CN113884492A - Ringelmann blackness calibration and detection method and device for motor vehicle exhaust - Google Patents
Ringelmann blackness calibration and detection method and device for motor vehicle exhaust Download PDFInfo
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Abstract
The invention discloses a Lingemann blackness calibration and detection method for motor vehicle exhaust, which comprises the following steps: automatically adjusting the parameters of the camera to be optimal imaging parameters; acquiring N frames of images for each Ringelmann blackness grade pattern, taking the average value of the gray values of the obtained N frames of images as the gray value of the Ringelmann blackness grade pattern, and acquiring the gray value of each Ringelmann blackness grade pattern; establishing a mapping relation between the gray value of each Ringelmann blackness grade pattern and the Ringelmann blackness standard value of the corresponding grade, and constructing a calibration curve according to the mapping relation; collecting M frames of exhaust images to be detected, and calculating the average value of the gray values of the collected M frames of exhaust images to be detected as the gray value of the exhaust images to be detected; and substituting the gray value of the tail gas image to be detected into the calibration curve to obtain the Ringelmann blackness of the tail gas to be detected. The method and the device can realize the on-site real-time calibration of the Ringelmann blackness and can improve the detection precision and accuracy of the Ringelmann blackness.
Description
Technical Field
The invention relates to the field of motor vehicle tail gas detection, in particular to a method and a device for calibrating and detecting the Ringelmann blackness of motor vehicle tail gas.
Background
Tail gas discharged by diesel vehicles and non-road mobile machinery in China is one of important factors causing urban air pollution, and national standards GB3847 and GB36886 respectively make limit value requirements on the black smoke level of the tail gas discharged by the diesel vehicles and the non-road mobile machinery, namely the Ringelmann blackness is required to be less than 1 level. In recent years, the portable detection device for measuring the Rigemann blackness of the tail gas of the diesel vehicle based on image acquisition and identification replaces the traditional subjective visual measurement means, the portable detection device avoids artificial subjective factors, improves the detection accuracy and the detection efficiency, and is widely applied to environment-friendly road inspection law enforcement, home entry supervision and environmental inspection line diesel vehicle detection.
However, the portable detection device finds technical problems of poor measurement repeatability, low detection precision, poor stability and the like in the use process, particularly when the ringelman blackness is 1.00 grade as a judgment threshold, when the ringelman blackness of the tail gas plume detected by the portable detection device is near the 1.00 grade, the tail gas superscript is judged based on the judgment rule, but the judgment of the black smoke by human eyes is fuzzy, so that the probability of low law enforcement reliability and erroneous judgment can occur. The reason for this problem is mainly that the portable detection device is different from the conventional detection device and does not perform effective calibration of the device before use to ensure high accuracy measurement.
The existing JJF 72 measurement standard method adopts a standard Ringelmann blackness plate to calibrate the inspection device, but the method is complicated in manual operation, is only suitable for calibrating the device in an experimental environment and is not suitable for field calibration.
Disclosure of Invention
In view of the above, the present invention provides a lingermann blackness calibration and detection method and apparatus for a motor vehicle exhaust, which can realize on-site real-time calibration of the lingermann blackness and can improve detection accuracy and precision of the lingermann blackness.
In order to achieve the above object, the present invention provides a lingerman blackness calibration and detection method for motor vehicle exhaust, the calibration and detection method being used for a motor vehicle exhaust detection apparatus provided with a camera, the calibration and detection method comprising the steps of:
s1, automatically adjusting the parameters of the camera according to the image quality of the reference pattern in the collected Ringelmann blackness standard plate every time, and setting the adjusted camera parameters as the optimal imaging parameters of the camera when the image quality of the reference pattern meets the preset conditions;
s2, collecting N frames of images for each Ringelmann blackness level pattern on the Ringelmann blackness standard board by using the camera, calculating the gray value of all pixel points of each frame of image, taking the average value of the gray values of the N frames of images obtained by calculation as the gray value of the Ringelmann blackness level pattern, and acquiring the gray value of each Ringelmann blackness level pattern;
s3, establishing a mapping relation between the gray value of each Ringelmann blackness grade pattern and the Ringelmann blackness standard value of the corresponding grade, and establishing a calibration curve according to the mapping relation;
s4, collecting M frames of exhaust images to be detected by the camera, calculating gray values of all pixel points of each frame of exhaust image to be detected, and taking the average value of the gray values of the M frames of exhaust images to be detected as the gray value of the exhaust image to be detected;
and S5, substituting the gray value of the exhaust gas image to be detected into the calibration curve, and performing inversion to obtain the Ringelmann blackness of the exhaust gas to be detected.
