Automobile lighting detection system and detection method

Abstract

The present invention discloses an automobile light detection system and a detection method, which relate to the technical field of light detection. By starting a target automobile light, when the target automobile light is running in a normal state, the color temperature data of the automobile light within a preset time period is obtained to obtain a color temperature deviation coefficient; within the preset time period, the brightness distribution image of the target automobile light beam projected is captured multiple times in real time to obtain a brightness distribution image set, and the light beam brightness unqualified coefficient and the light beam quality degradation coefficient are obtained according to the brightness distribution image set; the light quality comprehensive evaluation coefficient of the target automobile light is obtained according to the color temperature deviation coefficient, the light beam brightness uniformity coefficient and the light beam quality degradation coefficient, and whether the light quality of the target automobile light is qualified is judged in combination with a preset light quality comprehensive evaluation coefficient threshold. In this way, it is possible to judge whether the detection of automobile lights based on simple indicators such as brightness and angle will lead to insufficient detection according to the actual situation, thereby improving the comprehensiveness and accuracy of the detection.

Description

Technical Field

[0001] The present invention relates to the technical field of light detection, and in particular to an automobile light detection system and a detection method. Background Art

[0002] Automobile lighting testing is to test the key performance indicators of the vehicle lighting system, such as brightness, illumination angle, and light color, to ensure that the lighting meets safety specifications and regulatory requirements, thereby ensuring driving safety. Existing automobile lighting testing systems usually use dedicated testing equipment to determine whether the lights are qualified based on simple indicators such as brightness and angle; during the testing process, the equipment will use optical sensors and image processing technology to accurately measure parameters such as light intensity and illumination angle. Through the automated analysis system, the testing equipment can quickly process and compare the data, comparing the actual measured parameters with the specified standards to determine whether the lights meet the standards; this system not only improves testing efficiency, but also ensures the accuracy and consistency of the test results, which helps to achieve more reliable automobile safety performance management;

[0003] Existing car light testing usually uses simple indicators such as brightness and angle to determine whether the lights are qualified. However, as the lights are used, they will gradually age and add more subtle problems. If the car lights are only tested based on simple indicators such as brightness and angle, it may lead to insufficient detection. Summary of the invention

[0004] The purpose of the present invention is to solve the above-mentioned problems and provide an automobile light detection system and a detection method.

[0005] In a first aspect of the present invention, a method for detecting automobile lights is first proposed, the method comprising:

[0006] Start the target vehicle lamp, when the target vehicle lamp is operating in a normal state, obtain the vehicle lamp color temperature data within a preset time period, and obtain the color temperature deviation coefficient according to the vehicle lamp color temperature data;

[0007] When the target vehicle lamp is operating in a normal state, the brightness distribution image of the target vehicle lamp light beam is captured multiple times in real time within a preset time period to obtain a brightness distribution image set, and the light beam brightness unqualified coefficient and the light beam quality degradation coefficient are obtained according to the brightness distribution image set;

[0008] The comprehensive evaluation coefficient of the light quality of the target vehicle lamp is obtained according to the color temperature deviation coefficient, the beam brightness uniformity coefficient and the beam quality reduction coefficient;

[0009] Whether the light quality of the target headlight is qualified is judged according to the light quality comprehensive evaluation coefficient of the target headlight and a preset light quality comprehensive evaluation coefficient threshold.

[0010] Optionally, obtaining a color temperature deviation coefficient according to the vehicle light color temperature data includes:

[0011] Obtain the actual headlight color temperature value and the preset standard headlight color temperature value of the target headlight at different times in the preset time period, and mark the actual headlight color temperature value and the preset standard headlight color temperature value as and , The numbers indicating the order of the actual color temperature values ​​of the headlights at different times and the preset standard color temperature values ​​of the headlights. =1, 2, 3, 4, ..., , is a positive integer;

[0012] according to and Get the color temperature deviation value , the calculation formula is: ;

[0013] According to the color temperature deviation value And the corresponding preset deviation weight is used to obtain the color temperature deviation coefficient. The calculation formula is: , where is the preset bias weight, is the color temperature deviation coefficient.

