Headlight test machine, method for measurement, and measurement program

Abstract

To provide a mechanism which can run a test on a large variety of headlight machines.SOLUTION: A headlight test machine includes: a screen on which a headlight of a vehicle projects light; an RGB camera which takes an image projected on the screen; a correction filter which is arranged on the front stage of the RGB camera; and a processor which processes output of the RGB camera. The correction filter has a transmission characteristic of a green filter of the RGM camera and a transmission characteristic determined by spectral luminous efficiency. The processor calculates the light intensity of the headlight on the basis of the green output of the RGB camera.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to a headlamp tester, a measurement method, and a measurement program.

Background Art

[0002] Among automotive headlamps, passing headlamps (so-called low beams) are required to irradiate the front direction of the vehicle widely and visibly, while also preventing glare to the drivers of oncoming vehicles and preceding vehicles. To meet such requirements, the luminous intensity and light distribution characteristics of the headlamp are managed.

[0003] Luminous intensity is a physical quantity that the human eye perceives, representing the brightness of light radiated from a certain point light source in a certain direction. Luminous intensity is a measured quantity obtained by reflecting the visual sensitivity characteristics of the human eye. Luminous intensity is measured by arranging a visual sensitivity filter corresponding to the visual sensitivity characteristics of the human eye in front of the camera.

[0004] Regarding the measurement of such headlamp altitude and light distribution characteristics, etc., the following prior arts exist.

[0005] Japanese Unexamined Patent Application Publication No. 2007-163149 (Patent Document 1) discloses a method for adjusting the optical axis of a headlamp with higher accuracy and stability.

[0006] Japanese Patent No. 6548879 (Patent Document 2) and Japanese Patent No. 6570816 (Patent Document 3) disclose a color headlamp tester that performs a headlamp test by color image processing of the received light image of the headlamp.

[0007] Japanese Unexamined Patent Application Publication No. 2020-91182 (Patent Document 4) discloses a color image processing type headlamp tester that forms a cut-off line.

[0008] Japanese Patent Application Laid-Open No. 2020-101395 (Patent Document 5) discloses a headlight tester suitable for a case where the light (irradiation light) of the headlight of a test vehicle is a high-intensity lamp that turns on and off (flashes) at a predetermined cycle.

[0009] Japanese Patent Application Laid-Open No. 2017-67656 (Patent Document 6) discloses a technique capable of detecting an elbow point with relatively high accuracy.

[0010] Shinichiro Ito et al., "On the Detection of the Irradiation Direction of Headlights for Passing Vehicles" (Non-Patent Document 1) discloses an improvement of a technique capable of detecting an elbow point with relatively high accuracy.

Prior Art Documents

Patent Documents

[0011]

Patent Document 1

Patent Document 2

Patent Document 3

Patent Document 4

Patent Document 5

Patent Document 6

Non-Patent Documents

[0012]

Non-Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0013] One object of the present invention is to provide a mechanism capable of testing various headlights.

Means for Solving the Problems

[0014] (Configuration 1) A headlight tester according to an aspect of the present invention includes a screen on which light from a vehicle headlight is projected, an RGB camera that images an image projected on the screen, a correction filter disposed in front of the RGB camera, and a processing device that processes the output of the RGB camera. The correction filter has a transmittance characteristic determined based on the transmittance characteristic of the green filter of the RGB camera and the specific visual sensitivity. The processing device calculates the luminous intensity of the headlight based on the green output of the RGB camera.

[0015] (Configuration 2) In Configuration 1, the transmittance characteristic of the correction filter may be a result of dividing the specific visual sensitivity by the transmittance characteristic of the green filter.

[0016] (Configuration 3) In Configuration 1 or 2, the correction filter may be configured by stacking a plurality of simple Gaussian notch filters.

[0017] (Configuration 4) A headlight tester according to another aspect of the present invention includes a screen on which light from a vehicle headlight is projected, a camera that images an image projected on the screen, and a processing device that processes the output of the camera. The processing device discriminates the type of the light source of the headlight based on a first measurement image captured when a narrow-band band-pass filter having a center wavelength of 440 nm is disposed in front of the camera and a second measurement image captured when a specific visual sensitivity filter reflecting the specific visual sensitivity is disposed in front of the camera.

[0018] (Configuration 5) In Configuration 4, the processing device may discriminate the type of the light source of the headlight based on a discrimination value based on a difference between a value obtained by dividing an integrated value of pixel values included in the first measurement image by a wavelength integrated value of the transmittance characteristic of the band-pass filter and a value obtained by dividing an integrated value of pixel values included in the second measurement image by a wavelength integrated value of the transmittance characteristic of the specific visual sensitivity filter.

[0019] (Configuration 6) In Configuration 4 or 5, the contrast sensitivity filter may have a transmittance characteristic corresponding to the contrast sensitivity, or a transmittance characteristic determined based on the transmittance characteristic of the green filter of the RGB camera and the contrast sensitivity.

[0020] (Configuration 7) In any of Configurations 4 to 6, the processing device may determine which of a high-intensity discharge (HID) lamp, a light-emitting diode (LED), and a halogen lamp is the light source of the headlight.

[0021] (Configuration 8) In any of Configurations 4 to 7, the first measurement image may be captured with a neutral density filter disposed in addition to the band-pass filter, and the second measurement image may be captured with a neutral density filter disposed in addition to the contrast sensitivity filter.

[0022] (Configuration 9) A headlight tester according to still another aspect of the present invention includes a screen onto which light from a vehicle headlight is projected, a camera that images an image projected onto the screen, and a processing device that acquires a measurement image imaged by the camera. The processing device sequentially sets an area of a predetermined size for the measurement image, and based on a first integrated value and a second integrated value obtained by multiplying a first matrix and a second matrix by each area, respectively, extracts pixels representing an area that satisfies a first condition as a first candidate point group, and for each pixel included in the first candidate point group, the number of pixels having a light intensity lower than a predetermined value in the upper right area with respect to the pixel as a reference, and the number of pixels having a light intensity lower than a predetermined value in the upper right area and the number of pixels having a light intensity equal to or higher than the predetermined value in an area other than the upper right area with respect to the pixel as a reference, extracts one or more pixels that satisfy a second condition as a second candidate point group based on a first score, and among the pixels included in the second candidate point group, determines a pixel having the maximum integrated score based on a first score, an integrated value of the light intensity of the pixels in the upper right area, an integrated value of the light intensity of the pixels in the lower area with respect to the pixel as a reference, and a third score indicating the levelness as an elbow point.

[0023] (Configuration 10) In Configuration 9, the first matrix may have elements in the upper right side from the matrix center being zero. The second matrix may have elements other than the upper right side from the matrix center being zero. The first condition may include that the first integrated value is equal to or greater than a first threshold value and the second integrated value is less than the first threshold value.

[0024] (Configuration 11) In Configuration 9 or 10, the first score may be the sum of the number of pixels with a luminance lower than a predetermined value in the area upper-right of each pixel with respect to that pixel, and the number of pixels with a luminance greater than or equal to the predetermined value in the area other than the upper-right of each pixel with respect to that pixel. The second score may be the sum of the difference between the integrated value of the luminance of the pixels in the area lower-right of each pixel with respect to that pixel and the integrated value of the luminance of the pixels in the area upper-right of each pixel with respect to that pixel, and the difference between the integrated value of the luminance of the pixels in the area lower-left of each pixel with respect to that pixel and the integrated value of the luminance of the pixels in the area upper-right of each pixel with respect to that pixel.

[0025] (Configuration 12) In any of Configurations 9 to 11, the third score may be calculated based on the difference in luminance at both ends equidistant in the horizontal direction with respect to each pixel.

[0026] (Configuration 13) A measurement method according to still another aspect of the present invention includes a step of imaging an image projected from the headlight of a vehicle onto a screen with an RGB camera having a correction filter disposed in the front stage, and a step of calculating the luminance of the headlight based on the green output of the RGB camera. The correction filter has a transmittance characteristic determined based on the transmittance characteristic of the green filter of the RGB camera and the relative luminous sensitivity.

[0027] (Configuration 14) A measurement method according to still another aspect of the present invention includes a step of imaging an image projected from the headlight of a vehicle onto a screen with a camera having a narrow-band band-pass filter centered at 440 nm disposed in the front stage to obtain a first measurement image, a step of imaging an image projected from the headlight of a vehicle onto a screen with a camera having a relative luminous sensitivity filter reflecting the relative luminous sensitivity disposed in the front stage to obtain a second measurement image, and a step of discriminating the type of the light source of the headlight based on the first measurement image and the second measurement image.

[0028] (Configuration 15) A measurement method according to still another aspect of the present invention includes a step of capturing an image of an image projected from a headlight of a vehicle onto a screen by a camera to obtain a measurement image, and sequentially setting an area of a predetermined size for the measurement image, and for each area, based on a first integrated value and a second integrated value obtained by multiplying a first matrix and a second matrix, respectively, a step of extracting pixels representing an area that satisfies a first condition as a first candidate point group, and for each pixel included in the first candidate point group, the number of pixels having a light intensity lower than a predetermined value in the upper right area with respect to the pixel, and the number of pixels having a light intensity lower than a predetermined value in the upper right area and the number of pixels having a light intensity equal to or higher than the predetermined value in an area other than the upper right area with respect to the pixel, a step of extracting one or more pixels that satisfy a second condition as a second candidate point group based on a first score, and among the pixels included in the second candidate point group, a second score based on the first score, the integrated value of the light intensity of the pixels in the upper right area, and the integrated value of the light intensity of the pixels in the lower area with respect to the pixel, and a step of determining a pixel having the maximum sum of the second score and a third score indicating the levelness as an elbow point.