Further, the step S1 includes:
collecting reference patterns of the Ringelmann blackness standard plate for multiple times;
calculating the reference pattern acquired each time through a preset image quality evaluation function;
and automatically adjusting camera parameters according to the image quality evaluation parameters obtained by each calculation, and setting the adjusted camera parameters as the optimal imaging parameters of the camera when the calculated image quality evaluation parameters are within a parameter threshold range.
Further, the step of automatically adjusting the camera parameters specifically includes:
adjusting the reference pattern of the Ringelmann blackness standard plate to be within the field range of the camera, and setting the parameters of the camera as first camera parameters, wherein the parameters of the camera comprise a brightness value, a gain value, an exposure value and a gamma value;
acquiring a first reference pattern of the Ringelmann blackness standard plate under a first camera parameter of the camera, calculating an image quality evaluation parameter of the first reference pattern according to the image quality evaluation function, and setting the first camera parameter as an optimal imaging parameter of the camera if the image quality evaluation parameter of the first reference pattern is within the parameter threshold range;
if the image quality evaluation parameter of the second reference pattern is not within the parameter threshold range, adjusting the parameter of the camera to be a second camera parameter according to the image quality evaluation parameter of the first reference pattern, acquiring the second reference pattern of the Ringelmann blackness standard plate under the second camera parameter, obtaining the image quality evaluation parameter of the second reference pattern based on the same calculation method, and if the image quality evaluation parameter of the second reference pattern is within the parameter threshold range, setting the second camera parameter as the optimal imaging parameter of the camera;
and if the image quality evaluation parameter is not in the parameter threshold range, repeatedly executing the steps, and adjusting the camera parameters until the obtained image quality evaluation parameter of the reference pattern is in the parameter threshold range, wherein the camera parameters at the moment are set as the optimal imaging parameters of the camera.
Further, the image quality evaluation parameter Q is calculated by the following image quality evaluation function:
wherein G isx(x, y) and Gy(x, y) are gradient values of pixel points of the image in the horizontal direction and the vertical direction, U and V represent the resolution of the image in the horizontal direction and the vertical direction, alpha and beta are weighting factors respectively, and L is0Is the image dark channel norm.
Further, the step S2 includes:
automatically rotating the Ringelmann blackness standard plate, adjusting each Ringelmann blackness grade pattern in the Ringelmann blackness standard plate to be within the field range of the camera, and carrying out image acquisition on each Ringelmann blackness grade pattern to obtain N frames of images of the Ringelmann blackness grade pattern, wherein the parameters of the camera are set as optimal imaging parameters;
selecting an effective calculation region of each frame of image, extracting R, G, B components of each pixel point in the effective calculation region of each frame of image, and taking the minimum value in R, G, B components of each pixel point as the gray value of the pixel point to obtain the gray value of each pixel point in each frame of image;
counting the number of pixel points corresponding to each gray value in each frame of image, and taking the gray value corresponding to the mode of the pixel points as the gray value of the frame of image;
accumulating and summing the gray values corresponding to each frame of image in the N frames of images and calculating the average value to be used as the gray value of the Ringelmann blackness grade pattern;
and by analogy, the gray value of each Ringelmann blackness grade pattern is obtained.
Further, the step S4 includes:
automatically rotating the Ringelmann blackness standard plate, and positioning a 0.00-level pattern in the Ringelmann blackness standard plate in the field range of the camera, wherein the parameters of the camera are set as optimal imaging parameters;
acquiring a tail gas video to be detected to obtain M frames of tail gas images to be detected;
selecting an effective calculation area of each frame of exhaust image to be detected, extracting R, G, B components of each pixel point in the effective calculation area of each frame of exhaust image to be detected, and taking the minimum value in R, G, B components of each pixel point as the gray value of the pixel point to obtain the gray value of each pixel point in each frame of exhaust image to be detected;
counting the number of pixel points corresponding to each gray value in each frame of exhaust image to be detected, and taking the gray value corresponding to the pixel point mode as the gray value of the frame of exhaust image to be detected;
and accumulating and summing the gray values corresponding to each frame of image in the M exhaust images to be detected, and calculating the average value to be used as the gray value of the exhaust image to be detected.
