomly processed imaging number array LA1, and generates an accumulated integrated array LA2 in which the calculated cumulative integrated values ​​Sum1 are arranged. The accumulated integrated array LA2 includes, as array elements, the cumulative integrated values ​​Sum1 whose element numbers Li range from 1 to 32761.

[0092] More specifically, the extracted information generating unit 32 calculates the sum of the luminous flux values ​​corresponding to each angle number An from 1 to k as the cumulative integrated value Sum1 corresponding to the k-th angle number An in the post-random processing imaging number array LA1, where k is an integer greater than or equal to 1 and less than or equal to 32761.

[0093] Specifically, if the first angle number An in the imaging number array LA1 is "7273," and the luminous flux value corresponding to angle number An of "7273" in light distribution profile Rr1 is "zero," the first accumulated integrated value Sum1 in the accumulated integration array LA2 will be "zero." Furthermore, if the second angle number An in the imaging number array LA1 is "20002," and the luminous flux value corresponding to angle number An of "20002" in light distribution profile Rr1 is "3," the second accumulated integrated value Sum1 in the accumulated integration array LA2 will be "3 (zero + 3)."

[0094] 12 is a graph showing an example of an accumulated integrated value generated by a processing unit in the light data processing device according to the first embodiment of the present disclosure. In FIG. 12, the horizontal axis represents the element number Li in the image capture number array LA1, and the vertical axis represents the accumulated integrated value Sum1.

[0095] 12, for example, the extraction information generation unit 32 divides the range between the minimum value S1min and the maximum value S1max of the cumulative integrated value Sum1 in the cumulative integration array LA2 into two numerical ranges Rg. More specifically, the extraction information generation unit 32 divides the range between the minimum value S1min and the maximum value S1max into a numerical range Rg1 that is equal to or greater than the minimum value S1min and less than half the maximum value S1max, and a numerical range Rg2 that is equal to or greater than half the maximum value S1max and less than or equal to S1max. Note that the extraction information generation unit 32 may divide the range between the minimum value S1min and the maximum value S1max into three or more numerical ranges Rg.

[0096] 13 is a diagram illustrating an example of a procedure for determining the number of rays to be extracted by a processing unit in a light ray data processing device according to the first embodiment of the present disclosure. FIG. 13 is an enlarged view of a part of the numerical range Rg1 in the graph of FIG.

[0097] 13, the extraction information generation unit 32 determines the end point of the light vector Vt based on the imaging angle corresponding to a randomly determined value in each numerical range Rg. More specifically, the extraction information generation unit 32 obtains a random number Rv1 in the numerical range Rg1 from a predetermined random function, and searches for an element number Li that satisfies the following formula (1) for the obtained random number Rv1. Here, Sum1[Li] represents the cumulative integration value Sum1 corresponding to the element number Li in the cumulative integration array LA2. Sum1[Li-1] <Rv1≦Sum1[Li]···(1)

[0098] For example, when the acquired random number Rv1 is "16," the element number Li that satisfies formula (1) is "15." In this case, the extraction information generation unit 32 references the imaging number array LA1 shown in FIG. 11 and acquires the angle number An for which the element number Li is "15."

[0099] Referring again to FIG. 9, the extraction information generating unit 32 increments the number of extracted rays Ndr at the measurement point Mp corresponding to the acquired angle number An in the light ray extraction profile Pr2.

[0100] The extraction information generation unit 32 repeats the steps of obtaining a random number Rv1 in the numerical range Rg1, searching for an element number Li that satisfies equation (1), obtaining an angle number An corresponding to the element number Li, and incrementing the number of extracted rays Ndr at the measurement point Mp corresponding to the angle number An a number of times equal to 1 / 2 of the number of rays N specified by the user.

[0101] Similarly, the extraction information generation unit 32 repeats the following steps: obtain a random number Rv1 in the numerical range Rg2, search for an element number Li that satisfies formula (1), obtain an angle number An corresponding to the element number Li, and increment the number of extractions Ndr at the measurement point Mp corresponding to the angle number An, the number of times being half the number of rays N specified by the user. This makes it possible to generate a ray extraction profile Pr2 in which the sum of the numbers of extractions Ndr at each measurement point Mp is the number of rays N.

[0102] Referring back to FIG. 5, extraction information generation unit 32 outputs to start pixel determination unit 33 image data Dp received from light distribution information generation unit 31 and the generated ray extraction profile Pr2.

[0103] (Generating start and end point information) The start pixel determiner 33 determines a start pixel pps for each measurement point Mp using a random determination method based on the image data Dp and ray extraction profile Pr2 received from the extraction information generator 32. The start pixel determiner 33 generates start and end point information that indicates the correspondence between the measurement point Mp and the determined start pixel pps. The procedure for generating the start and end point information using the random determination method will be described in detail below.

[0104] The start pixel determination unit 33 refers to the ray extraction profile Pr2 and acquires from the image data Dp an image Im corresponding to a measurement point Mp where the number of extracted rays Ndr is equal to or greater than 1. The start pixel determination unit 33 performs the following process for each image Im to determine a start pixel pps from among 160,000 pixels p in the image Im to be processed.

[0105] 14 is a diagram showing an example of pixel numbers assigned to pixels by a processing unit in the light data processing device according to the first embodiment of the present disclosure. Referring to Fig. 14, the start pixel determination unit 33 assigns pixel numbers Bn ranging from 1 to 160,000 to pixels p in the acquired image Im, and generates a pixel number array LB1 in which the pixel numbers Bn are arranged in ascending order. For example, the start pixel determination unit 33 assigns pixel numbers Bn ranging from (400 x a - 399) to (400 x a) to pixels p in the first to fourth columns of the ath row.

[0106] Specifically, the start pixel determination unit 33 assigns pixel numbers Bn ranging from 1 to 400 to pixels p in the first row and the first column to the 400th column in the image Im. The start pixel determination unit 33 also assigns pixel numbers Bn ranging from 401 to 800 to pixels p in the second row and the first column to the 400th column in the image Im. The start pixel determination unit 33 also assigns pixel numbers Bn ranging from 159600 to 160000 to pixels p in the 400th row and the first column to the 400th column in the image Im.

[0107] 15 is a diagram showing an example of a pixel number array and an accumulated integration array generated by a processing unit in a light data processing device according to a first embodiment of the present disclosure. Referring to FIG. 15, for example, the start pixel determination unit 33 generates a pixel number array LB1 in which pixel numbers Bn are randomly arranged. More specifically, the start pixel determination unit 33 performs random processing to randomly shuffle the pixel numbers Bn in the pixel number array LB1 according to a predetermined algorithm. The pixel number array LB1 after the random processing includes pixel numbers Bn whose element numbers Li range from 1 to 160,000 as array elements.

[0108] The start pixel determination unit 33 calculates the cumulative integrated value Sum2 of the pixel intensity for each pixel number Bn in the pixel number array LB1 after the random processing, and generates a cumulative integrated array LB2 in which the calculated cumulative integrated values ​​Sum2 are arranged. The cumulative integrated array LB2 includes, as array elements, the cumulative integrated values ​​Sum2 for element numbers Li from 1 to 160,000.

