Industrial vision imaging method and system suitable for high-humidity water vapor environment and medium

Abstract

The invention provides an industrial visual imaging method and system suitable for a high-humidity water vapor environment and a medium, and the method comprises the steps: obtaining temperature fluctuation data and humidity fluctuation data in the water vapor environment at different time nodes based on a temperature and humidity sensor, and analyzing the environment parameters of a shooting environment; acquiring a shot image, analyzing brightness values of pixel points of the shot image, and performing equalization processing on the brightness values to obtain a brightness average value; analyzing fog concentration information of the shooting environment based on the environment parameters of the shooting environment, and analyzing interference information on the brightness mean value based on the fog concentration information; switching a shooting mode based on the interference information, and carrying out defogging processing on the shot image; carrying out enhancement processing, carrying out number domain stretching on the enhanced image, and then executing histogram equalization processing to obtain a visual imaging image; the shooting mode is adjusted by analyzing the interference information of the fog concentration on the image brightness, the image is defogged, the image is enhanced to recover image details, and the recognition capability is improved.

Description

Technical Field

[0001] This application relates to the field of industrial vision imaging technology, and more specifically, to an industrial vision imaging method, system, and medium suitable for high humidity and water vapor environments. Background Technology

[0002] With the increasing demand for industrial automation inspection, intelligent production line control, and quality traceability, machine vision is widely used in tasks such as dimensional measurement, defect detection, and product positioning. However, many production sites present interfering environmental factors such as high temperature, humidity, strong water vapor, fog, or condensation, which pose significant challenges to image acquisition quality.

[0003] Especially in the following typical operating conditions:

[0004] 1) Spray cleaning line: After the workpiece is cleaned by high-pressure water jet, a large amount of water vapor is dispersed.

[0005] 2) Water-cooled cutting area: generates a large amount of cold mist and condensation particles;

[0006] 3) Heat treatment or cooling channels: Due to alternating hot and cold temperatures, lens fogging and image distortion occur;

[0007] 4) Steam sterilization and cooking process: Air containing a large amount of water vapor forms a light scattering layer in front of the lens.

[0008] The main effects of water vapor on imaging systems are as follows:

[0009] 1) Lens condensation: Fogging or water film forming on the lens surface, resulting in blurred images;

[0010] 2) Strong Mie scattering: Water vapor particles with a diameter of 1 to 10 μm scatter visible light wavelengths with Mie scattering, resulting in a decrease in image grayscale and a reduction in contrast.

[0011] 3) Reduced areas of clear image: Local occlusion creates artifacts or dark areas;

[0012] 4) Unstable light intensity: Phenomena such as reflection and diffraction disrupt the image grayscale;

[0013] 5) Image structure missing: AI recognition algorithm cannot extract feature regions.

[0014] Current industrial vision systems often employ passive methods in high-humidity environments, such as:

[0015] 1) Add an air knife for demisting;

[0016] 2) Adjust the lighting angle;

[0017] 3) Increase brightness redundancy compensation;

[0018] 4) Use lenses with hydrophobic coatings;

[0019] However, these methods often suffer from problems such as complex integration, high power consumption, slow processing, and inability to adapt to dynamic water vapor disturbances, making it difficult to meet the requirements of online high-speed detection and continuous operation. Summary of the Invention

[0020] The purpose of this application is to provide an industrial visual imaging method, system, and medium suitable for high humidity and water vapor environments. By analyzing the interference information of fog concentration on image brightness, the shooting mode is adjusted, the image is defogging, and the image enhancement process restores image details and improves recognition capabilities.

[0021] This application also provides an industrial visual imaging method suitable for high humidity environments, including:

[0022] Temperature and humidity fluctuation data under water vapor conditions at different time points are obtained based on temperature and humidity sensors, and environmental parameters of the shooting environment are analyzed based on the temperature and humidity fluctuation data.

[0023] The image is acquired using an infrared-visible dual-spectrum imaging camera. The brightness values ​​of the pixels in the image are analyzed and averaged to obtain the average brightness value.

[0024] Based on the environmental parameters of the shooting environment, analyze the fog concentration information of the shooting environment, and based on the fog concentration information, analyze the interference information on the average brightness.

[0025] The shooting mode is switched based on the interference information, and the captured image is dehazed to obtain a dehazed image;

[0026] The dehazed image is enhanced to obtain an enhanced image. After the enhanced image is stretched in the digital domain, histogram equalization is performed to obtain the visual imaging image.

[0027] Optionally, in the industrial visual imaging method applicable to high humidity water vapor environments described in this application embodiment, temperature fluctuation data and humidity fluctuation data under water vapor environment at different time points are acquired based on temperature and humidity sensors, and environmental parameters of the shooting environment are analyzed based on the temperature fluctuation data and humidity fluctuation data, specifically including:

[0028] Acquire spatial parameter information of the shooting environment, including spatial volume, spatial shape, and spatial projection information;

[0029] Multiple temperature and humidity sensors are set up in different areas of the shooting environment based on spatial parameter information of the shooting environment.