[0014] Optionally, obtaining a beam brightness unqualified coefficient according to the brightness distribution image set includes:

[0015] During the preset time period, the brightness distribution image of the target vehicle light beam projected onto the detection screen is captured in real time by a high-precision camera to obtain a brightness distribution image set. , where n represents the total number of brightness distribution images in the brightness distribution image set;

[0016] For each brightness distribution image Process and extract the corresponding brightness value matrix , where each element Represents the image Image No. The brightness value of the pixel;

[0017] For each image , calculate the mean brightness and standard deviation , the formula is as follows:

[0018] ;

[0019] In the formula, For images The average pixel value, For images Height, For images The width of To transform the image in position The pixel value of

[0020] ;

[0021] According to the mean and standard deviation of all images, the beam brightness non-uniformity coefficient is calculated. The calculation formula is:

[0022] ;

[0023] In the formula, is the beam brightness unevenness coefficient; the beam brightness unqualified coefficient is obtained according to the beam brightness unevenness coefficient.

[0024] Optionally, obtaining a beam brightness unqualified coefficient according to the beam brightness non-uniformity coefficient includes:

[0025] For each image of the brightness distribution image set, a brightness value matrix is ​​extracted, and a center point of the light beam is determined according to the brightness value matrix;

[0026] Record the brightness value of the center of the light beam, define a certain range around the center of the light beam, and extract all brightness values ​​within the range from the brightness value matrix;

[0027] Calculate the average brightness value of the range area, and divide the brightness value at the center of the beam by the average brightness value of the range area to get the brightness attenuation ratio:

[0028] The beam brightness non-uniformity coefficient and the brightness attenuation ratio are normalized to obtain the beam brightness unqualified coefficient. The calculation formula is: , where and are the normalized beam brightness non-uniformity coefficient and brightness attenuation ratio, is the beam brightness failure coefficient, , They are and The preset scaling factor of , Both are greater than 0.

[0029] Optionally, obtaining the beam quality degradation coefficient according to the brightness distribution image set includes:

[0030] For each image in the brightness distribution image set, the edge detection algorithm is used to calculate the image edge clarity. The calculation formula is:

[0031] ;

[0032] In the formula, is the image edge clarity, Indicates the edge area The brightness value of a pixel, is the average brightness value of the edge area, is the number of edge pixels;

[0033] For each image in the brightness distribution image set, the captured image is processed by image processing software to determine the brightness of the center of the light beam, and a threshold is set, and the brightness values ​​falling below the threshold are extracted from the image, and the sum of these brightness values ​​is calculated to obtain the scattered light intensity;

[0034] Calculate the total brightness value of the entire image to obtain the total projection intensity, and divide the scattered light intensity by the total projection intensity to obtain the scattered light ratio;

[0035] Calculate image edge clarity The difference between the scattered light ratio and the preset scattered light ratio is calculated to obtain the beam quality degradation coefficient. The calculation formula is: , where and are the difference between the image edge clarity and the preset edge clarity, and the difference between the scattered light ratio and the preset scattered light ratio, respectively. is the beam quality degradation factor, , They are and The preset scaling factor of .

[0036] Optionally, the comprehensive evaluation coefficient of the light quality of the target vehicle light obtained according to the color temperature deviation coefficient, the beam brightness uniformity coefficient and the beam quality degradation coefficient includes:

[0037] ;

[0038] In the formula, is the comprehensive evaluation coefficient of lighting quality, , , They are color temperature deviation coefficient, beam brightness uniformity coefficient and beam quality degradation coefficient respectively; , , They are , , The preset scaling factor of , , Both are greater than 0.

[0039] Optionally, judging whether the light quality of the target headlight is qualified according to the light quality comprehensive evaluation coefficient of the target headlight and a preset light quality comprehensive evaluation coefficient threshold includes:

[0040] Comparing the light quality comprehensive evaluation coefficient of the target vehicle light with a preset light quality comprehensive evaluation coefficient threshold;

[0041] If the light quality comprehensive evaluation coefficient of the target vehicle lamp is not less than the preset light quality comprehensive evaluation coefficient threshold, it means that the light quality of the target vehicle lamp is unqualified;

[0042] If the light quality comprehensive evaluation coefficient of the target vehicle lamp is less than the preset light quality comprehensive evaluation coefficient threshold, and other indicators of the light of the target vehicle lamp are qualified, it means that the light quality of the target vehicle lamp is qualified.