To achieve the above object, the present invention provides a ringelman blackness calibration and detection apparatus for motor vehicle exhaust, comprising:
a camera;
the standard plate comprises a reference pattern and a plurality of standard Ringelmann blackness grade patterns;
the automatic calibration module is used for collecting N frames of images for each Ringelmann blackness level pattern on the Ringelmann blackness standard plate by using the camera, calculating the gray value of all pixel points of each frame of image, taking the average value of the gray values of the N frames of images obtained by calculation as the gray value of the Ringelmann blackness level pattern, acquiring the gray value of each Ringelmann blackness level pattern, establishing the mapping relation between the gray value of each Ringelmann blackness level pattern and the Ringelmann blackness standard value of the corresponding level, and establishing a calibration curve according to the mapping relation;
the detection module is used for collecting M frames of tail gas images to be detected by the camera, calculating the gray value of all pixel points of each frame of tail gas image to be detected, taking the average value of the gray values of the M frames of tail gas images to be detected as the gray value of the tail gas image to be detected, substituting the gray value of the tail gas image to be detected into the calibration curve, and performing inversion to obtain the Ringelmann blackness of the tail gas to be detected.
Further, the calibration and detection device further comprises a camera parameter adjustment module, the camera parameter adjustment module is used for automatically adjusting the parameters of the camera according to the image quality of the reference pattern in the collected Ringelmann blackness standard plate every time, and when the image quality of the reference pattern meets the preset condition, the adjusted camera parameters are set as the optimal imaging parameters of the camera.
Further, the calibrating and detecting device further comprises a transmission module, and the Lingemann blackness standard plate is arranged on the transmission device and used for moving the Lingemann blackness standard plate.
Further, the calibration and detection device further comprises a positioning device, and each Ringelmann blackness grade pattern in the Ringelmann blackness standard plate is positioned in the field of view of the camera through a control signal output by the positioning device.
Compared with the prior art, the method and the device for calibrating and detecting the Ringelmann blackness of the tail gas of the motor vehicle have the following beneficial effects: the method for calibrating and detecting the Ringelmann blackness is used for automating and intelligentizing the existing method for measuring and calibrating, and can be used for on-site real-time calibration of the Ringelmann blackness; in addition, the tail gas blackness is quantified in a lingermann blackness grade qualitative representation mode while the requirements of 10 grades of lingermann blackness calibration standards are met, and high-precision detection can be realized; the detection error caused by external factors and devices is eliminated, and the accuracy, repeatability and stability of the Ringelmann blackness calibration and detection device and the reliability of environment-friendly law enforcement are improved.
Drawings
FIG. 1 is a schematic flow diagram of a Lingemann blackness calibration and detection method for motor vehicle exhaust in accordance with an embodiment of the present invention;
FIG. 2 is a schematic illustration of a ringer Mannheim standard plate according to an embodiment of the present invention;
FIG. 3 is a schematic illustration of a calibration curve in accordance with an embodiment of the present invention;
FIG. 4 is a system diagram of a ringer Mannheim calibration and detection apparatus for motor vehicle exhaust in accordance with an embodiment of the present invention.
Detailed Description
The present invention will be described in detail with reference to the specific embodiments shown in the drawings, which are not intended to limit the present invention, and structural, methodological, or functional changes made by those skilled in the art according to the specific embodiments are included in the scope of the present invention.
According to the method, the gray value of each Ringelmann blackness grade pattern on the Ringelmann blackness standard plate is calculated, the mapping relation between the gray value of each Ringelmann blackness grade pattern and the Ringelmann blackness standard value of the corresponding grade is established, the calibration curve is established according to the mapping relation, the calculated gray value of the to-be-detected tail gas image is substituted into the calibration curve, and the Ringelmann blackness of the to-be-detected tail gas is obtained through inversion, so that the Ringelmann blackness grade of the to-be-detected tail gas is obtained, the on-site real-time calibration of the Ringelmann blackness can be realized, and the detection precision and accuracy of the Ringelmann blackness can be improved.