[0030] Set the sampling frequency, acquire temperature data at different time points under water vapor environment based on the sampling frequency, construct temperature change curve, analyze the temperature difference at different time points based on the temperature change curve, and obtain temperature fluctuation data.

[0031] Humidity data at different time points under water vapor environment are obtained based on the acquisition frequency, humidity change curves are constructed, and humidity difference at different time points is analyzed based on the humidity change curves to obtain humidity fluctuation data.

[0032] The environmental parameters of the shooting environment are analyzed based on temperature fluctuation data and humidity fluctuation data. These environmental parameters include temperature parameters, humidity parameters, and fog concentration.

[0033] Optionally, in the industrial visual imaging method applicable to high humidity and water vapor environments described in the embodiments of this application, the captured image is obtained based on an infrared-visible dual-spectrum imaging camera, the brightness values ​​of the captured image pixels are analyzed, and the brightness values ​​are averaged to obtain the average brightness value, specifically including:

[0034] The images are acquired using an infrared-visible dual-spectrum imaging camera, and then grayscale processing is performed on the captured images to obtain grayscale images.

[0035] The grayscale image is divided into multiple sub-regions based on grid partitioning technology;

[0036] The brightness value of each pixel in each sub-region is obtained, and the brightness value of each pixel in each sub-region is averaged to obtain the average brightness value of each sub-region.

[0037] The average brightness of the captured image is obtained by averaging the average brightness values ​​of all sub-regions.

[0038] Optionally, in the industrial visual imaging method applicable to high humidity water vapor environments described in this application embodiment, the analysis of fog concentration information of the shooting environment based on environmental parameters of the shooting environment, and the analysis of interference information on the average brightness based on fog concentration information, specifically includes:

[0039] Analyze the suspension state information of liquid water droplets in the shooting environment based on environmental parameters;

[0040] Analyze the humidity information of the shooting environment based on the suspension state information of liquid water droplets;

[0041] Acquire the temperature information and dew point temperature information of the shooting environment, calculate the difference between the temperature information of the shooting environment and the dew point temperature information, and obtain the dew point temperature difference.

[0042] Fog concentration information is analyzed based on dew point temperature difference, and light source transmittance under shooting conditions is analyzed based on fog concentration information;

[0043] The interference of fog concentration information on the average brightness is analyzed based on the light source transmittance.

[0044] Optionally, in the industrial visual imaging method for high-humidity water vapor environments described in this application embodiment, switching the shooting mode based on interference information and performing dehazing processing on the captured image to obtain a dehazed image specifically includes:

[0045] Obtain interference information, compare the interference information with multiple set interference threshold intervals, and analyze the interference interval in which the interference information is located;

[0046] Based on multiple interference threshold ranges, corresponding interference levels are established, the interference range where the interference information is located is analyzed, and the analysis results are obtained.

[0047] Based on the analysis results, the interference level is obtained by matching the interference information, and the interference level is compared with the set level.

[0048] If the interference level is greater than the set level, the shooting mode is switched to infrared shooting mode, and the captured image is dehazed based on the infrared shooting mode. The shooting mode includes visible light shooting mode and infrared shooting mode.

[0049] If the interference level is less than or equal to the set level, the captured image is deemed to meet the requirements.

[0050] Optionally, in the industrial visual imaging method applicable to high humidity and water vapor environments described in the embodiments of this application, the dehazed image is enhanced to obtain an enhanced image, and the enhanced image is stretched in the digital domain and then histogram equalization is performed to obtain a visual imaging image, specifically including:

[0051] Acquire the enhanced image, calculate the grayscale value of the enhanced image, and analyze the grayscale range based on the grayscale value of the enhanced image;

[0052] Set the stretching ratio to obtain a preset range, expand the grayscale range to the preset range, and obtain the number domain stretching result;

[0053] Based on the number domain stretching results, the number of pixels for each grayscale value is analyzed to obtain a histogram of the number of pixels for each grayscale value;

[0054] Set equalization parameters, iterate through different stretching ratios and equalization parameters, and perform equalization processing on the histogram of the number of pixels of grayscale values ​​based on the stretching ratio and equalization parameters to obtain the visual imaging image.

[0055] Secondly, embodiments of this application provide an industrial vision imaging system suitable for high-humidity water vapor environments. The system includes a memory and a processor. The memory includes a program for an industrial vision imaging method suitable for high-humidity water vapor environments. When the program for the industrial vision imaging method suitable for high-humidity water vapor environments is executed by the processor, it implements the following steps:

[0056] Temperature and humidity fluctuation data under water vapor conditions at different time points are obtained based on temperature and humidity sensors, and environmental parameters of the shooting environment are analyzed based on the temperature and humidity fluctuation data.

[0057] The image is acquired using an infrared-visible dual-spectrum imaging camera. The brightness values ​​of the pixels in the image are analyzed and averaged to obtain the average brightness value.

[0058] Based on the environmental parameters of the shooting environment, analyze the fog concentration information of the shooting environment, and based on the fog concentration information, analyze the interference information on the average brightness.

[0059] The shooting mode is switched based on the interference information, and the captured image is dehazed to obtain a dehazed image;

[0060] The dehazed image is enhanced to obtain an enhanced image. After the enhanced image is stretched in the digital domain, histogram equalization is performed to obtain the visual imaging image.