[0043] In a second aspect of the present invention, a vehicle light detection system is provided, the system comprising:

[0044] Color temperature deviation module: start the target headlight, when the target headlight is running in a normal state, obtain the headlight color temperature data within a preset time period, and obtain the color temperature deviation coefficient according to the headlight color temperature data;

[0045] Beam calculation module: when the target headlight is operating in a normal state, the brightness distribution image of the target headlight beam is captured multiple times in real time within a preset time period to obtain a brightness distribution image set, and the beam brightness unqualified coefficient and beam quality degradation coefficient are obtained based on the brightness distribution image set;

[0046] Comprehensive evaluation module: obtains the comprehensive evaluation coefficient of the target vehicle light quality according to the color temperature deviation coefficient, beam brightness uniformity coefficient and beam quality degradation coefficient;

[0047] Judgment and detection module: judge whether the light quality of the target headlight is qualified according to the light quality comprehensive evaluation coefficient of the target headlight and the preset light quality comprehensive evaluation coefficient threshold.

[0048] Beneficial effects of the present invention:

[0049] The present invention proposes an automobile light detection system and a detection method. By starting a target automobile light, when the target automobile light is operating in a normal state, the automobile light color temperature data within a preset time period is obtained to obtain a color temperature deviation coefficient; within the preset time period, the brightness distribution image of the target automobile light beam projected is captured multiple times in real time to obtain a brightness distribution image set, and the light beam brightness unqualified coefficient and the light beam quality degradation coefficient are obtained according to the brightness distribution image set; the light quality comprehensive evaluation coefficient of the target automobile light is obtained according to the color temperature deviation coefficient, the light beam brightness uniformity coefficient and the light beam quality degradation coefficient, and combined with the preset light quality comprehensive evaluation coefficient threshold, it is judged whether the light quality of the target automobile light is qualified. In this way, it is possible to judge whether the detection of automobile lights based on simple indicators such as brightness and angle will lead to insufficient detection according to the actual situation, thereby improving the comprehensiveness and accuracy of the detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] The present invention will be further described below in conjunction with the accompanying drawings.

[0051] Figure 1 is a flow chart of a method for detecting automobile lights;

[0052] Figure 2 The figure is a framework diagram of an automobile light detection system. DETAILED DESCRIPTION

[0053] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0054] Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in the field without making any creative work shall fall within the scope of protection of the present invention.

[0055] The embodiment of the present invention provides a method for detecting automobile lights. Figure 1 , Figure 1 A flow chart of a vehicle light detection method provided by an embodiment of the present invention. The method comprises the following steps:

[0056] Start the target vehicle lamp, when the target vehicle lamp is operating in a normal state, obtain the vehicle lamp color temperature data within a preset time period, and obtain the color temperature deviation coefficient according to the vehicle lamp color temperature data;

[0057] When the target vehicle lamp is operating in a normal state, the brightness distribution image of the target vehicle lamp light beam is captured multiple times in real time within a preset time period to obtain a brightness distribution image set, and the light beam brightness unqualified coefficient and the light beam quality degradation coefficient are obtained according to the brightness distribution image set;

[0058] The comprehensive evaluation coefficient of the light quality of the target vehicle lamp is obtained according to the color temperature deviation coefficient, the beam brightness uniformity coefficient and the beam quality reduction coefficient;

[0059] Whether the light quality of the target headlight is qualified is judged according to the light quality comprehensive evaluation coefficient of the target headlight and a preset light quality comprehensive evaluation coefficient threshold.

[0060] A vehicle light detection method provided in an embodiment of the present invention can determine whether detecting vehicle lights based on simple indicators such as brightness and angle will lead to insufficient detection according to actual conditions, thereby improving the comprehensiveness and accuracy of detection.