[0029] (Configuration 16) A measurement program according to still another aspect of the present invention causes a computer to execute the measurement method according to any one of the above-described Configurations 13 to 15.

Advantages of the Invention

[0030] According to an embodiment of the present invention, a mechanism capable of testing various types of headlights can be provided.

Brief Description of the Drawings

[0031]

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Mode for Carrying Out the Invention

[0032] Embodiments of the present invention will be described in detail with reference to the drawings. In the drawings, the same or corresponding parts are denoted by the same reference numerals and their description will not be repeated.

[0033] <A.装置構成例> An example of an apparatus configuration for realizing the optical measurement method according to the present embodiment will be described.

[0034] FIG. 1 is a schematic diagram showing an example of the arrangement of a headlamp tester 1 according to this embodiment. Referring to FIG. 1, the headlamp tester 1 is associated with, for example, a headlamp S of a vehicle VH to be tested. Therefore, two headlamp testers 1 may be arranged as a set. Note that a common processing device may control the two headlamp testers 1.

[0035] Each headlamp tester 1 includes a lens unit 10, a column 4 that supports the lens unit 10 so that it can move up and down, and a base 6 that supports the column 4 so that it can move horizontally.

[0036] Lens unit 10 receives light emitted by headlight S and measures the light distribution characteristics of headlight S. Lens unit 10 is positioned directly opposite headlight S under test by pillar portion 4 and base portion 6. Typically, lens unit 10 is positioned 1 m forward of headlight S of test vehicle VH. However, the image projected onto screen 13 (see FIG. 2) located inside lens unit 10 (screen projected image) is a similar image equivalent to an image projected 10 m forward. Therefore, lens unit 10 can capture the light distribution characteristics of headlight S 10 m forward.

[0037] The headlamp tester 1 may be capable of performing various other inspections and aiming in addition to measuring the luminous intensity and light distribution characteristics of the headlamp S. The headlamp tester 1 may be capable of testing both passing headlamps (low beam) and driving headlamps (high beam).

[0038] 2 is a schematic diagram showing an example configuration of lens unit 10 of headlamp tester 1 according to the present embodiment. Referring to FIG. 2, lens unit 10 includes detection module 50, facing confirmation camera 11, Fresnel lens 12, screen 13, and facing adjustment laser 14.

[0039] The front-facing confirmation camera 11 is disposed on the upper part of the lens unit 10. The front-facing confirmation camera 11 captures an image (hereinafter, also referred to as a "lamp image") generated by the headlamp S of the vehicle VH irradiating light. The image captured by the front-facing confirmation camera 11 may be displayed on the display unit 30 (FIG. 3). The front-facing confirmation camera 11 is used in both the case of adjusting the alignment of the vehicle VH and the lens unit 10 (hereinafter, also referred to as "vehicle alignment") and the case of adjusting the alignment of the headlamp S and the lens unit 10 (hereinafter, also referred to as "lamp alignment").

[0040] The Fresnel lens 12 is disposed at the light-receiving port of the lens unit 10. The Fresnel lens 12 is a condenser lens for condensing the light irradiated from the headlamp S. The screen 13 is disposed on the optical axis of the Fresnel lens 12. The light from the headlamp S of the vehicle VH is projected onto the screen 13 after being condensed by the Fresnel lens 12.

[0041] The detection module 50 includes a camera (a monochrome camera and / or a color camera (for example, an RGB camera), which will be described later). The camera captures the image projected on the screen 13. The image obtained by imaging with the camera (hereinafter, also referred to as a "measurement image") includes information on the light distribution characteristics and luminous intensity of the headlamp S.

[0042] As will be described later, the detection module 50 includes a mechanism for disposing various filters in front of the camera. Since the detection module 50 has mechanisms other than the camera and the housing is enlarged, it is preferably disposed on the upper part of the lens unit 10 instead of the bottom of the lens unit 10.

[0043] The alignment adjustment laser 14 is a line laser that irradiates a reference line for positioning the vehicle VH. When adjusting the alignment of the vehicle VH and the lens unit 10 (vehicle alignment), the alignment adjustment laser 14 irradiates the vehicle VH with the reference line, and when adjusting the alignment of the headlamp S and the lens unit 10 (lamp alignment), the alignment adjustment laser 14 irradiates the headlamp S with the reference line.

[0044] FIG. 3 is a schematic diagram showing an electrical configuration example of the headlamp tester 1 according to the present embodiment. Referring to FIG. 3, the headlamp tester 1 includes a processing device 100 electrically connected to the lens unit 10.

[0045] The processing device 100 is, for example, a general-purpose computer and includes one or more processors 102, a memory 104, and a storage 106.

[0046] The processor 102 reads and executes one or more programs stored in the storage 106 into the memory 104. The processor 102 is composed of, for example, a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), or the like. The processor 102 may include a hard-wired logic circuit such as an FPGA (Field-Programmable Gate Array) or an ASIC (Application Specific Integrated Circuit).

[0047] The memory 104 functions as a working memory for the processor 102 to execute programs. The memory 104 is composed of, for example, a DRAM (Dynamic Random Access Memory), an SRAM (Static Random Access Memory), or the like.

[0048] The storage 106 stores programs (computer-readable instructions) executed by the processor 102 and data necessary for processing. The storage 106 is composed of, for example, a non-transitory computer-readable medium such as a hard disk or a flash memory. The storage 106 stores, for example, a system program 108 and a measurement program 110. The system program 108 includes computer-readable instructions such as an operating system. The measurement program 110 includes computer-readable instructions for realizing measurement processing (including image processing) described later.

[0049] An operation unit 20, a display unit 30, and a driving device 40 are connected to the processing device 100. The processing device 100 may include an IO (Input Output) circuit and a relay circuit as an interface.

[0050] The operation unit 20 receives user operations. In addition to a keyboard, a mouse, etc., the operation unit 20 may include physical buttons and levers. At least a part of the operation unit 20 may be disposed in a box attached to the column portion 4. The processing device 100 starts measurement processing according to the user operation received by the operation unit 20. Further, the processing device 100 gives a command to the driving device 40 according to the user operation received by the operation unit 20.

[0051] The display unit 30 displays the processing result by the processing device 100 and the captured image. The display unit 30 is, for example, a liquid crystal display.

[0052] The display unit 30 may display information necessary as the headlamp tester 1, such as the measured value of the luminous intensity, the measured value of the irradiation direction, the measurement result, the pass / fail of the test, the current test mode, the setting of the tester, etc. The display unit 30 may display an image for visually observing the vehicle VH when the vehicle is facing forward, the headlamp S when the lamp is facing forward, the light distribution characteristics of the headlamp S, etc. The display unit 30 may display a user interface screen for the user to make adjustments.

[0053] The driving device 40 includes an actuator such as a motor and is disposed inside the column portion 4 or the like. The driving device 40 operates according to a command from the operation unit 20 to change the position of the lens unit 10 in the vertical direction. In this case, the driving device 40 may include a lifting motor for lifting the lens unit 10. The driving device 40 operates according to a command from the operation unit 20 to change the positions of the column portion 4 and the lens unit 10 in the width direction of the vehicle VH. In this case, the driving device 40 may include a moving motor for horizontally moving the lens unit 10.

[0054] The processing device 100 performs image processing as described later using the measurement image obtained by the camera of the detection module 50, and causes the display unit 30 to display the processing result (including the measurement result). The user grasps the measurement result by referring to the display unit 30.

[0055] A printer for printing out the processing result (including the measurement result) may be connected to the processing device 100. The processing device 100 may output a report including the processing result on an arbitrary medium.

[0056] <B. Light distribution characteristics of the headlamp> Next, the light distribution characteristics of the headlamp S will be described.

[0057] In the test of the headlamp S of the vehicle VH, measurement is performed based on an image (hereinafter also referred to as a "screen projection image") generated by the headlamp S projecting onto a screen.

[0058] FIG. 4 is a diagram showing an example of a measurement image captured by the camera of the detection module 50 of the headlamp tester 1 according to the present embodiment. The measurement image shown in FIG. 4 shows an example of the light distribution characteristics of the oncoming vehicle headlamp. In FIG. 4, the X direction and the Y direction correspond to the imaging surface of the detection module 50, and the Z direction corresponds to the pixel value of each pixel.

[0059] Referring to FIG. 4, for example, the screen projection image of the oncoming vehicle headlamp of a vehicle driving on the left side has a horizontal bright-dark boundary line (hereinafter also referred to as a "horizontal cut-off") on the right side and a bright-dark boundary line rising upward to the left at a predetermined angle (hereinafter also referred to as a "diagonal cut-off") on the left side. The intersection of the horizontal cut-off and the diagonal cut-off is called the "elbow point".