[0061] Optionally, in the industrial vision imaging system suitable for high-humidity water vapor environments described in this application embodiment, temperature fluctuation data and humidity fluctuation data under water vapor environment at different time points are acquired based on temperature and humidity sensors, and environmental parameters of the shooting environment are analyzed based on the temperature fluctuation data and humidity fluctuation data, specifically including:

[0062] Acquire spatial parameter information of the shooting environment, including spatial volume, spatial shape, and spatial projection information;

[0063] Multiple temperature and humidity sensors are set up in different areas of the shooting environment based on spatial parameter information of the shooting environment.

[0064] Set the sampling frequency, acquire temperature data at different time points under water vapor environment based on the sampling frequency, construct temperature change curve, analyze the temperature difference at different time points based on the temperature change curve, and obtain temperature fluctuation data.

[0065] Humidity data at different time points under water vapor environment are obtained based on the acquisition frequency, humidity change curves are constructed, and humidity difference at different time points is analyzed based on the humidity change curves to obtain humidity fluctuation data.

[0066] The environmental parameters of the shooting environment are analyzed based on temperature fluctuation data and humidity fluctuation data. These environmental parameters include temperature parameters, humidity parameters, and fog concentration.

[0067] Optionally, in the industrial vision imaging system suitable for high humidity environments described in this application embodiment, the captured image is obtained based on an infrared-visible dual-spectrum imaging camera, the brightness values ​​of the captured image pixels are analyzed, and the brightness values ​​are averaged to obtain the average brightness value, specifically including:

[0068] The images are acquired using an infrared-visible dual-spectrum imaging camera, and then grayscale processing is performed on the captured images to obtain grayscale images.

[0069] The grayscale image is divided into multiple sub-regions based on grid partitioning technology;

[0070] The brightness value of each pixel in each sub-region is obtained, and the brightness value of each pixel in each sub-region is averaged to obtain the average brightness value of each sub-region.

[0071] The average brightness of the captured image is obtained by averaging the average brightness values ​​of all sub-regions.

[0072] Thirdly, embodiments of this application also provide a computer-readable storage medium, which includes an industrial vision imaging method program suitable for high humidity environments. When the industrial vision imaging method program suitable for high humidity environments is executed by a processor, it implements the steps of the industrial vision imaging method suitable for high humidity environments as described in any of the above claims.

[0073] As can be seen from the above, the industrial visual imaging method, system, and medium provided in this application embodiment, suitable for high-humidity water vapor environments, acquires temperature and humidity fluctuation data at different time points in a water vapor environment based on temperature and humidity sensors, and analyzes environmental parameters of the shooting environment based on the temperature and humidity fluctuation data; acquires images based on an infrared-visible dual-spectrum imaging camera, analyzes the brightness values ​​of the pixels in the captured images, and performs average processing on the brightness values ​​to obtain a brightness average; analyzes the fog concentration information of the shooting environment based on the environmental parameters of the shooting environment, and analyzes the interference information on the brightness average based on the fog concentration information; switches the shooting mode based on the interference information, and performs dehazing processing on the captured images to obtain a dehazed image; enhances the dehazed image to obtain an enhanced image, stretches the enhanced image in the digital domain, and performs histogram equalization processing to obtain a visual imaging image; adjusts the shooting mode by analyzing the interference information of fog concentration on image brightness, performs dehazing processing on the image, and enhances the image to restore image details and improve recognition capabilities. Attached Figure Description

[0074] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0075] Figure 1 A flowchart of an industrial visual imaging method suitable for high humidity environments provided in this application embodiment;

[0076] Figure 2 A flowchart illustrating the environmental parameter analysis of the shooting environment for an industrial visual imaging method suitable for high humidity environments provided in this application embodiment;

[0077] Figure 3 A flowchart illustrating the brightness mean acquisition method for an industrial visual imaging method suitable for high humidity environments provided in this application embodiment;

[0078] Figure 4 A comparison of the shooting effects of this system and a traditional system for an industrial vision imaging system suitable for high humidity environments, provided in the embodiments of this application. Detailed Implementation

[0079] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0080] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, the terms "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0081] Please refer to Figure 1 , Figure 1This is a flowchart illustrating an industrial visual imaging method suitable for high-humidity environments, as described in some embodiments of this application. This industrial visual imaging method for high-humidity environments is used in a terminal device and includes the following steps:

[0082] S101 acquires temperature and humidity fluctuation data under water vapor conditions at different time points based on temperature and humidity sensors, and analyzes environmental parameters of the shooting environment based on the temperature and humidity fluctuation data.

[0083] S102: Based on the infrared-visible dual-spectrum imaging camera, the captured image is obtained, the brightness value of the captured image pixel is analyzed, and the brightness value is averaged to obtain the average brightness value.

[0084] S103, analyzes the fog concentration information of the shooting environment based on the environmental parameters of the shooting environment, and analyzes the interference information on the average brightness based on the fog concentration information;

[0085] S104, based on interference information, switches the shooting mode and performs dehazing processing on the captured image to obtain a dehazed image;

[0086] S105, the dehazed image is enhanced to obtain an enhanced image. After the enhanced image is stretched in the digital domain, histogram equalization is performed to obtain a visual imaging image.