[0061] In one embodiment, obtaining the color temperature deviation coefficient according to the vehicle light color temperature data includes:

[0062] Obtain the actual headlight color temperature value and the preset standard headlight color temperature value of the target headlight at different times in the preset time period, and mark the actual headlight color temperature value and the preset standard headlight color temperature value as and , The numbers indicating the order of the actual color temperature values ​​of the headlights at different times and the preset standard color temperature values ​​of the headlights. =1, 2, 3, 4, ..., , is a positive integer;

[0063] according to and Get the color temperature deviation value , the calculation formula is: ;

[0064] According to the color temperature deviation value And the corresponding preset deviation weight is used to obtain the color temperature deviation coefficient. The calculation formula is: , where is the preset bias weight, is the color temperature deviation coefficient.

[0065] It should be noted that, within a preset time period, the actual color temperature value of the target headlight at different time points is collected in real time by a high-precision color temperature sensor installed near the target headlight. Other acquisition methods may also be used, which are not specifically limited or elaborated upon. In addition, the preset standard headlight color temperature value is the standard color temperature range of the headlight when it leaves the factory, such as 4300K ​​to 6500K. These values ​​can be obtained from the technical specifications of the headlight manufacturer. In addition, the preset deviation weight is set by professionals according to actual conditions. For example, for slight deviations (0K to 100K), the weight is set to 1; for moderate deviations (100K to 200K), the weight is set to 2; for severe deviations (200K), the weight is set to 3, which are not limited or elaborated upon.

[0066] It should be noted that the color temperature deviation coefficient refers to the degree to which the actual color temperature value of the target headlight deviates from the preset standard color temperature value of the headlight; if the degree of deviation is greater, it means that the degree of aging of the target headlight will be great, and the light will have more subtle problems. If the car lights are only tested based on simple indicators such as brightness and angle, it may lead to insufficient detection. The reason is that as the headlights age, the color temperature may gradually tend to warm yellow or cold blue, which will not only affect the quality of vision at night, but may also cause the quality of reflected light to decline in rainy and foggy days, increasing driving risks; relying solely on simple indicators such as brightness and beam angle for testing often cannot fully reflect the actual performance of the headlights, because these indicators cannot fully capture the potential safety hazards brought about by changes in the color temperature of the headlights; therefore, comprehensive consideration of color temperature deviation and other complex factors can provide a more comprehensive lighting performance evaluation, ensure safe driving and promptly detect potential aging problems, thereby avoiding accidents.

[0067] In one embodiment, obtaining the beam brightness unqualified coefficient according to the brightness distribution image set includes:

[0068] During the preset time period, the brightness distribution image of the target vehicle light beam projected onto the detection screen is captured in real time by a high-precision camera to obtain a brightness distribution image set. , where n represents the total number of brightness distribution images in the brightness distribution image set;

[0069] For each brightness distribution image Process and extract the corresponding brightness value matrix , where each element Represents the image Image No. The brightness value of the pixel;

[0070] For each image , calculate the mean brightness and standard deviation , the formula is as follows:

[0071] ;

[0072] In the formula, For images The average pixel value, For images Height, For images The width of To transform the image in position The pixel value of

[0073] ;

[0074] According to the mean and standard deviation of all images, the beam brightness non-uniformity coefficient is calculated. The calculation formula is:

[0075] ;

[0076] In the formula, is the beam brightness unevenness coefficient; the beam brightness unqualified coefficient is obtained according to the beam brightness unevenness coefficient.

[0077] In one embodiment, obtaining a beam brightness unqualified coefficient according to the beam brightness non-uniformity coefficient includes:

[0078] For each image in the brightness distribution image set, a brightness value matrix is ​​extracted, and the center point of the light beam is determined according to the brightness value matrix; usually, the center of the light beam can be determined by finding the pixel position with the maximum brightness value;

[0079] Record the brightness value of the center of the light beam, define a certain range area (for example, a circular area with a radius of R) around the center of the light beam, and extract all brightness values ​​within the area from the brightness value matrix;

[0080] Calculate the average brightness value of the range area, and divide the brightness value at the center of the beam by the average brightness value of the range area to get the brightness attenuation ratio:

[0081] The beam brightness non-uniformity coefficient and the brightness attenuation ratio are normalized to obtain the beam brightness unqualified coefficient. The calculation formula is: , where and are the normalized beam brightness non-uniformity coefficient and brightness attenuation ratio, is the beam brightness failure coefficient, , They are and The preset scaling factor of , Both are greater than 0.