[0109] More specifically, the start pixel determination unit 33 calculates the sum of the intensities of the pixels corresponding to the first through j-th pixel numbers Bn as the cumulative integration value Sum2 corresponding to the j-th pixel number Bn in the cumulative integration array LB2 after the random processing, where j is an integer greater than or equal to 1 and less than or equal to 160,000.

[0110] Specifically, if the first pixel number Bn in pixel number array LB1 is "52339" and the intensity of the pixel in image Im corresponding to pixel number Bn "52339" is "zero," the first cumulative integrated value Sum2 in cumulative integration array LB2 will be "zero." Also, if the second angle number An in pixel number array LB1 is "54064" and the intensity of the pixel in image Im corresponding to pixel number Bn "54064" is "1," the second cumulative integrated value Sum2 in cumulative integration array LB2 will be "1 (zero + 1)."

[0111] 16 is a graph showing an example of an accumulated integrated value generated by a processing unit in the light data processing device according to the first embodiment of the present disclosure. In Fig. 16, the horizontal axis represents the element number Li in the pixel number array LB1, and the vertical axis represents the accumulated integrated value Sum2.

[0112] 16, for example, the start pixel determination unit 33 divides the range between the minimum value S2min and the maximum value S2max of the cumulative integration value Sum2 in the cumulative integration array LB2 into two numerical ranges Rh. More specifically, the start pixel determination unit 33 divides the range between the minimum value S2min and the maximum value S2max into a numerical range Rh1 that is equal to or greater than the minimum value S2min and less than half the maximum value S2max, and a numerical range Rh2 that is equal to or greater than half the maximum value S2max and less than or equal to S2max. Note that the start pixel determination unit 33 may divide the range between the minimum value S2min and the maximum value S2max into three or more numerical ranges Rh.

[0113] 17 is a diagram illustrating an example of a procedure for determining a start pixel by a processing unit in a light data processing device according to the first embodiment of the present disclosure. FIG. 17 shows an enlarged view of a part of the numerical range Rh1 in the graph of FIG.

[0114] 17, the start pixel determination unit 33 determines a start pixel pps to be the start point of a ray based on a pixel position corresponding to a randomly determined value in each numerical range Rh. More specifically, the start pixel determination unit 33 obtains a random number Rv2 in the numerical range Rh1 from a predetermined random function, and searches for an element number Li that satisfies the following equation (2) for the obtained random number Rv2. Here, Sum2[Li] represents the cumulative integration value Sum2 corresponding to the element number Li in the cumulative integration array LB2. Sum2[Li-1] <Rv2≦Sum2[Li]···(2)

[0115] For example, when the acquired random number Rv2 is "105," the element number Li that satisfies equation (2) is "10." In this case, the extraction information generation unit 32 references the pixel number array LB1 shown in FIG. 15 and acquires "89767," which is the pixel number Bn for which the element number Li is "10."

[0116] 18 is a diagram showing a start pixel determined by a processing unit in the light data processing device according to the first embodiment of the present disclosure. Referring to FIG. 18, the start pixel determination unit 33 determines the pixel (224,167) having the pixel number Bn of "89767" as the start pixel pps.

[0117] The start pixel determination unit 33 repeats the following steps: obtain a random number Rv2 in the numerical range Rh1, search for an element number Li that satisfies equation (2), obtain a pixel number Bn corresponding to the element number Li, and determine the start pixel pps a number of times equal to 1 / 2 the number Ndr of extracted measurement points Mp corresponding to the image Im to be processed.

[0118] Similarly, the start pixel determination unit 33 obtains a random number Rv2 in the numerical range Rh2, searches for an element number Li that satisfies equation (2), obtains a pixel number Bn corresponding to the element number Li, and determines a start pixel pps a number of times equal to half the number Ndr of extracted measurement points Mp corresponding to the image Im to be processed. In this way, the start pixel determination unit 33 can determine a start pixel pps to be used as the start point of the extracted number Ndr rays from among the 160,000 pixels p in the image Im to be processed, depending on the intensity of each pixel p in the image Im to be processed. Note that a single pixel p may be determined as a start pixel pps multiple times, so the number Ndr of extracted pixels may not match the number of start pixels pps.

[0119] The start pixel determination unit 33 determines the start pixel pps according to the above-described procedure for all images Im corresponding to measurement points Mp where the number of extracted lines Ndr is equal to or greater than 1. Thereafter, the start pixel determination unit 33 generates start and end point information indicating the correspondence between the angle number An of the measurement point Mp and the pixel number Bn of the determined start pixel pps.

[0120] Referring back to FIG. 5, the start pixel determination unit 33 outputs the generated start and end point information to the end point distribution processing unit .

[0121] (Endpoint distributed processing) The end point distribution processing unit 34 receives the start point and end point information from the start point pixel determination unit 33, and performs end point distribution processing to randomly change the measurement points Mp indicated by the received start point and end point information.

[0122] 19 is a diagram illustrating an example of endpoint distribution processing by a processing unit in a light data processing device according to the first embodiment of the present disclosure. Fig. 19 shows some measurement points Mp on a spherical surface Sp. Referring to Fig. 19, in the endpoint distribution processing, the endpoint distribution processing unit 34 randomly changes the imaging angle indicated by the measurement point Mp within a distribution range Dmp of ±½ of the measurement intervals Wα and Wβ, centered on the imaging angle.

[0123] More specifically, the endpoint distribution processor 34 obtains the random number Rαβ from a predetermined random function, and updates the measurement point Mp to a measurement point Mp determined in accordance with the random number Rαβ within the distribution range Dmp, according to a predetermined algorithm.

[0124] For example, the end point distribution processing unit 34 performs end point distribution processing on all measurement points Mp indicated by the start point and end point information. Referring again to Figure 5, the end point distribution processing unit 34 outputs the start point and end point information after the end point distribution processing to the start point distribution processing unit 35.

[0125] (Start point distributed processing) The start point distribution processor 35 receives the start point and end point information from the end point distribution processor 34 and performs start point distribution processing to randomly change the pixel position of the start point pixel pps indicated by the received start point and end point information.

[0126] FIG. 20 is a diagram illustrating an example of start point distribution processing by a processing unit in a light data processing device according to the first embodiment of the present disclosure. FIG. 20 shows some pixels p included in an image Im. Referring to FIG. 20, in the start point distribution processing, the start point distribution processing unit 35 randomly changes the pixel position of the start point pixel pps within a distribution range Dpp of ±½ of predetermined pixel pitches Pa and Pb centered on the pixel position of the start point pixel pps. Here, the pixel pitch Pa is the distance between the centers pc of pixels p adjacent in the row direction. The pixel pitch Pb is the distance between the centers pc of pixels p adjacent in the column direction. The pixel pitches Pa and Pb are examples of pixel sizes.