[0087] It should be noted that by analyzing the fog concentration in the shooting environment, the system determines the interference of fog concentration on image brightness, thereby dynamically switching shooting modes and performing defogging processing on the captured images to reduce fog interference and improve the clarity of the captured images.

[0088] Please refer to Figure 2 , Figure 2 This is a flowchart illustrating the environmental parameter analysis process for an industrial visual imaging method applicable to high-humidity water vapor environments, as described in some embodiments of this application. According to embodiments of the present invention, temperature and humidity fluctuation data under water vapor conditions at different time points are acquired using temperature and humidity sensors. The environmental parameters of the shooting environment are then analyzed based on this temperature and humidity fluctuation data, specifically including:

[0089] S201, acquire spatial parameter information of the shooting environment, including spatial volume, spatial shape and spatial projection information;

[0090] S202 sets up multiple temperature and humidity sensors in different areas of the shooting environment based on spatial parameter information of the shooting environment;

[0091] S203, set the acquisition frequency, acquire temperature data at different time points under water vapor environment based on the acquisition frequency, construct temperature change curve, analyze the temperature difference at different time points based on the temperature change curve, and obtain temperature fluctuation data.

[0092] S204: Based on the acquisition frequency, humidity data at different time points under water vapor environment are acquired, humidity change curves are constructed, and humidity difference at different time points is analyzed based on the humidity change curves to obtain humidity fluctuation data.

[0093] The S205 analyzes environmental parameters of the shooting environment based on temperature and humidity fluctuation data, including temperature, humidity, and fog concentration.

[0094] It should be noted that by setting the collection frequency to obtain temperature and humidity data at different time points, temperature change curves and humidity change curves are obtained, and then the temperature and humidity differences at different time points are accurately analyzed to obtain temperature fluctuation data and humidity fluctuation data.

[0095] Please refer to Figure 3 , Figure 3 This is a flowchart illustrating a method for obtaining the average brightness value in an industrial visual imaging method suitable for high-humidity water vapor environments, as described in some embodiments of this application. According to an embodiment of the present invention, an image is acquired using an infrared-visible dual-spectrum imaging camera, the brightness values ​​of the pixels in the captured image are analyzed, and the brightness values ​​are averaged to obtain the average brightness value. Specifically, this includes:

[0096] S301 acquires images based on an infrared-visible dual-spectrum imaging camera, processes the captured images into grayscale, and obtains grayscale images.

[0097] S301, based on grid partitioning technology, divides a grayscale image into multiple sub-regions;

[0098] S301, obtain the brightness value of the pixel in each sub-region, and perform average value processing on the brightness value of the pixel in each sub-region to obtain the average brightness value of each sub-region.

[0099] S301, calculate the average brightness of the captured image by averaging the average brightness values ​​of all sub-regions.

[0100] It should be noted that the image is divided into M×N sub-regions (e.g., 16×16 pixels); histogram equalization is performed independently on each sub-region; and bilinear interpolation is used to smoothly transition between sub-regions to avoid regional effects.

[0101] According to an embodiment of the present invention, the analysis of fog concentration information of the shooting environment based on environmental parameters of the shooting environment, and the analysis of interference information on the average brightness based on the fog concentration information, specifically includes:

[0102] Analyze the suspension state information of liquid water droplets in the shooting environment based on environmental parameters;

[0103] Analyze the humidity information of the shooting environment based on the suspension state information of liquid water droplets;

[0104] Acquire the temperature information and dew point temperature information of the shooting environment, calculate the difference between the temperature information of the shooting environment and the dew point temperature information, and obtain the dew point temperature difference.

[0105] Fog concentration information is analyzed based on dew point temperature difference, and light source transmittance under shooting conditions is analyzed based on fog concentration information;

[0106] The interference of fog concentration information on the average brightness is analyzed based on the light source transmittance.

[0107] It should be noted that the humidity of the shooting environment is determined by analyzing the suspension state of liquid water, and then the fog concentration is accurately analyzed based on the dew point temperature difference, which in turn accurately analyzes the interference of fog on the brightness of the captured image.

[0108] According to an embodiment of the present invention, switching the shooting mode based on interference information and performing dehazing processing on the captured image to obtain a dehazed image specifically includes:

[0109] Obtain interference information, compare the interference information with multiple set interference threshold intervals, and analyze the interference interval in which the interference information is located;

[0110] Based on multiple interference threshold ranges, corresponding interference levels are established, the interference range where the interference information is located is analyzed, and the analysis results are obtained.

[0111] Based on the analysis results, the interference level is obtained by matching the interference information, and the interference level is compared with the set level.

[0112] If the interference level is greater than the set level, the shooting mode will be switched to infrared shooting mode. The captured image will be dehazed based on the infrared shooting mode. Shooting modes include visible light shooting mode and infrared shooting mode.

[0113] If the interference level is less than or equal to the set level, the captured image is deemed to meet the requirements.

[0114] It should be noted that if there is fog interference, activate infrared illumination (850nm center wavelength) and switch to the infrared imaging channel.