[0082] It should be noted that and It is set by professionals according to the actual situation. Generally, and The sum of is 1, for example and They can be 0.4, 0.6 or other numbers respectively, and are not specifically limited. In addition, commonly used normalization methods include Min-Max normalization, Z-Score standardization, etc. The specific method is selected by professionals according to the actual situation and is not specifically limited or elaborated.

[0083] It should be noted that when the beam brightness unevenness coefficient is larger and the brightness attenuation ratio is larger, it means that the target headlight will be aged greatly, and the light will have more subtle problems. If the car lights are tested based on simple indicators such as brightness and angle, it may lead to insufficient detection. The reason is that when the beam brightness unevenness coefficient is larger, it means that the headlight cannot distribute light evenly when lighting, which may cause the brightness of some areas to be significantly reduced, while other areas have normal or excessive brightness. This unevenness is often caused by factors such as aging of the internal structure of the bulb, wear of the reflector or accumulation of dirt, which will directly affect the field of vision and safety during driving. The increase in the brightness attenuation ratio indicates that the brightness difference between the center of the beam and the surrounding area is increasing, which means that the concentrated lighting effect of the headlight is reduced and it cannot effectively illuminate the road ahead, which may cause the driver's recognition ability to decrease at night or in bad weather, increasing the risk of accidents. If only relying on simple indicators such as brightness and angle for detection, it may not be possible to identify such subtle changes in beam distribution, because these basic indicators cannot reflect the comprehensive performance of the light in actual use. For example, light scattering, changes in color temperature, and light beam clarity may gradually deteriorate when the surface brightness is normal. Therefore, focusing only on a single brightness value may cause potential safety hazards to not be discovered in time, resulting in distortion of lighting status assessment and failure to effectively protect driving safety.

[0084] In one implementation method, the beam brightness failure coefficient takes into account two important indicators: brightness non-uniformity and brightness attenuation ratio. This ensures that the test results are not limited to the absolute value of the brightness, but reflect the comprehensive performance of the light in actual use, and can more comprehensively evaluate the working status of the headlights.

[0085] In one embodiment, obtaining the beam quality degradation coefficient according to the brightness distribution image set includes:

[0086] For each image in the brightness distribution image set, the edge detection algorithm is used to calculate the image edge clarity. The calculation formula is:

[0087] ;

[0088] In the formula, is the image edge clarity, Indicates the edge area The brightness value of a pixel, is the average brightness value of the edge area, is the number of edge pixels;

[0089] For each image in the brightness distribution image set, the captured image is processed by image processing software so as to extract the relevant information of the light beam therefrom; this includes segmenting the light beam and extracting the light beam area and the background area;

[0090] In the processed image, the intensity of the scattered light and the total intensity of the projection are calculated using the brightness value matrix (the brightness value of each pixel);

[0091] Scattered light intensity: By analyzing the brightness values ​​in the image related to the edge of the beam and the background, the scattered light is identified and quantified; the area of ​​scattered light can usually be defined as the area around the beam where the brightness is significantly lower than the brightness of the center of the beam; it can be obtained using the following steps:

[0092] Calculate the brightness of the center of the light beam, set a threshold, extract the brightness values ​​below the threshold from the image, calculate the sum of these brightness values, and obtain the scattered light intensity;

[0093] Calculate the total brightness value of the entire image area to obtain the total projection intensity, and divide the scattered light intensity by the total projection intensity to obtain the scattered light ratio;

[0094] Calculate image edge clarity The difference between the scattered light ratio and the preset scattered light ratio is calculated to obtain the beam quality degradation coefficient. The calculation formula is: , where and are the difference between the image edge clarity and the preset edge clarity, and the difference between the scattered light ratio and the preset scattered light ratio, respectively. is the beam quality degradation factor, , They are and The preset scaling factor of .