[0127] More specifically, the start point distribution processor 35 obtains the random number Rab from a predetermined random function, and updates the center pc of the start point pixel pps to the center pc determined in accordance with the random number Rab within the distribution range Dpp, according to a predetermined algorithm.

[0128] For example, the start point distribution processor 35 performs the start point distribution process on all start point pixels pps indicated by the start point and end point information. Referring again to FIG. 5, the start point distribution processor 35 outputs the start point and end point information after the start point distribution process to the ray data generator 36.

[0129] (Generation of ray data set Dst) The light ray data generator 36 generates light ray data Dr for the number N of light rays based on the start and end point information received from the start point distribution processor 35, the intensity information received from the light distribution information generator 31, and the measurement condition data Dm in the memory 20.

[0130] More specifically, the light ray data generating unit 36 ​​acquires, from the start point / end point information, the angle number An of the measurement point Mp and the pixel number Bn of one or more start point pixels pps corresponding to the measurement point Mp.

[0131] The ray data generation unit 36 ​​calculates the coordinates of the principal point Cp in the three-dimensional polar coordinate system based on the tilt angle α and rotation angle β indicated by the measurement point Mp of the acquired angle number An, and the distance L indicated by the measurement condition data Dm. The ray data generation unit 36 ​​determines the calculated coordinates of the principal point Cp as the end point coordinates Pe(x, y, z).

[0132] The ray data generation unit 36 ​​also calculates the coordinates of the start pixel pps of the acquired pixel number Bn in the three-dimensional polar coordinate system based on the pixel position of the start pixel pps and the angle of view Wa indicated by the measurement condition data Dm. The ray data generation unit 36 ​​determines the calculated coordinates of the start pixel pps as the start coordinates Ps(x, y, z).

[0133] The ray data generation unit 36 ​​determines a vector extending from the determined start coordinate Ps(x, y, z) to the determined end coordinate Pe(x, y, z) as a ray vector Vt. Then, the ray data generation unit 36 ​​generates ray data Dr indicating the determined start coordinate Ps(x, y, z), the determined ray vector Vt, and the intensity Pw indicated by the intensity information.

[0134] When there are multiple start pixels pps corresponding to the measurement point Mp, the ray data generation unit 36 ​​determines the start coordinates Ps(x, y, z) and the ray vector Vt for each start pixel pps, and generates the ray data Dr.

[0135] After determining the start point coordinates Ps(x, y, z) and generating ray data Dr for all start point pixels pps corresponding to the measurement point Mp, the ray data generation unit 36 ​​obtains the angle number An of the new measurement point Mp and the pixel number Bn of the new start point pixel pps from the start point and end point information, determines the start point coordinates Ps(x, y, z) and ray vector Vt, and generates the ray data Dr.

[0136] When the ray data generation unit 36 ​​has completed generation of the ray data Dr for the number N of rays for all pairs of measurement points Mp and start pixels pps in the start point / end point information, it generates a ray data set Dst including the ray data Dr for the number N of rays. The ray data generation unit 36 ​​stores the generated ray data set Dst in the storage unit 20.

[0137] [Operation flow] FIG. 21 is a flowchart defining an example of an operation procedure when the ray data processing device according to the first embodiment of the present disclosure generates a ray data set.

[0138] Referring to FIG. 21, first, light ray data processing device 101 receives image data Dp from light distribution measurement device 201 (step S11).

[0139] Next, the light ray data processing device 101 accepts a user operation to specify the number N of light rays (step S12).

[0140] Next, the light ray data processing device 101 calculates a luminous flux value for each measurement point Mp based on the image data Dp, and generates a light distribution profile Pr1 indicating the correspondence between the inclination angle α and rotation angle β indicated by the measurement point Mp and the luminous flux value (step S13).

[0141] Next, the light ray data processing device 101 calculates a total light flux value TL based on the light flux value at each measurement point Mp, and determines the value obtained by dividing the total light flux value TL by the number of light rays N as the value of the intensity Pw (step S14).

[0142] Next, the light ray data processing device 101 determines the number of extracted rays Ndr using a random determination method based on the light distribution profile Pr1, and generates a light ray extraction profile Pr2 indicating the correspondence between the measurement points Mp and the number of extracted rays Ndr (step S15).

[0143] Next, the light ray data processing device 101 determines the start pixel pps using a random determination method based on the light ray extraction profile Pr2, and generates start and end point information indicating the correspondence between the measurement point Mp and the start pixel pps (step S16).

[0144] Next, the light ray data processing device 101 performs an end point distribution process to randomly change the measurement points Mp indicated by the start point and end point information (step S17).

[0145] Next, the light ray data processing device 101 performs a start point dispersion process to randomly change the pixel position of the start point pixel pps indicated by the start point and end point information (step S18).

[0146] Next, the ray data processing device 101 generates a ray data set Dst including ray data Dr for the number N of rays based on the start and end point information and the intensity Pw (step S19).

[0147] In the light ray data generation system 301 according to the first embodiment of the present disclosure, the light distribution measurement device 201 is configured to image the object S at a plurality of measurement points Mp by fixing the object S and changing the position of the detector 51, but this is not limited to this. The light distribution measurement device 201 may also be configured to image the object S at a plurality of measurement points Mp by fixing the detector 51 and rotating the object S about the origin of a three-dimensional Cartesian coordinate system.

[0148] Furthermore, in the light ray data processing device 101 according to the first embodiment of the present disclosure, the processing unit 30 is configured to determine the end point coordinates Pe(x, y, z) of the light ray vector Vt based on an imaging angle corresponding to a value randomly determined within a numerical range between the plurality of cumulative integrated values ​​Sum1 in the cumulative integrated array LA2. However, this is not limited to this. That is, the extraction information generation unit 32 in the processing unit 30 may be configured to determine the number of extracted rays Ndr for each measurement point Mp by normalizing the luminous flux value of each measurement point Mp indicated by the light distribution profile Pr1 without using a random determination method. Specifically, the extraction information generation unit 32 calculates the sum Fb of the luminous flux values ​​of each measurement point Mp indicated by the light distribution profile Pr1. Then, the extraction information generation unit 32 determines the number of extracted rays Ndr for the measurement point Mp by multiplying the luminous flux value of the measurement point Mp indicated by the light distribution profile Pr1 by (number of rays N / sum Fb).

[0149] Furthermore, in the light ray data processing device 101 according to the first embodiment of the present disclosure, the extraction information generation unit 32 is configured to generate the imaging number array LA1 in which the angle numbers An are randomly arranged, but this is not limiting. The extraction information generation unit 32 may be configured to determine the number of extractions Ndr for each measurement point Mp using a random determination method, without performing random processing to randomly shuffle the angle numbers An in the imaging number array LA1.