[0060] In this specification, "cut-off" means the boundary between the bright part (the part with relatively high luminous intensity) and the dark part (the part with relatively low luminous intensity) of the measurement image. In an image that is a set of pixels, "cut-off" may be a group of bright-dark boundary points. A part of the cut-off of the measurement image may be determined as a "horizontal cut-off" or a "diagonal cut-off".

[0061] In the inspection and adjustment of the optical axis of the headlight S of the vehicle VH, the elbow point must be adjusted so that, in the vertical direction, it is located slightly below (within 0.57 degrees) the horizontal line on the left side of the screen projection image, and in the left-right direction, it coincides with the traveling direction of the vehicle. Therefore, it is necessary to detect the elbow point in the light distribution characteristics of the headlight S.

[0062] In recent years, passing headlights with a light distribution characteristic in which a part of the cut-off is blurred have been put into practical use so as to prevent glare to oncoming vehicles even when the vehicle moves significantly up and down. In the measurement image of such a passing headlight, as shown in FIG. 4, a part of the horizontal cut-off shows a curved shape (for example, the concave portion shown in FIG. 4) instead of a straight line. In some cases, the concave portion of the measurement image may be erroneously detected as the elbow point. Also, the elbow point determined by calculation including unclear portions may be significantly different from the elbow point judged visually.

[0063] <C. Luminance measurement> Next, a method of luminance measurement in the headlight tester 1 according to the present embodiment will be described.

[0064] The amount of light energy passing through a certain surface per unit time is the radiant flux (W). When the radiant flux is P(λ), the luminous flux φ (lm), which is the brightness felt by the human eye for the radiant flux P, is expressed as in Equation (1).

[0065]

Equation

[0066] Here, V(λ) is the relative luminous efficiency, and K m is the maximum luminous efficiency (683 lm / W).

[0067] Also, the luminous intensity I v (cd) is the differential luminous flux dφ per differential solid angle dω, so the relationship as in Equation (2) holds.

[0068]

Number

[0069] In order to measure the luminous intensity, it is necessary to reflect the relative luminous sensitivity that represents the intensity felt by the human eye for each wavelength of light.

[0070] FIG. 5 is a graph showing an example of the transmittance characteristics of a relative luminous sensitivity filter. The relative luminous sensitivity filter has transmittance characteristics corresponding to the relative luminous sensitivity. In order to realize the measurement of luminous intensity reflecting the relative luminous sensitivity, a configuration in which a relative luminous sensitivity filter having transmittance characteristics as shown in FIG. 5 is arranged in front of a monochrome camera is generally adopted.

[0071] On the other hand, the light sources of headlamps are diversified, and there is an increasing need to record a color image of the irradiation image of the headlamp S using a color camera and to measure the luminous intensity using the same color camera.

[0072] In order to measure the luminous intensity using an RGB camera as a typical color camera, calculations for reflecting the relative luminous sensitivity are required. Specifically, the color temperature for each headlamp light source is determined from the relationship between the standard light source defined by the CIE (International Commission on Illumination) and the NTSC RGB color space, the correction coefficients for each of RGB at the determined color temperature are determined, and based on the determined correction coefficients, the luminous intensity can be calculated by performing a calculation similar to formula (1) on the RGB output of the color camera. However, the luminous intensity calculated by the above procedure has a large uncertainty.

[0073] In the headlamp tester 1 according to the present embodiment, the luminous intensity is measured using the green output of the RGB camera (hereinafter also abbreviated as "G output"). This is based on a new finding that the transmittance characteristics of the green filter corresponding to the G output of the RGB camera are close to the transmittance characteristics of the relative luminous sensitivity filter (see FIG. 5).

[0074] The green filter of an RGB camera refers to the green part among the color filters arranged in front of, for example, a CCD (Charge Coupled Device) or CMOS (Complementary Metal Oxide Semiconductor) image sensor. Therefore, the G output means the component corresponding to the light passing through the green part of the color filter among the signals (RGB output) output from the camera. When three independent CCDs or CMOS image sensors are arranged for each color, the output from the CCD or CMOS image sensor responsible for green becomes the G output.

[0075] FIG. 6 is a graph showing an example of the filter characteristics of an RGB camera. In FIG. 6, the transmittance characteristics of each RGB filter are shown. The G output indicates the intensity of the light after passing through the green filter (G in FIG. 6) of the RGB camera. To calculate the luminous intensity from the G output, a green correction filter (corresponding to the "correction filter" according to the present invention) is introduced.

[0076] The transmittance characteristic V of the green correction filter g (λ) can be defined as in Equation (3) using the transmittance characteristic G(λ) of the green filter and the relative spectral sensitivity V(λ).

[0077]

Equation

[0078] The green correction filter has a transmittance characteristic V g (λ) determined based on the transmittance characteristic V g (λ) of the green filter of the RGB camera and the relative spectral sensitivity V(λ). More specifically, as shown in Equation (3), the transmittance characteristic V g (λ) of the green correction filter is the result of dividing the relative spectral sensitivity V(λ) by the transmittance characteristic G(λ) of the green filter.

[0079] FIG. 7 is a graph showing an example of the transmittance characteristics of the green correction filter. In FIG. 7, the transmittance characteristic V g (λ) of the green correction filter calculated according to equation (3) is shown.

[0080] As is clear from the above equation (3), by arranging a green correction filter having the transmittance characteristic V g (λ) in front of the RGB camera, the G output of the RGB camera coincides with the specific luminous efficiency V(λ). That is, the luminous intensity can be more accurately obtained from the G output of the RGB camera.

[0081] Thus, the processing device 100 of the headlamp tester 1 calculates the luminous intensity of the headlamp S based on the G output of the RGB camera when an image projected from the headlamp S of the vehicle VH onto the screen 13 is captured by the RGB camera with the green correction filter in the front stage.

[0082] By arranging the green correction filter in front of the RGB camera, the red output (hereinafter also abbreviated as "R output") and the blue output (hereinafter also abbreviated as "B output") are also affected, so the color image can also change from the original color. However, since the image acquired by the RGB camera contains qualitative information, it is also possible to reproduce the original color by post-image processing. Alternatively, as will be described later, the green correction filter may be arranged in front of the RGB camera only when measuring the luminous intensity.

[0083] The green correction filter may be configured, for example, by stacking a plurality of simple Gaussian notch filters.

[0084] FIG. 8 is a graph showing an example of the transmittance characteristics of a simple Gaussian notch filter. FIG. 8 shows the transmittance characteristics of six types of notch filters.

[0085] FIG. 9 is a graph showing an example of the transmittance characteristics obtained by superimposing the six types of notch filters shown in FIG. 8. Referring to FIG. 9, it can be seen that the transmittance characteristics (dashed line in FIG. 9) obtained by superimposing the six types of notch filters approximate very well the ideal transmittance characteristics (solid line in FIG. 9) of the green correction filter.

[0086] FIG. 10 is a graph showing an example of the visual sensitivity obtained using a green correction filter composed of superimposing six types of notch filters. Referring to FIG. 10, by using the green correction filter (dashed line in FIG. 10) composed of superimposing six types of notch filters, characteristics close to the specific visual sensitivity (solid line in FIG. 10) can be realized.

[0087] <Measurement Method for D. Pulse Point Light Source> Next, an example of a measurement method for the headlight S composed of a pulse point light source will be described.

[0088] Light sources such as HID (High Intensity Discharge) lamps and LEDs (Light Emitting Diodes) are pulse-driven. When imaging such a light source with a camera, flicker etc. occurs and the measured values of the luminous intensity vary.

[0089] In order to prevent such variations in the measured values, methods have been proposed to obtain the period (driving period) during which the light source is pulse-driven by some method and synchronize the imaging timing of the camera with the obtained period. Also, a method of editing a plurality of images in which flicker is observed into images without flicker after measurement has been proposed. However, both methods have the problem of being costly and time-consuming.

[0090] The main cause of the variation in the measured values is that the exposure time of the camera cannot be made long with respect to the period during which the light source is pulse-driven.

[0091] FIG. 11 is a diagram for explaining the measurement of a pulse-driven light source. Referring to FIG. 11(A), when a light source such as an HID lamp or an LED is pulse-driven, a large amount of light can be obtained in a very short time, so it feels bright to the human eye with a small amount of electric power. However, when viewed from the light-receiving element of the camera, the saturation voltage is reached in a short exposure time. The frame rate of the camera can be made somewhat long, but the exposure time cannot be made long. Since the exposure time is short, the number of times the light source is lit (the number of pulses) within the exposure time is relatively small, and the measured number of lighting times is likely to vary from measurement to measurement.

[0092] In the headlight tester 1 according to the present embodiment, when measuring a light source with a large amount of light, it is dimmed using a dimming filter or the like. As the dimming filter, one whose dimming amount is calibrated using a standard light source or the like is used.

[0093] FIG. 11(B) shows a measurement example using a dimming filter. By using a dimming filter, the amount of light input to the light-receiving element of the camera is reduced, so the exposure time can be made long. For example, the exposure time (charge accumulation time) in FIG. 11(A) is for 4 pulses, whereas the exposure time (charge accumulation time) in FIG. 11(B) is for 15 pulses.