In one embodiment of the present invention as shown in fig. 1, the present invention provides a lingermann blackness calibration and detection method for motor vehicle exhaust, the calibration and detection method being used in a motor vehicle exhaust detection device, a camera being provided in the motor vehicle exhaust detection device, the calibration and detection method comprising the steps of:
s1, automatically adjusting the parameters of the camera according to the image quality of the reference pattern in the collected Ringelmann blackness standard plate every time, and setting the adjusted camera parameters as the optimal imaging parameters of the camera when the image quality of the reference pattern meets the preset conditions;
s2, collecting N frames of images for each Ringelmann blackness level pattern on the Ringelmann blackness standard board by using the camera, calculating the gray value of all pixel points of each frame of image, taking the average value of the gray values of the N frames of images obtained by calculation as the gray value of the Ringelmann blackness level pattern, and acquiring the gray value of each Ringelmann blackness level pattern;
s3, establishing a mapping relation between the gray value of each Ringelmann blackness grade pattern and the Ringelmann blackness standard value of the corresponding grade, and establishing a calibration curve according to the mapping relation;
s4, collecting M frames of exhaust images to be detected by the camera, calculating gray values of all pixel points of each frame of exhaust image to be detected, and taking the average value of the gray values of the M frames of exhaust images to be detected as the gray value of the exhaust image to be detected;
and S5, substituting the gray value of the exhaust gas image to be detected into the calibration curve, and performing inversion to obtain the Ringelmann blackness of the exhaust gas to be detected.
And automatically adjusting the parameters of the camera according to the image quality of the reference pattern in the Ringelmann blackness standard plate acquired every time, and setting the adjusted parameters of the camera as the optimal imaging parameters of the camera when the image quality of the reference pattern meets the preset conditions. As an implementation mode of the invention, the reference pattern of the Ringelmann blackness standard plate is acquired for multiple times, the acquired reference pattern is calculated for each time through a preset image quality evaluation function, the camera parameters are automatically adjusted according to the image quality evaluation parameters obtained by each time of calculation, and when the image quality evaluation parameters obtained by calculation are within a parameter threshold range, the adjusted camera parameters are set as the optimal imaging parameters of the camera. A schematic diagram of the ringelman blackness standard plate shown in fig. 2. The two ends of the Ringelmann blackness standard plate are rotating shafts, patterns with different blackness grids are distributed in the standard plate, the Ringelmann blackness standard plate comprises 11 images, black and white reference patterns and 10 grades of Ringelmann blackness standard patterns are respectively arranged from left to right, and the 10 grades of Ringelmann blackness standard patterns correspond to 0.00 grade patterns, 0.75 grade patterns, 1 grade patterns, 1.25 grade patterns, 1.50 grade patterns, 1.75 grade patterns, 2.00 grade patterns, 3.00 grade patterns, 4.00 grade patterns and 5.00 grade patterns. And adjusting the reference pattern of the ringer Mannheim standard plate to be within a field range of a camera in the motor vehicle exhaust detection device, wherein the parameters of the camera are set as first camera parameters, and the camera parameters comprise a brightness value, a gain value, an exposure value and a gamma value. Automatically shooting the reference pattern through the camera under the condition of a first camera parameter, acquiring a first reference pattern, calculating the first reference pattern through an image quality evaluation function to obtain an image quality evaluation parameter of the first reference pattern, taking the first camera parameter as an optimal imaging parameter of the camera if the image quality evaluation parameter of the first reference pattern is within a parameter threshold range, adjusting the camera parameter as a second camera parameter if the image quality evaluation parameter of the first reference pattern is not within the parameter threshold range, acquiring a second reference pattern under the condition of the second camera parameter, calculating the second reference pattern through the image quality evaluation function to obtain an image quality evaluation parameter of the second reference pattern, and if the image quality evaluation parameter of the second reference pattern is within the parameter threshold range, and taking the second camera parameter as the optimal imaging parameter of the camera, if not, repeating the iteration of the steps until the image quality evaluation parameter of the obtained reference pattern is within the parameter threshold value range, and taking the camera parameter at the moment as the optimal imaging parameter of the camera. The optimal imaging quality is realized by adjusting the camera parameters, the detection errors caused by ambient light and temperature and long-term attenuation of electronic devices are eliminated, and the calibration and detection consistency and stability of the tail gas detection device are favorably improved.
As an implementation of the present invention, the image quality evaluation parameter Q is calculated by the following image quality evaluation function:
wherein G isx(x, y) and Gy(x, y) are gradient values of pixel points of the image in the horizontal direction and the vertical direction, U and V represent the resolution of the image in the horizontal direction and the vertical direction, alpha and beta are weighting factors respectively, and L is0Is the image dark channel norm.