[0150] Furthermore, in the light ray data processing device 101 according to the first embodiment of the present disclosure, the extraction information generation unit 32 is configured to divide the range between the minimum value S1min and the maximum value S1max of the cumulative integrated value Sum1 in the cumulative integration array LA2 into a plurality of numerical ranges Rg and determine the number of extracted rays Ndr using a value randomly determined in each numerical range Rg, but this is not limited to this.The extraction information generation unit 32 may be configured to use the range between the minimum value S1min and the maximum value S1max of the cumulative integrated value Sum1 in the cumulative integration array LA2 as a single numerical range Rg and determine the number of extracted rays Ndr using a value randomly determined in that numerical range Rg, without dividing the range between the minimum value S1min and the maximum value S1max of the cumulative integrated value Sum1 in the cumulative integration array LA2 into a plurality of numerical ranges Rg.

[0151] Furthermore, in the light ray data processing device 101 according to the first embodiment of the present disclosure, the processing unit 30 is configured to determine the start coordinate Ps(x, y, z) based on the pixel position of the pixel p corresponding to a value randomly determined within a numerical range of the plurality of cumulative integrated values ​​Sum2 in the cumulative integrated array LB2. However, this is not limited to this. That is, the start pixel determination unit 33 in the processing unit 30 may be configured to determine the start pixel pps in the image Im by normalizing the intensity of the pixel p included in the image Im without using a random determination method. Specifically, the start pixel determination unit 33 calculates a sum Fp of the intensities of each pixel p in the image Im corresponding to the measurement point Mp. Then, the start pixel determination unit 33 determines the number of rays starting from the pixel p by multiplying the intensity of the pixel p in the image Im by (the number of extracted rays Ndr / the sum Fp). That is, if the value obtained by multiplying the intensity of pixel p by (number of extracted lines Ndr / total sum Fp) is 1 or more, the start pixel determination unit 33 determines the pixel p as the start pixel pps.

[0152] Furthermore, in the light ray data processing device 101 according to the first embodiment of the present disclosure, the start pixel determiner 33 is configured to generate a pixel number array LB1 in which pixel numbers Bn are randomly arranged, but this is not limiting. The start pixel determiner 33 may be configured to determine the start pixel pps for each measurement point Mp using a random determination method, without performing random processing to randomly shuffle the pixel numbers Bn in the pixel number array LB1.

[0153] Furthermore, in the light ray data processing device 101 according to the first embodiment of the present disclosure, the start pixel determiner 33 is configured to divide the minimum value S2min and the maximum value S2max of the cumulative integrated value Sum2 in the cumulative integration array LB2 into a plurality of numerical ranges Rh and determine the start pixel pps using a value randomly determined in each numerical range Rh, but this is not limited to this.The start pixel determiner 33 may be configured to use the range between the minimum value S2min and the maximum value S2max of the cumulative integrated value Sum2 in the cumulative integration array LB2 as a single numerical range Rh and determine the start pixel pps using a value randomly determined in that numerical range Rh, without dividing the range between the minimum value S2min and the maximum value S2max of the cumulative integrated value Sum2 in the cumulative integration array LB2 into a plurality of numerical ranges Rh.

[0154] Furthermore, in the light ray data processing device 101 according to the first embodiment of the present disclosure, the processing unit 30 is configured to perform end point distribution processing and determine the end point coordinates Pe(x, y, z) of the light vector Vt based on the imaging angle after the end point distribution processing, but this is not limited to this. The processing unit 30 may be configured not to include the end point distribution processing unit 34. In this case, the light ray data generation unit 36 ​​generates light ray data Dr based on start point and end point information that has not been subjected to end point distribution processing.

[0155] Furthermore, in the light data processing device 101 according to the first embodiment of the present disclosure, the endpoint dispersion processing unit 34 is configured to randomly change the imaging angle within a dispersion range Dmp of ±½ of the measurement intervals Wα and Wβ centered on the imaging angle indicated by the measurement point Mp, but this is not limited to this. The endpoint dispersion processing unit 34 may also be configured to randomly change the imaging angle within a range different from the dispersion range Dmp.

[0156] Furthermore, in the light ray data processing device 101 according to the first embodiment of the present disclosure, the processing unit 30 is configured to perform start point distribution processing and determine the start point coordinate Ps(x, y, z) based on the pixel position of pixel p after the start point distribution processing, but this is not limited to this. The processing unit 30 may be configured not to include the start point distribution processing unit 35. In this case, the light ray data generation unit 36 ​​generates light ray data Dr based on start point and end point information that has not been subjected to start point distribution processing.

[0157] Furthermore, in the light ray data processing device 101 according to the first embodiment of the present disclosure, the start point dispersion processor 35 is configured to randomly change the pixel position of the start pixel pps within a dispersion range Dpp of ±½ of the pixel pitch Pa, Pb centered on the pixel position of the start pixel pps, but this is not limited to this. The start point dispersion processor 35 may also be configured to randomly change the pixel position of the start pixel pps within a range different from the dispersion range Dpp.

[0158] Next, other embodiments of the present disclosure will be described with reference to the drawings. In the drawings, the same or corresponding parts are designated by the same reference numerals and their description will not be repeated.

[0159] <Second embodiment> [Configuration and basic operation] This embodiment is different from the ray data generation system 301 according to the first embodiment in that it relates to a ray data generation system 302 that generates a ray data set Dst using a plurality of images Im obtained by capturing images of an object S at a plurality of imaging positions translated relative to the object S. Contents other than those described below are the same as those of the ray data generation system 301 according to the first embodiment.

[0160] 22 is a diagram showing the configuration of a light ray data generation system according to the second embodiment of the present disclosure. Compared to light ray data generation system 301, light ray data generation system 302 includes light ray data processing device 102 instead of light ray data processing device 101, and includes light distribution measurement device 202 instead of light distribution measurement device 201.

[0161] (Light distribution measuring device) Light distribution measurement device 202 includes detector 51, X-stage 61, Y-stage 63, and support base 56. X-stage 61 includes table 62 that is movable in a direction parallel to the X-axis. Y-stage 63 includes table 64 that is movable in a direction parallel to the Y-axis. Y-stage 63 is connected to table 62 of X-stage 61. Detector 51 is attached to table 64 of Y-stage 63.

[0162] Light distribution measurement device 202 is capable of translating the position of detector 51 relatively to object S while maintaining distance L between object S and principal point Cp of detector 51, and measures the near-field light distribution of object S. More specifically, table 62 of X-stage 61 moves in a direction parallel to the X-axis, causing detector 51 to move in a direction parallel to the X-axis. Table 64 of Y-stage 63 moves in a direction parallel to the Y-axis, causing detector 51 to move in a direction parallel to the Y-axis. In other words, light distribution measurement device 202 translates detector 51 in the XY plane. Detector 51 generates an image Im of object S by capturing an image of object S with principal point Cp located at one or more measurement points Mq in the XY plane.

[0163] Light distribution measurement device 202 receives a measurement control command indicating one or more measurement points Mq from a control device (not shown) or light ray data processing device 102. X-stage 61 and Y-stage 63 in light distribution measurement device 202 operate in accordance with the measurement control command. Detector 51 generates an image Im by capturing an image of object S in a state where principal point Cp is positioned at measurement point Mq indicated by the measurement control command.