[0095] It should be noted that the preset edge clarity and the preset scattered light ratio are set by professionals according to actual conditions and are not limited or elaborated on in detail.

[0096] It should be noted that if the edge clarity of the image is lower than the preset edge clarity and the scattered light ratio is higher than the preset scattered light ratio, the greater the decline in the quality of the headlight beam, which means that the aging degree of the target headlight will be very large, and the light will increase more subtle problems. If the car lights are only tested based on simple indicators such as brightness and angle, it may lead to insufficient detection. The reason is that if the edge clarity of the image is lower than the preset value and the scattered light ratio is higher than the preset standard, it usually indicates that the beam quality of the headlight has been significantly reduced, reflecting the aging degree of the target headlight. Over time, the reflector, bulb and other components of the headlight may affect the projection effect of its beam due to aging, pollution or wear, resulting in blurred beam edges and increased scattered light. This change not only affects the concentration and brightness of the light, but may also reduce the effective lighting range of the beam, increasing the safety risk of night driving. Relying on simple indicators such as brightness and angle for testing is often difficult to fully capture the potential performance degradation of headlights, because these basic indicators cannot reflect important parameters such as the clarity of the light beam and the proportion of scattered light, which may lead to misjudgment of the status of the headlights, resulting in failure to discover and deal with hidden dangers in a timely manner, thereby affecting driving safety.

[0097] In one embodiment, the comprehensive evaluation coefficient of the light quality of the target vehicle light is obtained according to the color temperature deviation coefficient, the beam brightness uniformity coefficient and the beam quality degradation coefficient, including:

[0098] ;

[0099] In the formula, is the comprehensive evaluation coefficient of lighting quality, , , They are color temperature deviation coefficient, beam brightness uniformity coefficient and beam quality degradation coefficient respectively; , , They are , , The preset scaling factor of , , Both are greater than 0.

[0100] It should be noted that , , It is set by professionals according to the actual situation. Generally, , , The sum of is 1, for example , , They can be 0.4, 0.3, 0.3, or other numbers, and are not specifically limited. In addition, commonly used normalization methods include Min-Max normalization, Z-Score normalization, etc. The specific method is selected by professionals according to the actual situation, and is not specifically limited or elaborated.

[0101] In one embodiment, judging whether the light quality of the target headlight is qualified according to the light quality comprehensive evaluation coefficient of the target headlight and a preset light quality comprehensive evaluation coefficient threshold comprises:

[0102] Comparing the light quality comprehensive evaluation coefficient of the target vehicle light with a preset light quality comprehensive evaluation coefficient threshold;

[0103] If the light quality comprehensive evaluation coefficient of the target vehicle lamp is not less than the preset light quality comprehensive evaluation coefficient threshold, it means that the light quality of the target vehicle lamp is unqualified;

[0104] If the light quality comprehensive evaluation coefficient of the target vehicle lamp is less than the preset light quality comprehensive evaluation coefficient threshold, and other indicators of the light of the target vehicle lamp are qualified, it means that the light quality of the target vehicle lamp is qualified.

[0105] It should be noted that the preset threshold of the comprehensive evaluation coefficient of lighting quality is set by professionals according to actual conditions, and no specific limitation or elaboration is made;

[0106] It should be noted that when the comprehensive evaluation coefficient of the light quality of the target headlight is not less than the preset threshold value of the comprehensive evaluation coefficient of light quality, it means that the light quality of the target headlight is unqualified; and when the comprehensive evaluation coefficient of the light quality of the target headlight is less than the preset threshold value of the comprehensive evaluation coefficient of light quality, it means that the light quality of the target headlight is qualified. At this time, detecting the car lights based on simple indicators such as brightness and angle can already be a relatively comprehensive detection of the car lights. Whether there are problems with the car lights can be judged based on the detection results based on simple indicators such as brightness and angle, and there will be no problem of insufficient detection, thereby improving the comprehensiveness and accuracy of the detection.