[0115] Activate the front window defogger heating of the camera (power approximately 5W-15W); turn on the infrared LED array and turn off the white light source.

[0116] According to an embodiment of the present invention, the dehazed image is enhanced to obtain an enhanced image. After the enhanced image is stretched in the digital domain, histogram equalization is performed to obtain a visual imaging image. Specifically, this includes:

[0117] Acquire the enhanced image, calculate the grayscale value of the enhanced image, and analyze the grayscale range based on the grayscale value of the enhanced image;

[0118] Set the stretching ratio to obtain a preset range, expand the grayscale range to the preset range, and obtain the number domain stretching result;

[0119] Based on the number domain stretching results, the number of pixels for each grayscale value is analyzed to obtain a histogram of the number of pixels for each grayscale value;

[0120] Set equalization parameters, iterate through different stretching ratios and equalization parameters, and perform equalization processing on the histogram of the number of pixels of grayscale values ​​based on the stretching ratio and equalization parameters to obtain the visual imaging image.

[0121] It should be noted that the image dehazing and enhancement process is as follows:

[0122] Assuming image I(x,y) is the input image, the fog effect model is as follows:

[0123] I(x,y)=J(x,y)·t(x,y)+A(1-t(x,y))

[0124] I(x,y): Observed image;

[0125] J(x,y): Realistic and clear image;

[0126] A: Atmospheric light vector;

[0127] t(x,y): Transmittance, representing the transmittance.

[0128] Transmittance estimation uses a dark channel prior model:

[0129]

[0130] The restored image is:

[0131]

[0132] Where t0 is the lower limit to prevent over-enhancement (generally taken as 0.1).

[0133] The methods for enhancing image details are as follows:

[0134] Employing Laplacian enhancement and Retinex contrast enhancement:

[0135] Define the sharpening enhancement image:

[0136]

[0137] ω represents the weighting coefficient, I c (i,j) represents the pixel value of the c-th channel (R / G / B) at position (i,j) in the input image, A c This represents the atmospheric light value of channel c (R / G / B or infrared channel).

[0138] E(x,y) represents the pixel value of the output image after image enhancement, and represents the brightness of the enhanced image at position (x,y). This represents image gradient operators used for edge detection and image sharpening (such as the Laplacian operator).

[0139] The final image is stretched in the logarithmic domain and then histogram equalization is performed to enhance the edge structure.

[0140] Please refer to Figure 4 , Figure 4 These are comparison images of the imaging effects of an industrial vision imaging system suitable for high humidity environments, as described in some embodiments of this application, and a conventional system. Secondly, embodiments of this application provide an industrial vision imaging system suitable for high humidity environments. This system includes a memory and a processor. The memory includes a program for an industrial vision imaging method suitable for high humidity environments. When executed by the processor, the program for the industrial vision imaging method suitable for high humidity environments implements the following steps:

[0141] Temperature and humidity fluctuation data under water vapor conditions at different time points are obtained based on temperature and humidity sensors, and environmental parameters of the shooting environment are analyzed based on the temperature and humidity fluctuation data.

[0142] The image is acquired using an infrared-visible dual-spectrum imaging camera. The brightness values ​​of the pixels in the image are analyzed and averaged to obtain the average brightness value.

[0143] Based on the environmental parameters of the shooting environment, analyze the fog concentration information of the shooting environment, and based on the fog concentration information, analyze the interference information on the average brightness.

[0144] The shooting mode is switched based on the interference information, and the captured image is dehazed to obtain a dehazed image;

[0145] The dehazed image is enhanced to obtain an enhanced image. After the enhanced image is stretched in the digital domain, histogram equalization is performed to obtain the visual imaging image.

[0146] It should be noted that by analyzing the fog concentration in the shooting environment, the system determines the interference of fog concentration on image brightness, thereby dynamically switching shooting modes and performing defogging processing on the captured images to reduce fog interference and improve the clarity of the captured images.

[0147] According to an embodiment of the present invention, temperature fluctuation data and humidity fluctuation data under a water vapor environment at different time points are acquired based on a temperature and humidity sensor, and environmental parameters of the shooting environment are analyzed based on the temperature fluctuation data and humidity fluctuation data, specifically including:

[0148] Acquire spatial parameter information of the shooting environment, including spatial volume, spatial shape, and spatial projection information;

[0149] Multiple temperature and humidity sensors are set up in different areas of the shooting environment based on spatial parameter information of the shooting environment.

[0150] Set the sampling frequency, acquire temperature data at different time points under water vapor environment based on the sampling frequency, construct temperature change curve, analyze the temperature difference at different time points based on the temperature change curve, and obtain temperature fluctuation data.

[0151] Humidity data at different time points under water vapor environment are obtained based on the acquisition frequency, humidity change curves are constructed, and humidity difference at different time points is analyzed based on the humidity change curves to obtain humidity fluctuation data.

[0152] The environmental parameters of the shooting environment are analyzed based on temperature fluctuation data and humidity fluctuation data. These environmental parameters include temperature parameters, humidity parameters, and fog concentration.