[0094] By using a dimming filter, the luminous intensity can be accurately obtained without the need for a mechanism for synchronizing the imaging timing of the camera and a mechanism for post-editing. Further, by dimming, the dynamic range of the camera can be efficiently utilized, so the measurement accuracy can also be improved.

[0095] <E. Narrow-band measurement> Next, the narrow-band measurement using a band-pass filter will be described.

[0096] When a high-brightness LED is adopted as a headlight light source, if a material with a high refractive index is transmitted to achieve the target light distribution characteristics, wavelength dispersion occurs, and "color deviation" may occur in the irradiation image of the headlight S. Due to the color deviation, the position of the cut-off (horizontal cut-off and / or diagonal cut-off) may be dispersed between red and blue. That is, due to wavelength dispersion, the phenomenon that the cut-off bleeds into multiple colors occurs, and it seems as if there are multiple cut-offs. When the irradiation image is viewed with the human eye, it may be ambiguous which position is determined as the cut-off. Also, when the irradiation image captured by the camera is expressed in grayscale, the cut-off may be blurred.

[0097] FIG. 12 is a graph showing an example of the spectral spectrum of light irradiated by a headlight S using an LED as a light source. Referring to FIG. 12, the spectral spectrum of the headlight S using an LED as a light source includes a peak near 540 nm in addition to a peak near 440 nm which is the excitation wavelength of the blue LED.

[0098] FIG. 13 is a graph showing an example of the transmittance characteristics of the band-pass filter of the headlight tester 1 according to the present embodiment. Referring to FIG. 13, the band-pass filter is a narrow-band band-pass filter that transmits only near 440 nm which is the excitation wavelength of the blue LED. The band-pass filter may be, for example, a narrow-band filter having 440 nm as the center wavelength. Note that the center wavelength of the band-pass filter may deviate slightly from 440 nm. Therefore, the center wavelength of the band-pass filter may be substantially 440 nm.

[0099] Thus, in narrow-band measurement, the measurement image captured when the band-pass filter is arranged in front of the camera is used.

[0100] FIG. 14 is a diagram showing an example of the effect by narrow-band measurement of the headlamp tester 1 according to the present embodiment. FIG. 14(A) shows a grayscale image of the headlamp S using an LED as a light source, which is captured without arranging a band-pass filter (normal measurement). FIG. 14(B) shows a grayscale image of the headlamp S using an LED as a light source, which is captured with a band-pass filter arranged in front of the camera (narrow-band measurement).

[0101] FIG. 15 is a graph showing the profiles in the Y direction for the two images shown in FIG. 14. FIG. 15 shows the profiles in the Y direction near X = 700 of the two images.

[0102] Referring to FIGS. 14 and 15, it can be seen that the cut-off becomes clearer by narrow-band measurement using a band-pass filter. That is, the position of the cut-off can be obtained more accurately by narrow-band measurement.

[0103] <F. Discrimination of the type of light source> Next, an example of the process for discriminating the type of the light source of the headlamp S will be described.

[0104] In the headlamp tester 1 according to the present embodiment, a discrimination value D L reflecting the specific visibility is used to discriminate the type of the light source. More specifically, assuming that the spectral spectrum of the light source to be discriminated is L(λ), the transmittance characteristic of the specific visibility filter is V(λ), and the transmittance spectrum of the narrow-band band-pass filter described above is N(λ), the discrimination value D L is defined as in equation (4).

[0105]

Equation

[0106] In equation (4), the first term represents a value obtained by normalizing the component of the spectral spectrum L(λ) of the light source that passes through the band-pass filter with the transmittance characteristic of the band-pass filter, and the second term represents a value obtained by normalizing the component of the spectral spectrum L(λ) of the light source that passes through the relative spectral sensitivity filter with the transmittance characteristic of the relative spectral sensitivity filter.

[0107] Regarding the second term of equation (4), instead of the transmittance characteristic V(λ) of the relative spectral sensitivity filter, the G output of the RGB camera when a green correction filter (transmittance characteristic V g (λ)) is arranged in front of the RGB camera may be used.

[0108] The numerator of the first term of equation (4) is calculated based on the measurement image (output of the camera or sensor) captured when the band-pass filter is arranged in front of the camera, and the numerator of the second term is calculated based on the measurement image (output of the camera or sensor) captured when a filter reflecting the relative spectral sensitivity (relative spectral sensitivity filter or green correction filter) is arranged in front of the camera.

[0109] The denominator of each term of equation (4) is calculated based on the transmittance data of the band-pass filter and the relative spectral sensitivity filter (or green correction filter). For example, the denominators of the first and second terms of equation (4) can be calculated mathematically by integrating the transmittance spectrum N(λ) and the transmittance characteristic V(λ) of the relative spectral sensitivity filter (or the transmittance characteristic V g (λ)) with respect to the wavelength.

[0110] That is, the value obtained by dividing the integrated value of the pixel values (luminance) included in the measurement image captured when the band-pass filter is arranged in front of the camera by the wavelength integrated value of the transmittance characteristic of the band-pass filter corresponds to the first term of equation (4). Also, the value obtained by dividing the integrated value of the pixel values (luminance) included in the measurement image captured when the relative spectral sensitivity filter (or green correction filter) is arranged in front of the camera by the wavelength integrated value of the transmittance characteristic of the relative spectral sensitivity filter (or green correction filter) corresponds to the second term of equation (4). The discrimination value D Lis based on the difference between the two.

[0111] (4) The discrimination value D calculated according to the formula L becomes a value corresponding to the difference between the component passing through the band-pass filter and the component passing through the specific sensitivity filter.

[0112] FIG. 16 shows the discrimination value D for each type of light source L is a graph showing an example of the range that can be taken.

[0113] Referring to FIG. 16, the value of the discrimination value D L shows clearly different values for LED, HID lamp, and halogen lamp. Therefore, by setting appropriate one or more threshold values, the type of the light source of the headlamp S can be discriminated. Thus, the processing device 100 of the headlamp tester 1 may discriminate whether the light source of the headlamp S is an HID lamp, an LED, or a halogen lamp based on the discrimination value D L .

[0114] In addition to the band-pass filter, the discrimination value D may be calculated using a measurement image captured with a dimming filter disposed in front of the camera and a measurement image captured with a dimming filter disposed in addition to the specific sensitivity filter (or green correction filter). L is calculated.

[0115] In a conventional headlamp tester, correction coefficients for each of RGB are required to calculate the luminous intensity from the RGB output of a color camera. To determine the correction coefficients for each of RGB, the type of the light source of the headlamp S is required. This is because the correction coefficients for each of RGB must be determined according to the spectral spectrum of the light source and / or the color temperature of the light source.

[0116] When using a monochrome camera with a ratio sensitivity filter placed in the front stage, the luminous intensity can be accurately obtained regardless of the type of light source. Also, when using a color camera, by introducing the above-mentioned green correction filter, the luminous intensity can be accurately obtained regardless of the type of light source. Therefore, in order to measure the luminous intensity, it is not necessary to discriminate the type of light source. However, in the final confirmation by vehicle manufacturers, etc., and / or in inspection sites, etc., there is a need to confirm whether the headlamp S assembled in the vehicle is the intended light source.

[0117] <Detection process of the elbow point> Next, an example of the detection process of the elbow point will be described.

[0118] Even if the position of the cut-off (horizontal cut-off and / or diagonal cut-off) is clear, depending on the shape and structure of the headlamp S, the light distribution characteristics of the headlamp S are diverse, so it is difficult to detect the elbow point based on predetermined conditions (detection program).

[0119] Also, conventionally, it was important to cope with changes in the length and angle of the diagonal cut-off in the detection of the elbow point, but light distribution characteristics showing characteristic horizontal cut-offs have come to be seen. More specifically, many of the conventional horizontal cut-offs showed a uniform straight line. However, for example, in the light distribution characteristics of a headlamp S using an LED as a light source, there may be a recess in the horizontal part (3.5R position) of the horizontal cut-off.

[0120] FIG. 17 is a diagram showing an example of light distribution characteristics with a recess in the horizontal part of the horizontal cut-off. The reason why the light distribution characteristics as shown in FIG. 17(A) are adopted is to ensure that the upper limit value of the luminous intensity (13,200 cd) at the measurement point 50R (3.43R - 0.87D), which is defined as the luminous intensity measurement point during the component certification of the headlamp S, is not exceeded. That is, because the high brightness of the LED is remarkable, it is designed so as not to exceed the upper limit value of the luminous intensity by intentionally providing a recess to reduce the luminous intensity.

[0121] Regarding the light distribution characteristics as shown in Fig. 17(A), in the conventional elbow point detection process, due to the influence of the recess, there is a possibility of misdetecting points other than the correct elbow point as the elbow point.

[0122] Also, as shown in Fig. 17(B), there are light distribution characteristics in which the recess is slightly darker. Even in such light distribution characteristics, an algorithm capable of appropriately detecting the elbow point is required.

[0123] The headlamp tester 1 according to the present embodiment adopts a method capable of correctly detecting the elbow point even for light distribution characteristics in which the correct elbow point cannot be detected by the method based on the intersection of the straight line indicated by the horizontal cut-off and the oblique cut-off.