[0107] Based on the same inventive concept, the embodiment of the present invention also provides an automobile light detection system. Figure 2 , Figure 2 A framework diagram of an automobile light detection system provided by an embodiment of the present invention, the system comprising:

[0108] Color temperature deviation module: start the target headlight, when the target headlight is running in a normal state, obtain the headlight color temperature data within a preset time period, and obtain the color temperature deviation coefficient according to the headlight color temperature data;

[0109] Beam calculation module: when the target headlight is operating in a normal state, the brightness distribution image of the target headlight beam is captured multiple times in real time within a preset time period to obtain a brightness distribution image set, and the beam brightness unqualified coefficient and beam quality degradation coefficient are obtained based on the brightness distribution image set;

[0110] Comprehensive evaluation module: obtains the comprehensive evaluation coefficient of the target vehicle light quality according to the color temperature deviation coefficient, beam brightness uniformity coefficient and beam quality degradation coefficient;

[0111] Judgment and detection module: judge whether the light quality of the target headlight is qualified according to the light quality comprehensive evaluation coefficient of the target headlight and the preset light quality comprehensive evaluation coefficient threshold.

[0112] An automobile light detection system provided based on an embodiment of the present invention can determine whether detecting automobile lights based on simple indicators such as brightness and angle will lead to insufficient detection according to actual conditions, thereby improving the comprehensiveness and accuracy of detection.

[0113] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A method for detecting automobile lights, characterized in that: The following steps are involved: Start the target vehicle lamp, when the target vehicle lamp is operating in a normal state, obtain the vehicle lamp color temperature data within a preset time period, and obtain the color temperature deviation coefficient according to the vehicle lamp color temperature data; When the target vehicle lamp is operating in a normal state, the brightness distribution image of the target vehicle lamp light beam is captured multiple times in real time within a preset time period to obtain a brightness distribution image set, and the light beam brightness unqualified coefficient and the light beam quality degradation coefficient are obtained according to the brightness distribution image set; The comprehensive evaluation coefficient of the light quality of the target vehicle lamp is obtained according to the color temperature deviation coefficient, the beam brightness uniformity coefficient and the beam quality reduction coefficient; Judging whether the light quality of the target headlight is qualified according to the light quality comprehensive evaluation coefficient of the target headlight and a preset light quality comprehensive evaluation coefficient threshold; The beam quality degradation coefficients obtained based on the brightness distribution image set include: For each image in the brightness distribution image set, the edge detection algorithm is used to calculate the image edge clarity. The calculation formula is: ； In the formula, is the image edge clarity, Indicates the edge area The brightness value of a pixel, is the average brightness value of the edge area, is the number of edge pixels; For each image in the brightness distribution image set, the captured image is processed by image processing software to determine the brightness of the center of the light beam, and a threshold is set, and the brightness values ​​falling below the threshold are extracted from the image, and the sum of these brightness values ​​is calculated to obtain the scattered light intensity; Calculate the total brightness value of the entire image to obtain the total projection intensity, and divide the scattered light intensity by the total projection intensity to obtain the scattered light ratio; Calculate image edge clarity The difference between the scattered light ratio and the preset scattered light ratio is calculated to obtain the beam quality degradation coefficient. The calculation formula is: , where and are the difference between the image edge clarity and the preset edge clarity, and the difference between the scattered light ratio and the preset scattered light ratio, respectively. is the beam quality degradation factor, , They are and The preset scaling factor of .

2. The vehicle light detection method according to claim 1, characterized in that: The color temperature deviation coefficients obtained based on the color temperature data of the vehicle lights include: Obtain the actual headlight color temperature value and the preset standard headlight color temperature value of the target headlight at different times in the preset time period, and mark the actual headlight color temperature value and the preset standard headlight color temperature value as and , The numbers indicating the order of the actual color temperature values ​​of the headlights at different times and the preset standard color temperature values ​​of the headlights. =1, 2, 3, 4, ..., , is a positive integer; according to and Get the color temperature deviation value , the calculation formula is: ; According to the color temperature deviation value And the corresponding preset deviation weight is used to obtain the color temperature deviation coefficient. The calculation formula is: , where is the preset bias weight, is the color temperature deviation coefficient.