[0153] It should be noted that by setting the collection frequency to obtain temperature and humidity data at different time points, temperature change curves and humidity change curves are obtained, and then the temperature and humidity differences at different time points are accurately analyzed to obtain temperature fluctuation data and humidity fluctuation data.

[0154] According to an embodiment of the present invention, an image is acquired based on an infrared-visible dual-spectrum imaging camera, the brightness values ​​of the pixels in the acquired image are analyzed, and the brightness values ​​are averaged to obtain the average brightness value. Specifically, this includes:

[0155] The images are acquired using an infrared-visible dual-spectrum imaging camera, and then grayscale processing is performed on the captured images to obtain grayscale images.

[0156] The grayscale image is divided into multiple sub-regions based on grid partitioning technology;

[0157] The brightness value of each pixel in each sub-region is obtained, and the brightness value of each pixel in each sub-region is averaged to obtain the average brightness value of each sub-region.

[0158] The average brightness of the captured image is obtained by averaging the average brightness values ​​of all sub-regions.

[0159] It should be noted that the image is divided into M×N sub-regions (e.g., 16×16 pixels); histogram equalization is performed independently on each sub-region; and bilinear interpolation is used to smoothly transition between sub-regions to avoid regional effects.

[0160] According to an embodiment of the present invention, the analysis of fog concentration information of the shooting environment based on environmental parameters of the shooting environment, and the analysis of interference information on the average brightness based on the fog concentration information, specifically includes:

[0161] Analyze the suspension state information of liquid water droplets in the shooting environment based on environmental parameters;

[0162] Analyze the humidity information of the shooting environment based on the suspension state information of liquid water droplets;

[0163] Acquire the temperature information and dew point temperature information of the shooting environment, calculate the difference between the temperature information of the shooting environment and the dew point temperature information, and obtain the dew point temperature difference.

[0164] Fog concentration information is analyzed based on dew point temperature difference, and light source transmittance under shooting conditions is analyzed based on fog concentration information;

[0165] The interference of fog concentration information on the average brightness is analyzed based on the light source transmittance.

[0166] It should be noted that the humidity of the shooting environment is determined by analyzing the suspension state of liquid water, and then the fog concentration is accurately analyzed based on the dew point temperature difference, which in turn accurately analyzes the interference of fog on the brightness of the captured image.

[0167] According to an embodiment of the present invention, switching the shooting mode based on interference information and performing dehazing processing on the captured image to obtain a dehazed image specifically includes:

[0168] Obtain interference information, compare the interference information with multiple set interference threshold intervals, and analyze the interference interval in which the interference information is located;

[0169] Based on multiple interference threshold ranges, corresponding interference levels are established, the interference range where the interference information is located is analyzed, and the analysis results are obtained.

[0170] Based on the analysis results, the interference level is obtained by matching the interference information, and the interference level is compared with the set level.

[0171] If the interference level is greater than the set level, the shooting mode will be switched to infrared shooting mode. The captured image will be dehazed based on the infrared shooting mode. Shooting modes include visible light shooting mode and infrared shooting mode.

[0172] If the interference level is less than or equal to the set level, the captured image is deemed to meet the requirements.

[0173] It should be noted that if there is fog interference, activate infrared illumination (850nm center wavelength) and switch to the infrared imaging channel.

[0174] Activate the front window defogger heating of the camera (power approximately 5W-15W); turn on the infrared LED array and turn off the white light source.

[0175] According to an embodiment of the present invention, the dehazed image is enhanced to obtain an enhanced image. After the enhanced image is stretched in the digital domain, histogram equalization is performed to obtain a visual imaging image. Specifically, this includes:

[0176] Acquire the enhanced image, calculate the grayscale value of the enhanced image, and analyze the grayscale range based on the grayscale value of the enhanced image;

[0177] Set the stretching ratio to obtain a preset range, expand the grayscale range to the preset range, and obtain the number domain stretching result;

[0178] Based on the number domain stretching results, the number of pixels for each grayscale value is analyzed to obtain a histogram of the number of pixels for each grayscale value;

[0179] Set equalization parameters, iterate through different stretching ratios and equalization parameters, and perform equalization processing on the histogram of the number of pixels of grayscale values ​​based on the stretching ratio and equalization parameters to obtain the visual imaging image.

[0180] It should be noted that the image dehazing and enhancement process is as follows:

[0181] Assuming image I(x,y) is the input image, the fog effect model is as follows:

[0182] I(x,y)=J(x,y)·t(x,y)+A(1-t(x,y))

[0183] I(x,y): Observed image;

[0184] J(x,y): Realistic and clear image;

[0185] A: Atmospheric light value;

[0186] t(x,y): Transmittance, representing the transmittance.

[0187] Transmittance estimation uses a dark channel prior model:

[0188]

[0189] The restored image is:

[0190]

[0191] Where t0 is the lower limit to prevent over-enhancement (generally taken as 0.1).

[0192] The methods for enhancing image details are as follows:

[0193] Employing Laplacian enhancement and Retinex contrast enhancement:

[0194] Define the sharpening enhancement image:

[0195] E(x,y)=J(x,y)-▽ 2 J(x,y)

[0196] The final image is stretched in the logarithmic domain and then histogram equalization is performed to enhance the edge structure.