[0124] Fig. 18 is a flowchart showing the processing procedure for detecting the elbow point in the headlamp tester 1 according to the present embodiment. Each step shown in Fig. 18 may be realized, for example, by one or a plurality of processors 102 of the processing device 100 executing the measurement program 110. It is assumed that the headlamp tester 1 has previously acquired a measurement image.

[0125] Referring to Fig. 18, the headlamp tester 1 performs simple extraction on the measurement image (step S1). Specifically, the headlamp tester 1 extracts a plurality of candidate points from the measurement image. Subsequently, the headlamp tester 1 narrows down the plurality of extracted candidate points (step S2). More specifically, the headlamp tester 1 extracts candidate points with a large brightness difference among the plurality of candidate points. Subsequently, the headlamp tester 1 detects the level (step S3). Then, the headlamp tester 1 determines the elbow point (step S4).

[0126] (g1: Simple extraction (step S1)) In simple extraction, two 7×7 matrices H shown in Equation (5) ij B , H ij D are used. Matrix H ij B , H ijD is a kind of spatial filter.

[0127]

Number

[0128] According to equation (6), for each pixel included in the measurement image, the photometric integration value L xy B , L xy D is calculated.

[0129]

Number

[0130] However, I x,y represents the photometric value at the pixel coordinates (x, y) of the measurement image.

[0131] As shown in equation (5), for the matrix H ij B the elements in the upper right side from the matrix center are zero. Also, for the matrix H ij D the elements other than those in the upper right side from the matrix center are zero.

[0132] Among the set of the calculated photometric integration values L xy B , L xy D for the threshold T1, the pixel coordinates representing the area satisfying equation (7) are determined as the candidate point group C1 that is simply extracted.

[0133]

Number

[0134] As shown in equation (7), the condition for simply extracting the area (pixel coordinates) is that the photometric integration value L xy B is greater than or equal to the threshold T1, and the photometric integration value Lxy D is less than the threshold value T1.

[0135] FIG. 19 is a diagram for explaining the processing content of the simple extraction of step S1 shown in FIG. 18. For each pixel (center point) of the measurement image, the photometric integration value L in the 7-pixel × 7-pixel area shown in FIG. 19 xy B , L xy D is calculated. The photometric integration value L xy B is calculated from the 15 pixels drawn with diagonal lines in the matrix shown in FIG. 19. The photometric integration value L xy D is calculated from the 6 black pixels in the matrix shown in FIG. 19.

[0136] When the photometric integration value L calculated in the 7-pixel × 7-pixel area centered on a certain pixel xy B , L xy D satisfies the condition of formula (7) (L xy B ≧ T1 and L xy D < T1), the pixel coordinates (x, y) at the center of the area are added to the candidate point group C1.

[0137] Thus, in the simple extraction (step S1), an area of a predetermined size (for example, 7 pixels × 7 pixels) is sequentially set for the measurement image. For each sequentially set area, the matrix H ij B (first matrix) and the matrix H ij D (second matrix) are multiplied respectively to obtain the photometric integration value L xy B (first integration value) and the photometric integration value L xy D (second integration value), and an area that satisfies the condition (first condition) shown in formula (7) is determined. The pixel representing the determined area is extracted as the candidate point group C1 (first candidate point group).

[0138] Figure 20 is a diagram showing an example of the processing result of the simple extraction of step S1 shown in FIG. 18. In the example shown in FIG. 20, six pixel coordinates are extracted as the candidate point group C1.

[0139] (g2: Narrowing down candidate points (step S2)) Next, for each candidate point (pixel coordinate) included in the candidate point group C1, a threshold score S1 and a photometric score S2 are calculated. With each pixel coordinate included in the candidate point group C1 as the origin (x = 0, y = 0), the integrated value of the light intensity and the number of pixels are calculated for each of the following four areas.

[0140] (1) 0 > x ≥ -75 and 0 ≤ y ≤ 75 The integrated value of the light intensity of each pixel is calculated as B1, and the number of pixels with a light intensity equal to or greater than the threshold value T1 is calculated as P1.

[0141] (2) 0 ≤ x ≤ 75 and 0 ≤ y ≤ 75 The integrated value of the light intensity of each pixel is calculated as B2, and the number of pixels with a light intensity less than the threshold value T1 is calculated as P2.

[0142] (3) 0 > x ≥ -75 and 0 > y ≥ -75 The integrated value of the light intensity of each pixel is calculated as B3, and the number of pixels with a light intensity equal to or greater than the threshold value T1 is calculated as P3.

[0143] (4) 0 < x ≤ 75 and 0 > y ≥ -75 The integrated value of the light intensity of each pixel is calculated as B4, and the number of pixels with a light intensity equal to or greater than the threshold value T1 is calculated as P4.

[0144] Using the integrated light intensity values B1 to B4 and the number of pixels P1 to P4, the threshold score S1 and the photometric score S2 are calculated as in equations (8-1) and (8-2).

[0145] Threshold score S1 = P1 + P2 + P3 + P4 ··· (8-1) Luminance score S2 = B3 + B4 - 2B2 ··· (8 - 2) Pixel coordinates that satisfy the conditions shown in equation (9) for the number of pixels P2 and the threshold score S1 with respect to thresholds T2 and T3 are determined as the candidate point group C2.

[0146] P2 ≥ T2 ∩ S1 ≥ T3 ··· (9) Figure 21 is a diagram for explaining the processing content of narrowing down candidate points in step S2 shown in Figure 18. Referring to Figure 21, the following calculations are performed for an area of 75 pixels each in the vertical, horizontal, upper, lower, left, and right directions centered on each candidate point (pixel coordinates) included in the candidate point group C1.

[0147] In the sub - area A of Figure 21 (0 > x ≥ - 75 and 0 ≤ y ≤ 75), the number of pixels with luminance greater than or equal to the threshold T1 is counted, and the number of pixels P1 is determined. In the sub - area B of Figure 21 (0 ≤ x ≤ 75 and 0 ≤ y ≤ 75), the number of pixels less than the threshold T1 is counted, and the number of pixels P2 is determined. In the sub - area C of Figure 21 (0 > x ≥ - 75 and 0 > y ≥ - 75), the number of pixels with luminance greater than or equal to the threshold T1 is counted, and the number of pixels P3 is determined. In the sub - area D of Figure 21 (0 < x ≤ 75 and 0 > y ≥ - 75), the number of pixels with luminance greater than or equal to the threshold T1 is counted, and the number of pixels P4 is determined.

[0148] The difference between the integrated luminance value in sub - area C of Figure 21 and the integrated luminance value in sub - area B, and the difference between the integrated luminance value in sub - area D of Figure 21 and the integrated luminance value in sub - area B are determined as the luminance score S2.

[0149] In this way, for each pixel included in the candidate point group C1, based on the number of pixels (pixel number P2) with a luminance lower than the threshold value T1 existing in the upper right area (sub-area B shown in FIG. 21) with respect to the pixel, and the number of pixels (pixel numbers P1, P3, P4) with a luminance equal to or higher than the threshold value T1 existing in the areas other than the upper right area (sub-areas A, C, D shown in FIG. 21) with respect to the pixel, a threshold score S1 is calculated. Also, based on the integrated value B2 of the luminances of the pixels existing in the upper right area (sub-area B shown in FIG. 21) with respect to the pixel, and the integrated values B3, B4 of the luminances of the pixels existing in the lower area (sub-areas C, D shown in FIG. 21) with respect to the pixel, a luminance score S2 is calculated. Then, one or more pixels for which the pixel number P2 and the threshold score S1 satisfy the conditions are extracted as the candidate point group C2.

[0150] More specifically, the threshold score S1 is the sum of the pixel number P2 and the pixel numbers P1, P3, P4 for each pixel included in the candidate point group C1. The luminance score S2 is the sum of the difference between the integrated value B4 of the luminances of the pixels existing in the lower right area (sub-area D shown in FIG. 21) with respect to the pixel and the integrated value B2 of the luminances of the pixels existing in the upper right area (sub-area B shown in FIG. 21) with respect to the pixel, and the difference between the integrated value B3 of the luminances of the pixels existing in the lower left area (sub-area C shown in FIG. 21) with respect to the pixel and the integrated value B2 of the luminances of the pixels existing in the upper right area (sub-area B shown in FIG. 21) with respect to the pixel for each pixel included in the candidate point group C1.

[0151] FIG. 22 is a diagram showing an example of the processing result of narrowing down the candidate points in step S2 shown in FIG. 18. In the example shown in FIG. 22, three pixel coordinates are extracted as the candidate point group C2.

[0152] (g3: Detection of horizontal degree (step S3) and determination of elbow point (step S4)) Next, a level score S3 indicating the levelness is calculated. More specifically, with each pixel coordinate included in the candidate point group C2 as the origin (x = 0, y = 0), the level score S3 is calculated according to Equation (10).

[0153]

Equation

[0154] Here, I x,y represents the light intensity at the coordinate (x, y) with each pixel coordinate included in the candidate point group C2 as the origin. α is a positive coefficient. Equation (10) scores the levelness in the x - direction from the pixel coordinates included in the candidate point group C2. The level score S3 indicates a value closer to zero as the levelness is more horizontal.