3. The vehicle light detection method according to claim 1, characterized in that: The beam brightness unqualified coefficients obtained according to the brightness distribution image set include: During the preset time period, the brightness distribution image of the target vehicle light beam projected onto the detection screen is captured in real time by a high-precision camera to obtain a brightness distribution image set. , where n represents the total number of brightness distribution images in the brightness distribution image set; For each brightness distribution image Process and extract the corresponding brightness value matrix , where each element Represents the image Image No. The brightness value of the pixel; For each image , calculate the mean brightness and standard deviation , the formula is as follows: ； In the formula, For images The average pixel value, For images Height, For images The width of To transform the image in position The pixel value of ； According to the mean and standard deviation of all images, the beam brightness non-uniformity coefficient is calculated. The calculation formula is: ； In the formula, is the beam brightness unevenness coefficient; the beam brightness unqualified coefficient is obtained according to the beam brightness unevenness coefficient.

4. The automobile light detection method according to claim 3, characterized in that: The beam brightness unqualified coefficients obtained according to the beam brightness unevenness coefficient include: For each image of the brightness distribution image set, a brightness value matrix is ​​extracted, and a center point of the light beam is determined according to the brightness value matrix; Record the brightness value of the center of the light beam, define a certain range around the center of the light beam, and extract all brightness values ​​within the range from the brightness value matrix; Calculate the average brightness value of the range area, and divide the brightness value at the center of the beam by the average brightness value of the range area to get the brightness attenuation ratio: The beam brightness non-uniformity coefficient and the brightness attenuation ratio are normalized to obtain the beam brightness unqualified coefficient. The calculation formula is: , where and are the normalized beam brightness non-uniformity coefficient and brightness attenuation ratio, is the beam brightness failure coefficient, , They are and The preset scaling factor of , Both are greater than 0.

5. The vehicle light detection method according to claim 1, characterized in that: The comprehensive evaluation coefficients of the target vehicle light quality obtained based on the color temperature deviation coefficient, beam brightness uniformity coefficient and beam quality degradation coefficient include: ； In the formula, is the comprehensive evaluation coefficient of lighting quality, , , They are color temperature deviation coefficient, beam brightness uniformity coefficient and beam quality degradation coefficient respectively; , , They are , , The preset scaling factor of , , Both are greater than 0.

6. The automobile light detection method according to claim 1, characterized in that: Judging whether the light quality of the target light is qualified according to the light quality comprehensive evaluation coefficient of the target light and the preset light quality comprehensive evaluation coefficient threshold includes: Comparing the light quality comprehensive evaluation coefficient of the target vehicle light with a preset light quality comprehensive evaluation coefficient threshold; If the light quality comprehensive evaluation coefficient of the target vehicle lamp is not less than the preset light quality comprehensive evaluation coefficient threshold, it means that the light quality of the target vehicle lamp is unqualified; If the light quality comprehensive evaluation coefficient of the target vehicle lamp is less than the preset light quality comprehensive evaluation coefficient threshold, and other indicators of the light of the target vehicle lamp are qualified, it means that the light quality of the target vehicle lamp is qualified.

7. An automobile light detection system, used to implement an automobile light detection method according to any one of claims 1 to 6, characterized in that: The system comprises: Color temperature deviation module: start the target headlight, when the target headlight is running in a normal state, obtain the headlight color temperature data within a preset time period, and obtain the color temperature deviation coefficient according to the headlight color temperature data; Beam calculation module: when the target headlight is operating in a normal state, the brightness distribution image of the target headlight beam is captured multiple times in real time within a preset time period to obtain a brightness distribution image set, and the beam brightness unqualified coefficient and beam quality degradation coefficient are obtained based on the brightness distribution image set; Comprehensive evaluation module: obtains the comprehensive evaluation coefficient of the target vehicle light quality according to the color temperature deviation coefficient, beam brightness uniformity coefficient and beam quality degradation coefficient; Judgment and detection module: judge whether the light quality of the target headlight is qualified according to the light quality comprehensive evaluation coefficient of the target headlight and the preset light quality comprehensive evaluation coefficient threshold.

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