[0197] A third aspect of the present invention provides a computer-readable storage medium including an industrial vision imaging method program suitable for high humidity environments. When the industrial vision imaging method program suitable for high humidity environments is executed by a processor, it implements the steps of the industrial vision imaging method suitable for high humidity environments as described above.

[0198] This invention discloses an industrial visual imaging method, system, and medium suitable for high-humidity water vapor environments. It acquires temperature and humidity fluctuation data at different time points under water vapor conditions using temperature and humidity sensors, and analyzes environmental parameters of the shooting environment based on this data. It then acquires images using an infrared-visible dual-spectrum imaging camera, analyzes the brightness values ​​of the image pixels, and performs average value processing to obtain a brightness average. Based on the environmental parameters of the shooting environment, it analyzes the fog concentration information and its interference with the brightness average. Based on the interference information, it switches the shooting mode and performs dehazing processing on the captured images to obtain a dehazed image. The dehazed image is then enhanced to obtain an enhanced image. After multi-domain stretching, histogram equalization is performed on the enhanced image to obtain a visual imaging image. By analyzing the interference information of fog concentration on image brightness, the shooting mode is adjusted, the image is dehazed, and the image enhancement process restores image details and improves recognition capabilities.

[0199] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.

[0200] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units. They may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs.

[0201] In addition, in the various embodiments of the present invention, each functional unit can be integrated into one processing unit, or each unit can be a separate unit, or two or more units can be integrated into one unit; the integrated unit can be implemented in hardware or in the form of hardware plus software functional units.

[0202] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0203] Alternatively, if the integrated units of the present invention are implemented as software functional modules and sold or used as independent products, they can also be stored in a readable storage medium. Based on this understanding, the technical solutions of the embodiments of the present invention, or the parts that contribute to the prior art, can be embodied in the form of a software product. This software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROM, RAM, magnetic disks, or optical disks.

Claims

1. An industrial visual imaging method suitable for high-humidity water vapor environments, characterized in that, include: Temperature and humidity fluctuation data under water vapor conditions at different time points are obtained based on temperature and humidity sensors, and environmental parameters of the shooting environment are analyzed based on the temperature and humidity fluctuation data. The image is acquired using an infrared-visible dual-spectrum imaging camera. The brightness values ​​of the pixels in the image are analyzed and averaged to obtain the average brightness value. Based on the environmental parameters of the shooting environment, analyze the fog concentration information of the shooting environment, and based on the fog concentration information, analyze the interference information on the average brightness. The shooting mode is switched based on the interference information, and the captured image is dehazed to obtain a dehazed image; The dehazed image is enhanced to obtain an enhanced image. After the enhanced image is stretched in the digital domain, histogram equalization is performed to obtain the visual imaging image.

2. The industrial visual imaging method suitable for high humidity and water vapor environments according to claim 1, characterized in that, Temperature and humidity fluctuation data under water vapor conditions are acquired using temperature and humidity sensors at different time points. Environmental parameters of the shooting environment are analyzed based on this data, specifically including: Acquire spatial parameter information of the shooting environment, including spatial volume, spatial shape, and spatial projection information; Multiple temperature and humidity sensors are set up in different areas of the shooting environment based on spatial parameter information of the shooting environment. Set the sampling frequency, acquire temperature data at different time points under water vapor environment based on the sampling frequency, construct temperature change curve, analyze the temperature difference at different time points based on the temperature change curve, and obtain temperature fluctuation data. Humidity data at different time points under water vapor environment are obtained based on the acquisition frequency, humidity change curves are constructed, and humidity difference at different time points is analyzed based on the humidity change curves to obtain humidity fluctuation data. The environmental parameters of the shooting environment are analyzed based on temperature fluctuation data and humidity fluctuation data. These environmental parameters include temperature parameters, humidity parameters, and fog concentration.

3. The industrial visual imaging method suitable for high-humidity water vapor environments according to claim 2, characterized in that, Based on images acquired using an infrared-visible dual-spectrum imaging camera, the brightness values ​​of the pixels in the captured images are analyzed, and the brightness values ​​are averaged to obtain the average brightness value. Specifically, this includes: The images are acquired using an infrared-visible dual-spectrum imaging camera, and then grayscale processing is performed on the captured images to obtain grayscale images. The grayscale image is divided into multiple sub-regions based on grid partitioning technology; The brightness value of each pixel in each sub-region is obtained, and the brightness value of each pixel in each sub-region is averaged to obtain the average brightness value of each sub-region. The average brightness of the captured image is obtained by averaging the average brightness values ​​of all sub-regions.

4. The industrial visual imaging method suitable for high-humidity water vapor environments according to claim 3, characterized in that, Based on environmental parameters of the shooting environment, analyze the fog concentration information of the shooting environment, and analyze the interference information on the average brightness based on the fog concentration information, specifically including: Analyze the suspension state information of liquid water droplets in the shooting environment based on environmental parameters; Analyze the humidity information of the shooting environment based on the suspension state information of liquid water droplets; Acquire the temperature information and dew point temperature information of the shooting environment, calculate the difference between the temperature information of the shooting environment and the dew point temperature information, and obtain the dew point temperature difference. Fog concentration information is analyzed based on dew point temperature difference, and light source transmittance under shooting conditions is analyzed based on fog concentration information; The interference of fog concentration information on the average brightness is analyzed based on the light source transmittance.