[0155] FIG. 23 is a diagram for explaining the processing details of the levelness detection in step S3 shown in FIG. 18. For each pixel coordinate included in the candidate point group C2, in the area of 150 pixels × 10 pixels shown in FIG. 23, a level score S3 indicating the levelness of the light distribution characteristic is obtained. That is, the level score S3 corresponds to the difference between the integrated light intensity value of the sub - area G and the integrated light intensity value of the sub - area H. The level score S3 indicates a larger value as the difference is smaller.

[0156] In this way, the level score S3 is calculated for each pixel based on the difference in light intensity at both ends equidistant in the horizontal direction with respect to the pixel as the reference.

[0157] Finally, among the pixel coordinates included in the candidate point group C2, the pixel coordinate at which the integrated score S all is maximized based on the threshold score S1, the light intensity score S2, and the level score S3 is determined as the elbow point.

[0158] The integrated score all is calculated, for example, according to Equation (11).

[0159] S all=a1×S1 + a2×S2 + a3×S3···(11) The coefficients a1, a2, and a3 can be arbitrarily determined. For example, if a1 = a2 = a3 = 1, the integrated score all means the sum of the threshold score S1, the photometric score S2, and the flatness score S3. Alternatively, the coefficients a1, a2, and a3 may be determined according to the elements (threshold, photometric, flatness) that are emphasized to determine the elbow point.

[0160] FIG. 24 is a diagram showing an example of the detection result of the elbow point by steps S3 and S4 shown in FIG. 18. In the example shown in FIG. 24, one of the three pixel coordinates extracted as the candidate point group C2 is determined as the elbow point.

[0161] (g4: effect) According to the above-described process for detecting the elbow point, when measuring the light distribution characteristics in which a concave portion exists, the concave portion can be excluded from the candidate point group of the elbow point, and the elbow point can be correctly detected.

[0162] For example, regarding the light distribution characteristics shown in FIGS. 17(A) and 17(B), since the threshold score S1 and / or the photometric score S2 is low, the pixel coordinates of the concave portion are not extracted as the candidate point group C2.

[0163] FIG. 25 is a diagram showing an example of the detection result of the elbow point for the light distribution characteristics shown in FIG. 17. FIG. 25(A) shows an example of the detection result for the light distribution characteristics shown in FIG. 17(A), and FIG. 25(B) shows an example of the detection result for the light distribution characteristics shown in FIG. 17(B).

[0164] In the light distribution characteristics shown in FIG. 25(A), since the number of pixels above the threshold T1 in the sub-area B (see FIG. 21) is large, the number of pixels P2 is small, and the threshold score S1 is low. Also, in the light distribution characteristics shown in FIG. 25(B), in addition to the threshold score S1, the photometric score S2 is also low.

[0165] Thus, for any light distribution characteristic, the score as a candidate point remains low and is excluded from the candidate point group C2. As a result, the pixel coordinates of the concave portion are not detected as the elbow point.

[0166] <H. Detection Module 50 and Measurement Processing Example> Next, a configuration example and a measurement processing example of the detection module 50 of the headlight tester 1 according to the present embodiment will be described.

[0167] (h1: Monochrome Camera + Color Filter Wheel + Neutral Density Filter Wheel) FIG. 26 is a schematic diagram showing a configuration example of the detection module 50 of the headlight tester 1 according to the present embodiment. Referring to FIG. 26, the detection module 50 includes a monochrome camera 51, a motor 53, a color filter wheel 54, a motor 55, and a neutral density filter wheel 56.

[0168] The monochrome camera 51 includes a lens onto which the screen projection image is incident. The motor 53 is driven by the drive device 40 to rotate the color filter wheel 54. The motor 55 is driven by the drive device 40 to rotate the neutral density filter wheel 56. The motors 53 and 55 may be stepping motors.

[0169] The drive device 40 can also detect the origins of the motor 53 (color filter wheel 54) and the motor 55 (neutral density filter wheel 56).

[0170] The processing device 100 gives commands to the drive device 40 to rotate the motor 53 (color filter wheel 54) and the motor 55 (neutral density filter wheel 56), and gives an imaging command to the monochrome camera 51. The processing device 100 processes the output of the monochrome camera 51. More specifically, the processing device 100 acquires a measurement image captured by the monochrome camera 51.

[0171] The color filter wheel 54 has a plurality of holes at a predetermined distance from the rotation axis RX1. Similarly, the neutral density filter wheel 56 has a plurality of holes at a predetermined distance from the rotation axis RX2. The centers of the holes of the color filter wheel 54 and the neutral density filter wheel 56 are configured to coincide with the optical axis AX of the monochrome camera 51. By adopting such a configuration, any one of the holes of the color filter wheel 54 and any one of the holes of the neutral density filter wheel 56 can be arranged in front of the monochrome camera 51.

[0172] That is, when testing (measuring) the headlight S, the color filter wheel 54 and / or the neutral density filter wheel 56 is rotated to arrange the necessary filter in front of the monochrome camera 51.

[0173] For example, a band-pass filter 541, a blue filter 542, a green filter 543, a red filter 544, and a relative spectral sensitivity filter 545 may be respectively attached to the plurality of holes of the color filter wheel 54.

[0174] Instead of the blue filter 542, the green filter 543, and the red filter 544, an X filter, a Y filter, and a Z filter corresponding to the XYZ colorimetric system may be adopted.

[0175] The band-pass filter 541 may use, for example, a narrow-band filter with a center wavelength of 440 nm and a half-value width of 20 nm.

[0176] A plurality of neutral density filters 561, 562, 563, 564, 565 with different light attenuation amounts may be respectively attached to the plurality of holes of the neutral density filter wheel 56.

[0177] By using the configuration example shown in FIG. 26, the following measurements are possible.

[0178] (1) Rotate the color filter wheel 54 to place the relative sensitivity filter 545 in front of the monochrome camera 51 and measure the luminous intensity. Note that the neutral density filter wheel 56 may be rotated to place an appropriate neutral density filter.

[0179] (2) Rotate the color filter wheel 54 to place the band-pass filter 541 in front of the monochrome camera 51 and measure the light distribution characteristics (cut-off and elbow points). Note that the neutral density filter wheel 56 may be rotated to place an appropriate neutral density filter.

[0180] (3) Sequentially rotate the color filter wheel 54 to place the blue filter 542, green filter 543, and red filter 544 in front of the monochrome camera 51 respectively, capture three images, and synthesize a color image of the irradiation image from the three captured images. Note that the neutral density filter wheel 56 may be rotated to place an appropriate neutral density filter.

[0181] (4) Determine the type of the light source of the headlamp S based on the image captured with the band-pass filter 541 placed in front of the monochrome camera 51 and the image captured with the relative sensitivity filter 545 placed in front of the monochrome camera 51.

[0182] (5) Rotate the neutral density filter wheel 56 to place an appropriate neutral density filter to measure the pulsed point light source.

[0183] FIG. 27 is a flowchart showing an example of the processing procedure of the headlamp test using the headlamp tester 1 shown in FIG. 26. The processing executed by the headlamp tester 1 shown in FIG. 27 may be realized, for example, by one or a plurality of processors 102 of the processing device 100 executing the measurement program 110. Note that previously, the vehicle VH is adjusted to face the lens unit 10 (vehicle facing straight).

[0184] Referring to FIG. 27, the headlamp tester 1 arranges one of the specific visibility filter 545 and the band-pass filter 541 in front of the monochrome camera 51 according to a user operation (step S100). The user selects an appropriate dimming filter while checking the output of the monochrome camera 51. That is, the headlamp tester 1 arranges a dimming filter in front of the monochrome camera 51 according to a user operation (step S102). The dimming filter may be selected according to the exposure time of the monochrome camera 51.

[0185] If an appropriate dimming filter has not been selected for both the specific visibility filter 545 and the band-pass filter 541 (NO in step S104), the headlamp tester 1 arranges the other of the specific visibility filter 545 and the band-pass filter 541 in front of the monochrome camera 51 according to a user operation (step S106). Then, the processes below step S102 are repeated.

[0186] If an appropriate dimming filter has been selected for both the specific visibility filter 545 and the band-pass filter 541 (YES in step S104), the user adjusts the positional relationship between the headlamp S and the lens unit 10 while checking the output of the monochrome camera 51 (step S108).

[0187] The headlamp tester 1 arranges the specific visibility filter 545 in front of the monochrome camera 51 (step S110), and acquires a measurement image captured by the monochrome camera 51 (step S112). Then, the headlamp tester 1 measures the luminous intensity based on the measurement image acquired in step S112 (step S114).

[0188] Subsequently, the headlamp tester 1 arranges the band-pass filter 541 in front of the monochrome camera 51 (step S116), and acquires the measurement image captured by the monochrome camera 51 (step S118). Then, the headlamp tester 1 detects the elbow point based on the measurement image acquired in step S112 or the measurement image acquired in step S118 (step S120). In detecting the elbow point in step S120, the process of detecting the elbow point shown in FIG. 18 may be executed, or a method based on the intersection of the straight line indicated by the conventional horizontal cut-off and the oblique cut-off may be executed.