[0164] For example, detector 51 captures images of object S at multiple measurement points Mq at measurement intervals Wx and Wy specified by the user. Measurement interval Wx is the measurement interval in the X-axis direction, and measurement interval Wy is the measurement interval in the Y-axis direction. As an example, detector 51 captures images of object S at 2601 (51 × 51) measurement points Mq, each consisting 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, thereby generating 2601 images Im.

[0165] The detector 51 generates image data Dq indicating the correspondence between the generated image Im and measurement points Mq expressed using X and Y coordinates. The detector 51 also generates measurement condition data Dm indicating the angle of view Wa of the image Im 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 light ray data processing device 102.

[0166] (Configuration of the light data processing device) FIG. 23 is a diagram illustrating a configuration of a light ray data processing device according to a second embodiment of the present disclosure. Referring to FIG. 23, compared to the light ray data processing device 101, the light ray data processing device 102 includes an acquisition unit 70 instead of the acquisition unit 10 and a processing unit 80 instead of the processing unit 30. The processing unit 80 is an example of a first distribution unit, an example of a second distribution unit, and an example of a generation unit. One or both of the acquisition unit 70 and the processing unit 80 are realized, for example, by a processing circuit including one or more processors. The storage unit 20 is, for example, a non-volatile memory included in the processing circuit.

[0167] 24 is a diagram showing an example of image data acquired by an acquisition unit in a light ray data processing device according to a second embodiment of the present disclosure. Referring to FIG. 24 , the acquisition unit 70 acquires image data Dq indicating a correspondence between a plurality of images Im obtained by capturing images of the object S at a plurality of imaging positions translated relative to the object S and the imaging positions. More specifically, the acquisition unit 70 receives the image data Dq indicating a correspondence between the X coordinate and Y coordinate indicating the measurement point Mq and the image Im from the light distribution measurement device 202. The acquisition unit 70 also receives measurement condition data Dm from the light distribution measurement device 202. The acquisition unit 70 stores the received image data Dq and measurement condition data Dm in the storage unit 20.

[0168] The processing unit 80 generates a ray data set Dst indicating the starting points and vectors of rays emanating from the object S, based on the image data Dq acquired by the acquisition unit 70. More specifically, the processing unit 80 receives a user operation specifying the number of rays N. The processing unit 80 generates a ray data set Dst including ray data Dr for the specified number of rays N, in accordance with the received user operation.

[0169] Fig. 25 is a diagram illustrating an example of a method for generating a ray data set by a processing unit in a ray data processing device according to a second embodiment of the present disclosure. Fig. 25 illustrates the positional relationship between a detector 51 on the XZ plane and an imaging plane Is of the detector 51. The imaging plane Is is a surface on the XY plane that is perpendicular to a line passing through the object S and the principal point Cp.

[0170] 25, the processing unit 80 determines a start pixel pps, which is a pixel p that should be the start point of a light ray, based on the number N of light rays and the intensity of each pixel p in multiple images Im. The processing unit 80 calculates the coordinates of the start pixel pps in a three-dimensional polar coordinate system based on the angle of view Wa indicated by the measurement condition data Dm in the storage unit 20. The processing unit 80 determines start coordinates Ps(x, y, z) based on the calculated coordinates of the start pixel pps. The start coordinates Ps(x, y, z) are coordinates on the imaging plane Is.

[0171] The processing unit 80 also calculates the coordinates of the principal point Cp in a three-dimensional polar coordinate system based on the measurement point Mq corresponding to the image Im and the distance L indicated by the measurement condition data Dm. The processing unit 80 determines the end point coordinate Pe(x,y,z) based on the calculated coordinates of the principal point Cp. The processing unit 80 then determines the vector extending from the determined start point coordinate Ps(x,y,z) to the determined end point coordinate Pe(x,y,z) as the ray vector Vt.

[0172] Furthermore, the processing unit 80 calculates a total luminous flux value TL of the object S based on all images Im indicated by the image data Dq. The processing unit 80 calculates a luminous flux value per ray by dividing the calculated total luminous flux value TL by the number of light rays N. The processing unit 80 determines the calculated luminous flux value per ray as the value of the intensity Pw of the light ray data Dr.

[0173] The processing unit 80 generates ray data Dr indicating the determined start point coordinates Ps(x, y, z), the determined ray vector Vt, and the determined intensity. The processing unit 80 generates N pieces of ray data Dr, and generates a ray data set Dst including the N pieces of ray data Dr.

[0174] (Generation of light distribution profile Pr3) When the image data Dq is stored in the storage unit 20 by the acquisition unit 70, the processing unit 80 acquires the image data Dq. The processing unit 80 calculates the luminous intensity at each measurement point Mq indicated by the image data Dq. More specifically, the processing unit 80 calculates the sum of the intensities of each pixel p of the image Im corresponding to the measurement point Mq as the luminous intensity at the measurement point Mq. The processing unit 80 calculates the luminous intensity for each measurement point Mq.

[0175] The processing unit 80 calculates the luminous flux value for each measurement point Mq in accordance with, for example, Japanese Industrial Standards (JIS C 8105-5). Here, because the measurement points Mq are positions on a plane, it is not necessary to correct the luminous intensity at each measurement point Mq using a zonal coefficient. Therefore, the processing unit 80 calculates the luminous flux value at the measurement point Mq without multiplying the luminous intensity at the measurement point Mq by the zonal coefficient.

[0176] 26 is a diagram showing an example of a light distribution profile generated by a processing unit in a light ray data processing device according to the second embodiment of the present disclosure. Referring to Fig. 26, processing unit 80 calculates a luminous flux value for each measurement point Mq and generates a light distribution profile Pr3 indicating the correspondence between the X and Y coordinates of measurement point Mq and the luminous flux value.

[0177] Furthermore, the processing unit 80 calculates a total luminous flux value TL of the object S based on the luminous flux value at each measurement point Mq in accordance with, for example, Japanese Industrial Standards (JIS C 8105-5). The processing unit 80 determines the value obtained by dividing the calculated total luminous flux value TL by the number N of light rays as the value of the intensity Pw.

[0178] (Generation of ray extraction profile Pr4) 27 is a diagram showing an example of a light ray extraction profile generated by a processing unit in a light data processing device according to the second embodiment of the present disclosure. Referring to Fig. 27, the processing unit 80 determines the number of extracted rays Ndr for each measurement point Mq based on the light distribution profile Pr3.

[0179] For example, processing unit 80 determines the number of rays Ndr to be extracted for each measurement point Mq by normalizing the luminous flux value at each measurement point Mq indicated by light distribution profile Pr3. More specifically, processing unit 80 calculates the sum Fc of the luminous flux values ​​at each measurement point Mq indicated by light distribution profile Pr3. Processing unit 80 then determines the value obtained by multiplying the luminous flux value at measurement point Mq indicated by light distribution profile Pr3 by (number of rays N / sum Fc) as the number Ndr to be extracted for that measurement point Mq.