5. The industrial visual imaging method suitable for high-humidity water vapor environments according to claim 4, characterized in that, The shooting mode is switched based on interference information, and the captured image is dehazed to obtain a dehazed image, specifically including: Obtain interference information, compare the interference information with multiple set interference threshold intervals, and analyze the interference interval in which the interference information is located; Based on multiple interference threshold ranges, corresponding interference levels are established, the interference range where the interference information is located is analyzed, and the analysis results are obtained. Based on the analysis results, the interference level is obtained by matching the interference information, and the interference level is compared with the set level. If the interference level is greater than the set level, the shooting mode is switched to infrared shooting mode, and the captured image is dehazed based on the infrared shooting mode. The shooting mode includes visible light shooting mode and infrared shooting mode. If the interference level is less than or equal to the set level, the captured image is deemed to meet the requirements.

6. The industrial visual imaging method suitable for high humidity and water vapor environments according to claim 5, characterized in that, The dehazed image is enhanced to obtain an enhanced image. This enhanced image is then subjected to multi-domain stretching and histogram equalization to obtain the visual image. Specifically, this includes: Acquire the enhanced image, calculate the grayscale value of the enhanced image, and analyze the grayscale range based on the grayscale value of the enhanced image; Set the stretching ratio to obtain a preset range, expand the grayscale range to the preset range, and obtain the number domain stretching result; Based on the number domain stretching results, the number of pixels for each grayscale value is analyzed to obtain a histogram of the number of pixels for each grayscale value; Set equalization parameters, iterate through different stretching ratios and equalization parameters, and perform equalization processing on the histogram of the number of pixels of grayscale values ​​based on the stretching ratio and equalization parameters to obtain the visual imaging image.

7. An industrial vision imaging system suitable for high humidity and water vapor environments, characterized in that, The system includes a memory and a processor. The memory contains a program for an industrial vision imaging method suitable for high humidity environments. When the program for the industrial vision imaging method suitable for high humidity environments is executed by the processor, it performs the following steps: Temperature and humidity fluctuation data under water vapor conditions at different time points are obtained based on temperature and humidity sensors, and environmental parameters of the shooting environment are analyzed based on the temperature and humidity fluctuation data. The image is acquired using an infrared-visible dual-spectrum imaging camera. The brightness values ​​of the pixels in the image are analyzed and averaged to obtain the average brightness value. Based on the environmental parameters of the shooting environment, analyze the fog concentration information of the shooting environment, and based on the fog concentration information, analyze the interference information on the average brightness. The shooting mode is switched based on the interference information, and the captured image is dehazed to obtain a dehazed image; The dehazed image is enhanced to obtain an enhanced image. After the enhanced image is stretched in the digital domain, histogram equalization is performed to obtain the visual imaging image.

8. The industrial vision imaging system suitable for high humidity and water vapor environments according to claim 7, characterized in that, Temperature and humidity fluctuation data under water vapor conditions are acquired using temperature and humidity sensors at different time points. Environmental parameters of the shooting environment are analyzed based on this data, specifically including: Acquire spatial parameter information of the shooting environment, including spatial volume, spatial shape, and spatial projection information; Multiple temperature and humidity sensors are set up in different areas of the shooting environment based on spatial parameter information of the shooting environment. Set the sampling frequency, acquire temperature data at different time points under water vapor environment based on the sampling frequency, construct temperature change curve, analyze the temperature difference at different time points based on the temperature change curve, and obtain temperature fluctuation data. Humidity data at different time points under water vapor environment are obtained based on the acquisition frequency, humidity change curves are constructed, and humidity difference at different time points is analyzed based on the humidity change curves to obtain humidity fluctuation data. The environmental parameters of the shooting environment are analyzed based on temperature fluctuation data and humidity fluctuation data. These environmental parameters include temperature parameters, humidity parameters, and fog concentration.

9. The industrial vision imaging system suitable for high humidity and water vapor environments according to claim 8, characterized in that, Based on images acquired using an infrared-visible dual-spectrum imaging camera, the brightness values ​​of the pixels in the captured images are analyzed, and the brightness values ​​are averaged to obtain the average brightness value. Specifically, this includes: The images are acquired using an infrared-visible dual-spectrum imaging camera, and then grayscale processing is performed on the captured images to obtain grayscale images. The grayscale image is divided into multiple sub-regions based on grid partitioning technology; The brightness value of each pixel in each sub-region is obtained, and the brightness value of each pixel in each sub-region is averaged to obtain the average brightness value of each sub-region. The average brightness of the captured image is obtained by averaging the average brightness values ​​of all sub-regions.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes an industrial vision imaging method program suitable for high humidity environments. When the industrial vision imaging method program suitable for high humidity environments is executed by a processor, it implements the steps of the industrial vision imaging method suitable for high humidity environments as described in any one of claims 1 to 6.

Images