[0189] The headlamp tester 1 arranges the blue filter 542 in front of the monochrome camera 51 (step S122), and acquires the measurement image captured by the monochrome camera 51 (step S124). The headlamp tester 1 arranges the green filter 543 in front of the monochrome camera 51 (step S126), and acquires the measurement image captured by the monochrome camera 51 (step S128). The headlamp tester 1 arranges the red filter 544 in front of the monochrome camera 51 (step S130), and acquires the measurement image captured by the monochrome camera 51 (step S132).

[0190] The headlamp tester 1 synthesizes the color image of the irradiation image from the measurement image acquired in step S124, the measurement image acquired in step S128, and the measurement image acquired in step S132 (step S134).

[0191] The headlamp tester 1 discriminates the type of the light source of the headlamp S based on the measurement image acquired in step S112 and the measurement image acquired in step S118 (step S136).

[0192] Finally, the headlamp tester 1 outputs the measurement result (step S138). Then, the process ends.

[0193] Note that the execution order of the light intensity measurement (step S114), the elbow point detection (step S120), the color image synthesis (step S134), and the light source type determination (step S136) may be any order.

[0194] (h2: Multi-camera + ND filter wheel) FIG. 28 is a schematic diagram showing another configuration example of the detection module 50 of the headlamp tester 1 according to the present embodiment. Referring to FIG. 28, the detection module 50 includes monochrome cameras 51-1 and 51-2, an RGB camera 52, an ND filter wheel 56, and a motor 57.

[0195] A specific sensitivity filter 511 is attached to the lens of the monochrome camera 51-1. A band-pass filter 512 is attached to the lens of the monochrome camera 51-2. The band-pass filter 512 may use, for example, a narrow-band filter having a center wavelength of 440 nm and a half-value width of 20 nm.

[0196] The motor 57 is driven by the driving device 40 to rotate the ND filter wheel 56. The motor 57 may be a stepping motor.

[0197] The driving device 40 can also detect the origin of the motor 57 (ND filter wheel 56).

[0198] The processing device 100 gives a command to the driving device 40 to rotate the motor 57 (ND filter wheel 56), and gives an imaging command to the monochrome cameras 51-1 and 51-2 and the RGB camera 52. The processing device 100 processes the outputs of the monochrome cameras 51-1 and 51-2 and the RGB camera 52. More specifically, the processing device 100 acquires the measurement images respectively captured by the monochrome cameras 51-1 and 51-2 and the RGB camera 52.

[0199] The monochrome cameras 51-1 and 51-2 and the RGB camera 52 are arranged on the circumference through which the holes of the dimming filter wheel 56 pass as the dimming filter wheel 56 rotates. Accordingly, an arbitrary dimming filter can be arranged in front of each of the monochrome cameras 51-1 and 51-2 and the RGB camera 52.

[0200] FIG. 29 is a flowchart showing an example of a processing procedure of a headlight test using the headlight tester 1 shown in FIG. 28. The processing executed by the headlight tester 1 shown in FIG. 29 may be realized, for example, by one or a plurality of processors 102 of the processing device 100 executing the measurement program 110. Note that, previously, adjustment is performed so that the vehicle VH faces the lens unit 10 (vehicle facing).

[0201] Referring to FIG. 29, the user selects an appropriate dimming filter while checking the output of the cameras (the monochrome cameras 51-1 and 51-2 and the RGB camera 52). That is, the headlight tester 1 arranges a dimming filter in front of the cameras according to a user operation (step S200). The dimming filter may be selected according to the exposure time of the monochrome camera 51.

[0202] The user adjusts the positional relationship between the headlight S and the lens unit 10 while checking the output of the cameras (step S202).

[0203] The headlight tester 1 arranges the dimming filter selected in step S200 in front of the monochrome camera 51-1 (step S204), and acquires a measurement image captured by the monochrome camera 51-1 having the relative sensitivity filter 511 attached to the lens (step S206).

[0204] Subsequently, the headlight tester 1 arranges the dimming filter selected in step S200 in front of the monochrome camera 51-2 (step S208), and acquires a measurement image captured by the monochrome camera 51-2 having the band-pass filter 512 attached to the lens (step S210).

[0205] Subsequently, the headlight tester 1 places the dimming filter selected in step S200 in front of the RGB camera 52 (step S212), and acquires a measurement image captured by the RGB camera 52 (step S214). The measurement image acquired in step S214 is a color image.

[0206] Based on the measurement image acquired in step S206, the headlight tester 1 measures the luminous intensity (step S216).

[0207] Based on at least one of the measurement image acquired in step S206, the measurement image acquired in step S210, and the measurement image acquired in step S214, the headlight tester 1 detects the elbow point (step S218). In detecting the elbow point in step S218, the process of detecting the elbow point shown in FIG. 18 may be executed, or a method based on the intersection of the straight line indicated by the conventional horizontal cut-off and the oblique cut-off may be executed.

[0208] Based on the measurement image acquired in step S206 and the measurement image acquired in step S210, the headlight tester 1 discriminates the type of the light source of the headlight S (step S220).

[0209] Finally, the headlight tester 1 outputs the measurement result (step S222). Then, the process ends.

[0210] Note that the execution order of the luminous intensity measurement (step S216), the elbow point detection (step S218), the color image acquisition (step S214), and the light source type discrimination (step S220) may be any order.

[0211] According to the headlight tester 1 shown in FIG. 28, since imaging can be performed with three cameras, the measurement time can be shortened.

[0212] (h3: Color camera + correction filter wheel) FIG. 30 is a schematic diagram showing still another configuration example of the detection module 50 of the headlamp tester 1 according to the present embodiment. The process executed by the headlamp tester 1 shown in FIG. 30 may be realized, for example, by one or a plurality of processors 102 of the processing device 100 executing the measurement program 110. Referring to FIG. 30, the detection module 50 includes an RGB camera 52, a correction filter wheel 58, and a motor 59.

[0213] The motor 59 is driven by the driving device 40 to rotate the correction filter wheel 58. The motor 59 may be a stepping motor.

[0214] The driving device 40 can also detect the origin of the motor 59 (correction filter wheel 58).

[0215] The processing device 100 gives a command to the driving device 40 to rotate the motor 59 (correction filter wheel 58), and gives an imaging command to the RGB camera 52. The processing device 100 processes the output of the RGB camera 52. More specifically, the processing device 100 acquires the measurement images respectively captured by the RGB camera 52.

[0216] For example, a green correction filter 581, a band-pass filter 582, and a dimming filter 583 may be respectively mounted on a plurality of holes of the correction filter wheel 58. Any filter may be mounted on the remaining holes of the correction filter wheel 58. For example, dimming filters 584 and 585 having different dimming amounts may be respectively mounted on the correction filter wheel 58.

[0217] Since the detection module 50 shown in FIG. 30 has the RGB camera 52, a color image of the irradiation image can be captured by arranging an appropriate dimming filter in front of the RGB camera 52.

[0218] By arranging the band - pass filter 582 in front of the RGB camera 52, narrow - band measurement becomes possible. Since the transmission wavelength width of the band - pass filter 582 is narrower than the transmission wavelength width of the blue filter of the RGB camera (refer to the transmittance characteristics in Fig. 6), narrow - band measurement is possible even if the blue filter exists. Also, a dimming effect can occur when the band - pass filter 582 and the blue filter of the RGB camera overlap. Therefore, even if the dimming filter 583 is not arranged in front of the RGB camera 52, the pulsed point - light source can be measured.

[0219] By arranging the green correction filter 581 in front of the RGB camera 52, the luminous intensity can be measured (refer to the above formula (3) etc.). Also, a dimming effect can occur when the green correction filter 581 and the blue filter of the RGB camera overlap. Therefore, even if the dimming filter 583 is not arranged in front of the RGB camera 52, the pulsed point - light source can be measured.

[0220] FIG. 31 is a flowchart showing an example of the processing procedure of the headlight test using the headlight tester 1 shown in FIG. 30. First, the vehicle VH is adjusted to face the lens unit 10 (vehicle facing).

[0221] Referring to FIG. 31, the headlight tester 1 arranges the band - pass filter 582 in front of the RGB camera 52 (step S300) and acquires a measurement image captured by the RGB camera 52 (step S302). The headlight tester 1 detects the elbow point based on the measurement image acquired in step S302 (step S304). In detecting the elbow point in step S304, the process of detecting the elbow point shown in FIG. 18 may be executed, or a method based on the intersection of the straight line indicated by the conventional horizontal cut - off and the diagonal cut - off may be executed.

[0222] The headlight tester 1 arranges the dimming filter 583 in front of the RGB camera 52 (step S306) and acquires a measurement image (color image of the irradiation image) captured by the RGB camera 52 (step S308).

[0223] The headlamp tester 1 arranges the green correction filter 581 in front of the RGB camera 52 (step S310) and acquires a measurement image captured by the RGB camera 52 (step S312). The headlamp tester 1 measures the luminous intensity based on the measurement image acquired in step S312 (step S314).

[0224] The headlamp tester 1 determines the type of the light source of the headlamp S based on the measurement image acquired in step S302 and the measurement image acquired in step S312 (step S316).

[0225] Finally, the headlamp tester 1 outputs the measurement result (step S318). Then, the process ends.