[0180] The processing unit 80 determines the number of extracted rays Ndr for each measurement point Mq, and generates a ray extraction profile Pr4 that indicates the correspondence between the measurement points Mq and the number of extracted rays Ndr.

[0181] (Generating start and end point information) The processing unit 80 determines the starting pixel pps for each measurement point Mq based on the image data Dq and the light ray extraction profile Pr4.

[0182] For example, the processing unit 80 determines the start pixel pps in the image Im by normalizing the intensity of each pixel p included in the image Im. More specifically, the processing unit 80 calculates the sum Fq of the intensities of each pixel p in the image Im corresponding to the measurement point Mq. Then, the processing unit 80 determines the value obtained by multiplying the intensity of the pixel p in the image Im by (number of extracted rays Ndr / sum Fq) as the number of rays starting from the pixel p. That is, if the value obtained by multiplying the intensity of the pixel p by (number of extracted rays Ndr / sum Fq) is 1 or greater, the processing unit 80 determines the pixel p as the start pixel pps.

[0183] The processing unit 80 generates start and end point information indicating the correspondence between the identifier of the measurement point Mq and the identifier of the determined start pixel pps.

[0184] (Generation of ray data set Dst) The processing unit 80 generates light beam data Dr for the number N of light beams based on the start and end point information, intensity information, and measurement condition data Dm in the storage unit 20.

[0185] More specifically, the processing unit 80 acquires, from the start point / end point information, the identifier of the measurement point Mq and the identifiers of one or more start point pixels pps corresponding to the measurement point Mq.

[0186] The processing unit 80 calculates the coordinates of the principal point Cp in the three-dimensional 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 end point coordinates Pe(x, y, z).

[0187] The processing unit 80 also calculates the coordinates of the start pixel pps in the three-dimensional polar coordinate system based on the pixel position of the acquired start pixel pps and the angle of view Wa indicated by the measurement condition data Dm. The processing unit 80 determines the calculated coordinates of the start pixel pps as the start coordinates Ps(x, y, z).

[0188] The processing unit 80 determines a vector extending from the determined start coordinate Ps(x, y, z) to the determined end coordinate Pe(x, y, z) as a ray vector Vt. Then, the processing unit 80 generates ray data Dr indicating the determined start coordinate Ps(x, y, z), the determined ray vector Vt, and the intensity Pw indicated by the intensity information.

[0189] When there are multiple start pixels pps corresponding to the measurement point Mq, the processing unit 80 determines the start coordinates Ps(x, y, z) and the ray vector Vt for each start pixel pps, and generates the ray data Dr.

[0190] After the processing unit 80 determines the start coordinates Ps(x, y, z) and generates ray data Dr for all start pixels pps corresponding to the measurement point Mq, it obtains the identifier of the new measurement point Mq and the identifier of the new start pixel pps from the start and end point information, determines the start coordinates Ps(x, y, z) and ray vector Vt, and generates the ray data Dr.

[0191] When the processing unit 80 has completed generating the light ray data Dr for the number N of rays for all pairs of measurement points Mq and start pixels pps in the start point / end point information, it generates a light ray data set Dst including the light ray data Dr for the number N of rays. The processing unit 80 stores the generated light ray data set Dst in the storage unit 20.

[0192] [Operation flow] FIG. 28 is a flowchart defining an example of an operation procedure when a ray data processing device according to the second embodiment of the present disclosure generates a ray data set.

[0193] Referring to FIG. 28, first, light ray data processing device 102 receives image data Dq from light distribution measurement device 202 (step S21).

[0194] Next, the light ray data processing device 102 accepts a user operation to specify the number N of light rays (step S22).

[0195] Next, the light ray data processing device 102 calculates a luminous flux value for each measurement point Mq based on the image data Dq, and generates a light distribution profile Pr3 indicating the correspondence between the X coordinate and Y coordinate indicated by the measurement point Mq and the luminous flux value (step S23).

[0196] Next, the light ray data processing device 102 calculates a total light flux value TL based on the light flux value at each measurement point Mq, and determines the value obtained by dividing the total light flux value TL by the number of light rays N as the value of the intensity Pw (step S24).

[0197] Next, the light ray data processing device 102 determines the number of extracted rays Ndr for each measurement point Mq based on the light distribution profile Pr3, and generates a light ray extraction profile Pr4 indicating the correspondence between the measurement points Mq and the number of extracted rays Ndr (step S25).

[0198] Next, the light ray data processing device 102 determines a start pixel pps for each measurement point Mq based on the light ray extraction profile Pr4, and generates start and end point information indicating the correspondence between the measurement point Mq and the start pixel pps (step S26).

[0199] Next, the ray data processing device 102 generates a ray data set Dst including ray data Dr for the number N of rays based on the start and end point information and the intensity Pw (step S27).

[0200] In the light ray data generation system 302 according to the second embodiment of the present disclosure, the light distribution measurement device 202 is configured to capture images of the object S at multiple measurement points Mq by translating the detector 51 in the XY plane, but the present invention is not limited to this. The light distribution measurement device 202 may also be configured to capture images of the object S at multiple measurement points Mq by fixing the detector 51 and translating the object S in the XY plane. In this case, the light ray data processing device 102 converts the amount of movement of the object S in the XY plane into the amount of movement of the detector 51 relative to the object S, and then determines the end point coordinate Pe(x, y, z) and the start point coordinate Ps(x, y, z).

[0201] Furthermore, in the light ray data processing device 102 according to the second embodiment of the present disclosure, the processing unit 80 may be configured to determine the number of extracted rays Ndr for each measurement point Mq using a random determination method based on the light distribution profile Pr3, similar to the processing unit 30. More specifically, the processing unit 80 creates a position number array in which the position numbers of the image capture positions are arranged, and an accumulation array in which the accumulated integrated values ​​of the luminous flux values ​​at the image capture positions are arranged in the order of the position numbers in the position number array. The processing unit 80 determines the end point of the light ray vector Vt based on the image capture position corresponding to a random value randomly determined within a numerical range between the multiple accumulated integrated values ​​in the accumulation integration array. That is, the processing unit 80 generates the light ray extraction profile Pr4 by repeating the process of incrementing the number of extracted rays Ndr at the image capture position corresponding to the random value a number of times corresponding to the number of light rays N.

[0202] Furthermore, in the light ray data processing device 102 according to the second embodiment of the present disclosure, the processing unit 80 may be configured to determine a start pixel pps for each measurement point Mq using a random determination method based on the image data Dq and the light ray extraction profile Pr4, similar to the processing unit 30. More specifically, the processing unit 80 creates a pixel number array in which the pixel numbers of pixels p in the image Im are arranged, and an accumulation array in which the accumulated integrated values ​​of the intensities of pixels p are arranged in accordance with the arrangement order of the pixel numbers in the pixel number array. The processing unit 80 determines the start pixel pps to be the start point of the light ray based on the pixel position of pixel p corresponding to a random value randomly determined within a numerical range between multiple accumulation integrated values ​​in the accumulation integrated array.