[0226] Note that the execution order of the luminous intensity measurement (step S314), the elbow point detection (step S304), the color image acquisition (step S308), and the light source type determination (step S316) may be any order.

[0227] According to the headlamp tester 1 shown in FIG. 30, since the device configuration is simple, the cost can be suppressed and the measurement time can be made relatively short.

[0228] (h4: Variant example) In the above-described configuration example, a configuration using a filter wheel is adopted, but a configuration in which individual filters can be fixedly or variably arranged in front of the camera may be adopted. For example, as a configuration in which individual filters can be variably arranged, a solenoid or the like may be used.

[0229] <I. Advantages> According to the present embodiment, by adopting a configuration in which a green correction filter can be arranged in front of an RGB camera, a color image of the irradiation image of a headlamp can be recorded using the RGB camera, and the luminous intensity can be measured using the same RGB camera.

[0230] According to this embodiment, by adopting a configuration in which a dimming filter can be arranged in front of the camera, it is possible to reduce the measurement variation even for a light source that is pulsed on and off.

[0231] According to this embodiment, by adopting narrow-band measurement using a band-pass filter, it is possible to suppress the cutoff included in the irradiation image of the headlight from becoming ambiguous.

[0232] According to this embodiment, the type of the light source can be determined using the images obtained by the light intensity measurement and the narrow-band measurement.

[0233] According to this embodiment, it is possible to more accurately determine the elbow point of a headlight having a light distribution characteristic in which a concave portion exists in the horizontal portion of the horizontal cutoff.

[0234] According to this embodiment, by arranging the filter wheel in front of the camera, it is possible to perform a plurality of types of measurements in a relatively short time.

[0235] The embodiments disclosed this time should be considered to be illustrative in all respects and not restrictive. The scope of the present invention is shown not by the above description but by the claims, and it is intended that all modifications within the meaning and scope equivalent to the claims are included.

Explanation of Reference Numerals

[0236] 1 Headlight tester, 4 Column part, 6 Base part, 10 Lens unit, 11 Camera for frontal alignment confirmation, 12 Fresnel lens, 13 Screen, 14 Laser for frontal alignment adjustment, 20 Operation part, 30 Display part, 40 Driving device, 50 Detection module, 50R Measurement point, 51 Monochrome camera, 52 RGB camera, 53, 55, 57, 59 Motor, 54 Color filter wheel, 56 Neutral density filter wheel, 58 Correction filter wheel, 100 Processing device, 102 Processor, 104 Memory, 106 Storage, 108 System program, 110 Measurement program, 511, 545 Luminosity efficiency filter, 512, 541, 582 Band-pass filter, 542 Blue filter, 543 Green filter, 544 Red filter, 561, 562, 563, 564, 565, 583, 584, 585 Neutral density filter, 581 Green correction filter, AX Optical axis, RX1, RX2 Rotation axis, S Headlight, VH Vehicle.

Claims

1. A screen onto which light from a vehicle headlamp is projected, an RGB camera that captures an image projected onto the screen, a correction filter disposed in front of the RGB camera, and a processing device that processes the output of the RGB camera, wherein the correction filter has a transmittance characteristic determined based on the transmittance characteristic of the green filter of the RGB camera and the relative spectral sensitivity, and the processing device calculates the luminous intensity of the headlamp based on the green output of the RGB camera, the headlamp tester.

2. The headlamp tester according to claim 1, wherein the transmittance characteristic of the correction filter is a result of dividing the relative spectral sensitivity by the transmittance characteristic of the green filter.

3. The headlamp tester according to claim 1 or 2, wherein the correction filter is configured by stacking a plurality of simple Gaussian notch filters.

4. A screen onto which light from a vehicle headlamp is projected, a camera that captures an image projected onto the screen, and a processing device that processes the output of the camera, wherein the processing device discriminates the type of the light source of the headlamp based on a first measurement image captured when a narrow-band band-pass filter having a center wavelength of 440 nm is disposed in front of the camera and a second measurement image captured when a relative spectral sensitivity filter reflecting the relative spectral sensitivity is disposed in front of the camera, the headlamp tester.

5. The headlamp tester according to claim 4, wherein the processing device discriminates the type of the light source of the headlamp based on a discrimination value based on a difference between a value obtained by dividing an integrated value of pixel values included in the first measurement image by a wavelength integration value of the transmittance characteristic of the band-pass filter and a value obtained by dividing an integrated value of pixel values included in the second measurement image by a wavelength integration value of the transmittance characteristic of the relative spectral sensitivity filter.

6. The headlamp tester according to claim 4, wherein the relative spectral sensitivity filter has a transmittance characteristic corresponding to the relative spectral sensitivity or a transmittance characteristic determined based on the transmittance characteristic of the green filter of the RGB camera and the relative spectral sensitivity.

7. The headlamp tester according to any one of claims 4 to 6, wherein the processing device discriminates whether the light source of the headlamp is a high-intensity discharge (HID) lamp, a light-emitting diode (LED), or a halogen lamp.

8. The first measurement image is captured with a dimming filter arranged in addition to the band-pass filter, and the second measurement image is captured with the dimming filter arranged in addition to the specific sensitivity ratio filter. The headlamp tester according to any one of claims 4 to 6.

9. A screen on which light from a vehicle headlamp is projected; A camera that captures an image projected on the screen; A processing device that acquires a measurement image captured by the camera, The processing device sequentially sets an area of a predetermined size for the measurement image, and based on a first integrated value and a second integrated value obtained by multiplying a first matrix and a second matrix for each area, respectively, extracts pixels representing an area that satisfies a first condition as a first candidate point group; for each pixel included in the first candidate point group, the number of pixels with a light intensity lower than a predetermined value in the upper right area with respect to the pixel as a reference, and the number of pixels with a light intensity lower than a predetermined value in the upper right area and pixels with a light intensity equal to or higher than the predetermined value in areas other than the upper right area with respect to the pixel as a reference, extracting one or more pixels that satisfy a second condition as a second candidate point group; Among the pixels included in the second candidate point group, determining a pixel with the maximum integrated score based on the first score, the integrated value of the light intensity of the pixels in the upper right area, the integrated value of the light intensity of the pixels in the lower area with respect to the pixel as a reference, and a third score indicating the levelness as an elbow point. The headlamp tester that executes the process.

10. The first matrix has elements in the upper right side from the matrix center being zero, The second matrix has elements other than those in the upper right side from the matrix center being zero, The first condition includes that the first integrated value is equal to or greater than a first threshold value and the second integrated value is less than the first threshold value. The headlamp tester according to claim 9.

11. The first score is the sum of the number of pixels with a luminance lower than a predetermined value in the upper right area with respect to each pixel as a reference, and the number of pixels with a luminance greater than or equal to the predetermined value in areas other than the upper right area with respect to each pixel as a reference. The second score is the sum of the difference between the integrated value of the luminance of the pixels in the lower right area with respect to each pixel as a reference and the integrated value of the luminance of the pixels in the upper right area with respect to each pixel as a reference, and the difference between the integrated value of the luminance of the pixels in the lower left area with respect to each pixel as a reference and the integrated value of the luminance of the pixels in the upper right area with respect to each pixel as a reference. The headlamp tester according to claim 9 or 10.

12. The third score is calculated based on the difference in luminance at both ends equidistant in the horizontal direction with respect to each pixel as a reference. The headlamp tester according to claim 9 or 10.

13. Imaging an image projected from the headlamp of a vehicle onto a screen with an RGB camera having a correction filter disposed in the front stage. Calculating the luminance of the headlamp based on the green output of the RGB camera. The correction filter has a transmittance characteristic determined based on the transmittance characteristic of the green filter of the RGB camera and the specific visibility. A measurement method.

14. Imaging an image projected from the headlamp of a vehicle onto a screen with a camera having a narrow-band band-pass filter centered at 440 nm disposed in the front stage to obtain a first measurement image. Imaging an image projected from the headlamp of the vehicle onto the screen with a camera having a specific visibility filter reflecting the specific visibility disposed in the front stage to obtain a second measurement image. Discriminating the type of the light source of the headlamp based on the first measurement image and the second measurement image. A measurement method.

15. Imaging an image projected from the headlamp of a vehicle onto a screen with a camera to obtain a measurement image. An area of a predetermined size is sequentially set for the measurement image, and based on a first integrated value and a second integrated value obtained by multiplying a first matrix and a second matrix by each area, respectively, pixels representing an area that satisfies a first condition are extracted as a first candidate point group; For each pixel included in the first candidate point group, the number of pixels with a light intensity lower than a predetermined value in the upper right area with respect to the pixel, and the number of pixels with a light intensity lower than a predetermined value in the upper right area and the number of pixels with a light intensity greater than or equal to the predetermined value in the area other than the upper right area with respect to the pixel, a first score is calculated, and one or more pixels that satisfy a second condition are extracted as a second candidate point group; Among the pixels included in the second candidate point group, based on the first score, the integrated value of the light intensity of the pixels in the upper right area, the integrated value of the light intensity of the pixels in the lower area with respect to the pixel, and a second score, and a third score indicating the degree of horizontalness, a pixel with the maximum integrated score is determined as an elbow point, and a measurement method is provided.

16. A measurement program for causing a computer to execute the measurement method according to any one of Claims 13 to 15.

Images