[0203] Furthermore, in the light data processing device 102 according to the second embodiment of the present disclosure, the processing unit 80 may be configured to perform end point dispersion processing in which the measurement point Mq in the image data Dq is randomly changed, similar to the processing unit 30, or may be configured to perform start point dispersion processing in which the pixel position of the pixel p in the image Im of the image data Dq is randomly changed.

[0204] The above-described embodiments should be considered to be illustrative in all respects and not restrictive. The scope of the present invention is defined by the claims, not by the above description, and is intended to include all modifications within the meaning and scope of the claims.

[0205] Each process (each function) in the above-described embodiments is realized by a processing circuit including one or more processors. The processing circuit may be configured as an integrated circuit or the like that combines one or more memories, various analog circuits, and various digital circuits in addition to the one or more processors. The one or more memories store programs (instructions) that cause the one or more processors to execute each of the processes. The one or more processors may execute each of the processes according to the program read from the one or more memories, or according to a logic circuit pre-designed to execute each of the processes. The processor may be various processors suitable for computer control, such as a central processing unit (CPU), a graphics processing unit (GPU), a digital signal processor (DSP), a field programmable gate array (FPGA), and an application-specific integrated circuit (ASIC). Note that the physically separate processors may cooperate with each other to execute each of the processes. For example, the processors mounted on a plurality of physically separated computers may cooperate with each other to execute the above processes via a network such as a LAN (Local Area Network), a WAN (Wide Area Network), the Internet, etc. The program may be installed into the memory from an external server device or the like via the network, or may be distributed in a state stored on a recording medium such as a CD-ROM (Compact Disc Read Only Memory), a DVD-ROM (Digital Versatile Disc Read Only Memory), or a semiconductor memory, and installed into the memory from the recording medium. [Explanation of symbols]

[0206] 10,70 Acquisition Department 20 Memory section 30,80 Processing section 31 Light distribution information generation unit 32 Extraction information generation section 33 Starting pixel determination unit 34 End point distributed processing unit 35 Starting point distributed processing unit 36 Ray data generation 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 Light data processing device 201,202 Light distribution measuring device 301,302 Ray Data Generation System S Object E1,E2 arrows Sp sphere Cp principal point Im Images Dr. Ray Data Dst ray dataset Dp, Dq image data Is imaging surface Wa angle of view L distance Ps Starting point coordinates Pe End point coordinates Vt ray vector Pr1, Pr3 light distribution profile Pr2,Pr4 ray extraction profile Rg1, Rg2, Rh1, Rh2 numerical range S1max, S2max maximum value S1min, S2min minimum value Rv1,Rv2 random numbers Dmp, Dpp dispersion range Wα,Wβ measurement interval pc center Pa,Pb pixel pitch

Claims

1. A light ray data processing device that generates a light ray data set used to calculate a light distribution characteristic of an object, comprising: an acquisition unit that acquires a plurality of images obtained by capturing images of the object at a plurality of imaging angles at a predetermined interval and image data indicating a correspondence relationship between the imaging angles; a generation unit that generates the ray data set indicating starting points and vectors of rays emanating from the object based on the image data acquired by the acquisition unit; a first distribution unit that performs a first distribution process of randomly changing at least one of the plurality of imaging angles in the image data, The generation unit determines an end point of the vector based on the imaging angle after the first distribution processing in the first distribution unit, and generates the ray data set indicating the determined vector.

2. The light ray data processing device according to claim 1 , wherein the first dispersion unit randomly changes the imaging angle within a range of ±½ of the predetermined interval centered on the imaging angle.

3. A light ray data processing device that generates a light ray data set used to calculate a light distribution characteristic of an object, comprising: an acquisition unit that acquires an image obtained by capturing an image of the object at a predetermined imaging angle and image data that indicates a correspondence relationship between the imaging angle; a generation unit that generates the ray data set indicating starting points and vectors of rays emanating from the object based on the image data acquired by the acquisition unit; a second distribution unit that performs second distribution processing to randomly change a pixel position of at least one of a plurality of pixels in the image of the image data, The generation unit determines the starting point based on a pixel position of the pixel after the second distribution process, and generates the ray data set indicating the determined starting point.

4. The light ray data processing device according to claim 3 , wherein the second distribution unit randomly changes the pixel position of the pixel within a range of ±½ of a pixel size centered on the pixel position of the pixel.

5. A light ray data processing device that generates a light ray data set used to calculate a light distribution characteristic of an object, comprising: an acquisition unit that acquires an image obtained by capturing an image of the object at a predetermined imaging angle and image data that indicates a correspondence relationship between the imaging angle; a generation unit that generates the light ray data set indicating starting points and vectors of light rays emitted from the object based on the image data acquired by the acquisition unit, the generation unit creates a pixel number array in which pixel numbers of pixels in the image are arranged, and an accumulated integration array in which accumulated integration values ​​of intensities of the pixels are arranged in accordance with the arrangement order of the pixel numbers in the pixel number array, determines the starting point based on a pixel position of the pixel corresponding to a value randomly determined in a numerical range between a plurality of the accumulated integration values ​​in the accumulated integration array, and generates the light ray data set indicating the determined starting point.

6. The light ray data processing device according to claim 5 , wherein the generating section generates the pixel number array in which the pixel numbers are randomly arranged.

7. 7. The light ray data processing device according to claim 5, wherein the generation unit divides a range between a minimum value and a maximum value of the cumulative integrated value in the cumulative integrated array into a plurality of numerical ranges, and determines the starting point based on a pixel position of the pixel corresponding to a value randomly determined in each of the numerical ranges.

8. A light ray data processing device that generates a light ray data set used to calculate a light distribution characteristic of an object, comprising: an acquisition unit that acquires a plurality of images obtained by capturing images of the object at a plurality of imaging angles and image data indicating a correspondence relationship between the imaging angles; a generation unit that generates the light ray data set indicating starting points and vectors of light rays emitted from the object based on the image data acquired by the acquisition unit, the generation unit creates an imaging number array in which angle numbers of the imaging angles are arranged, and an accumulated integration array in which accumulated integrated values ​​of light flux values ​​at the imaging angles are arranged in accordance with the arrangement order of the angle numbers in the imaging number array, determines an end point of the vector based on the imaging angle corresponding to a value randomly determined in a numerical range between a plurality of the accumulated integrated values ​​in the accumulated integration array, and generates the light ray data set indicating the determined vector.

9. The light ray data processing device according to claim 8 , wherein the generation unit generates the imaging number sequence in which the angle numbers are randomly arranged.

10. 10. The light ray data processing device according to claim 8, wherein the generation unit divides a range between a minimum value and a maximum value of the cumulative integrated value in the cumulative integrated array into a plurality of numerical ranges, and determines an end point of the vector based on the imaging angle corresponding to a value randomly determined in each of the numerical ranges.

11. A light ray data processing device that generates a light ray data set used to calculate a light distribution characteristic of an object, comprising: an acquisition unit that acquires a plurality of images obtained by capturing images of the object at a plurality of imaging positions that are translated relative to the object, and acquires image data that indicates a correspondence between the imaging positions; a generation unit that generates the ray data set indicating starting points and vectors of ray beams emanating from the object based on the image data acquired by the acquisition unit.

12. A ray data processing method in a ray data processing device that generates a ray data set used to calculate a light distribution characteristic of an object, comprising: acquiring a plurality of images obtained by capturing images of the object at a plurality of imaging angles at a predetermined interval, and image data indicating a correspondence relationship between the imaging angles; generating the ray data set based on the acquired image data, the ray data set indicating starting points and vectors of rays emanating from the object; performing a first distribution process of randomly changing at least one of the plurality of imaging angles in the image data; A ray data processing method, wherein in the step of generating the ray data set, an end point of the vector is determined based on the imaging angle after the first distribution processing, and the ray data set indicating the determined vector is generated.

13. A ray data processing method in a ray data processing device that generates a ray data set used to calculate a light distribution characteristic of an object, comprising: acquiring an image obtained by capturing an image of the object at a predetermined imaging angle and image data indicating a correspondence relationship between the imaging angle; generating the ray data set based on the acquired image data, the ray data set indicating starting points and vectors of rays emanating from the object; and performing a second distribution process of randomly changing a pixel position of at least one of a plurality of pixels in the image of the image data, a light ray data processing method, in which in the step of generating the light ray data set, the starting point is determined based on the pixel position of the pixel after the second distribution processing, and the light ray data set indicating the determined starting point is generated.

14. A ray data processing method in a ray data processing device that generates a ray data set used to calculate a light distribution characteristic of an object, comprising: acquiring an image obtained by capturing an image of the object at a predetermined imaging angle and image data indicating a correspondence relationship between the imaging angle; generating the ray data set indicating starting points and vectors of rays emanating from the object based on the acquired image data; a light ray data processing method, in which the step of generating the light ray data set includes creating a pixel number array in which pixel numbers of pixels in the image are arranged, and an accumulation accumulation array in which accumulated accumulation values ​​of the intensities of the pixels are arranged in accordance with the arrangement order of the pixel numbers in the pixel number array, determining the starting point based on a pixel position of the pixel corresponding to a value randomly determined within a numerical range between a plurality of the accumulated accumulation values ​​in the accumulation accumulation array, and generating the light ray data set indicating the determined starting point.

15. A ray data processing method in a ray data processing device that generates a ray data set used to calculate a light distribution characteristic of an object, comprising: acquiring a plurality of images obtained by capturing images of the object at a plurality of imaging angles and image data indicating a correspondence relationship between the imaging angles; generating the ray data set indicating starting points and vectors of rays emanating from the object based on the acquired image data; a light ray data processing method in which the step of generating the light ray data set includes creating an imaging number array in which the angle numbers of the imaging angles are arranged, and an accumulated integration array in which accumulated integrated values ​​of light flux values ​​at the imaging angles are arranged in accordance with the arrangement order of the angle numbers in the imaging number array, determining an end point of the vector based on the imaging angle corresponding to a value randomly determined in a numerical range between a plurality of the accumulated integrated values ​​in the accumulated integration array, and generating the light ray data set indicating the determined vector.

16. A ray data processing method in a ray data processing device that generates a ray data set used to calculate a light distribution characteristic of an object, comprising: acquiring image data indicating a correspondence between a plurality of images obtained by capturing images of the object at a plurality of imaging positions that are translated relative to the object and the imaging positions; generating the ray data set indicating starting points and vectors of rays emanating from the object based on the acquired image data.

17. A ray data processing program used in a ray data processing device that generates a ray data set used to calculate a light distribution characteristic of an object, comprising: Computer, an acquisition unit that acquires a plurality of images obtained by capturing images of the object at a plurality of imaging angles at a predetermined interval and image data indicating a correspondence relationship between the imaging angles; a generation unit that generates the ray data set indicating starting points and vectors of rays emanating from the object based on the image data acquired by the acquisition unit; a first distribution unit that performs a first distribution process of randomly changing at least one of the plurality of imaging angles in the image data; It is a program to function as The generation unit determines an end point of the vector based on the imaging angle after the first distribution processing in the first distribution unit, and generates the ray data set indicating the determined vector.

18. A ray data processing program used in a ray data processing device that generates a ray data set used to calculate a light distribution characteristic of an object, comprising: Computer, an acquisition unit that acquires an image obtained by capturing an image of the object at a predetermined imaging angle and image data that indicates a correspondence relationship between the imaging angle; a generation unit that generates the ray data set indicating starting points and vectors of rays emanating from the object based on the image data acquired by the acquisition unit; a second distribution unit that performs second distribution processing to randomly change the pixel position of at least one of a plurality of pixels in the image of the image data; It is a program to function as the generation unit determines the starting point based on a pixel position of the pixel after the second distribution processing, and generates the ray data set indicating the determined starting point.

19. A ray data processing program used in a ray data processing device that generates a ray data set used to calculate a light distribution characteristic of an object, comprising: Computer, an acquisition unit that acquires an image obtained by capturing an image of the object at a predetermined imaging angle and image data that indicates a correspondence relationship between the imaging angle; a generation unit that generates the ray data set indicating starting points and vectors of rays emanating from the object based on the image data acquired by the acquisition unit; It is a program to function as the generation unit creates a pixel number array in which pixel numbers of pixels in the image are arranged, and an accumulated integration array in which accumulated integration values ​​of the intensities of the pixels are arranged in accordance with the arrangement order of the pixel numbers in the pixel number array, determines the starting point based on a pixel position of the pixel corresponding to a value randomly determined in a numerical range between a plurality of the accumulated integration values ​​in the accumulated integration array, and generates the light data set indicating the determined starting point.

20. A ray data processing program used in a ray data processing device that generates a ray data set used to calculate a light distribution characteristic of an object, comprising: Computer, an acquisition unit that acquires a plurality of images obtained by capturing images of the object at a plurality of imaging angles and image data indicating a correspondence relationship between the imaging angles; a generation unit that generates the ray data set indicating starting points and vectors of rays emanating from the object based on the image data acquired by the acquisition unit; It is a program to function as the generation unit creates an imaging number array in which angle numbers of the imaging angles are arranged, and an accumulated integration array in which accumulated integrated values ​​of light flux values ​​at the imaging angles are arranged in accordance with the arrangement order of the angle numbers in the imaging number array, determines an end point of the vector based on the imaging angle corresponding to a value randomly determined in a numerical range between a plurality of the accumulated integrated values ​​in the accumulated integration array, and generates the light ray data set indicating the determined vector.

21. A ray data processing program used in a ray data processing device that generates a ray data set used to calculate a light distribution characteristic of an object, comprising: Computer, an acquisition unit that acquires a plurality of images obtained by capturing images of the object at a plurality of imaging positions that are translated relative to the object, and acquires image data that indicates a correspondence between the imaging positions; a generation unit that generates the ray data set indicating starting points and vectors of rays emanating from the object based on the image data acquired by the acquisition unit; A ray data processing program to function as a

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