And collecting N frames of images for each Ringelmann blackness grade pattern on the Ringelmann blackness standard plate by using a camera, calculating the gray value of all pixel points of each frame of image, taking the average value of the gray values of the N frames of images obtained by calculation as the gray value of the Ringelmann blackness grade pattern, and obtaining the gray value of each Ringelmann blackness grade pattern. Specifically, the ringer man blackness standard plate is automatically rotated, each ringer man blackness level pattern in the ringer man blackness standard plate is adjusted to be within a field range of a camera, parameters of the camera are set to be optimal imaging parameters, video stream collection is carried out on each ringer man blackness level pattern, and each ringer man blackness level pattern correspondingly collects N frames of images. The effective calculation area of each frame image is selected, and is generally set to be 90% of the area of the frame image. Extracting R, G, B components of each pixel point in the effective calculation area of each frame of image, taking the minimum value in R, G, B components of each pixel point as the gray value of the pixel point to obtain the gray value of each pixel point in each frame of image, performing statistical analysis on the pixel number corresponding to the gray value of each frame of image, counting the pixel number corresponding to each gray value, taking the gray value corresponding to the mode of the pixel points as the gray value of the frame of image, accumulating and summing the gray values corresponding to each frame of image in the N frames of image, performing mean value calculation to obtain the average value of the gray values, and taking the average value as the gray value of the Ringelmann blackness level pattern. And by analogy, obtaining the gray value corresponding to each Ringelmann blackness grade pattern.
And establishing a mapping relation between the gray value of each Ringelmann blackness grade pattern and the Ringelmann blackness standard value of the corresponding grade, and establishing a calibration curve according to the mapping relation. The gray scale values of the 10-level Ringelmann blackness pattern correspond to 10 gray scale values recorded as X0.00、X0.75、X1、X1.25、X1.50、X1.75、X2.00、X3.00、X4.00、X5.00. The 10 levels of the lingemann blackness standard values are respectively 0.00, 0.75, 1, 1.25, 1.50, 1.75, 2.00, 3.00, 4.00 and 5.00, the mapping relation between the gray value of each corresponding level of the lingemann blackness level pattern and the lingemann blackness standard value is respectively constructed, and a calibration curve is constructed through the mapping relation.The calibration curve may be a non-linear curve or may be a piecewise curve. As shown in fig. 3, the calibration curve of an embodiment is shown in fig. 3, in which the camera acquires an image with 30FPS, acquires 60 pictures within 2 seconds, obtains the gray value distribution of each lingermann black level pattern by the calculation method of the present invention, and obtains the calibration curve graph 3.
And collecting M frames of exhaust images to be detected by using a camera, performing gray value calculation on all pixel points of each frame of exhaust image to be detected, and taking the average value of the gray values of the M frames of exhaust images to be detected as the gray value of the exhaust image to be detected. And automatically rotating the Ringelmann blackness standard plate, positioning the 0.00-level patterns in the Ringelmann blackness standard plate in the field range of the camera, and setting the parameters of the camera as the optimal imaging parameters. Shooting a video of the tail gas to be detected through a camera, and performing single-frame separation on the shot tail gas to be detected video to obtain M frames of tail gas images to be detected. And selecting an effective calculation area of each frame of the exhaust gas image to be detected, wherein the effective calculation area is generally set to be 90% of the whole frame of the image. And extracting R, G, B components of each pixel point in the effective calculation area of each frame of exhaust image to be detected, and taking the minimum value in R, G, B components of each pixel point as the gray value of the pixel point to obtain the gray value of each pixel point of each frame of exhaust image to be detected. And performing statistical analysis on the pixel number corresponding to the gray value of each frame of the tail gas image to be detected, counting the pixel number corresponding to each gray value, taking the gray value corresponding to the pixel number as the gray value of the frame of the tail gas image to be detected, accumulating and summing the gray values corresponding to each frame of the image in the M frames of the tail gas image to be detected, and performing average calculation to obtain the average value of the gray values as the gray value of the tail gas image to be detected.
And substituting the gray value of the tail gas image to be detected into the calibration curve, and performing inversion to obtain the Ringelmann blackness of the tail gas to be detected. And substituting the gray value of the tail gas image to be detected into the calibration curve according to the mapping relation between the gray value of each Ringelmann blackness grade pattern in the calibration curve and the Ringelmann blackness standard value to obtain the Ringelmann blackness of the tail gas to be detected, and further obtaining the Ringelmann blackness grade of the tail gas to be detected.
In one embodiment of the present invention, as shown in fig. 4, the present invention provides a ringelman blackness detection and calibration apparatus for motor vehicle exhaust, the detection and calibration apparatus comprising:
a camera 40;
a ringer Mannheim standard board 41 including a reference pattern and a plurality of standard ringer Mannheim level patterns;
the automatic calibration module 42 is configured to collect N frames of images for each lingemann blackness level pattern on the lingemann blackness standard plate by using a camera, calculate gray values of all pixel points of each frame of image, use an average value of the gray values of the N frames of images obtained by calculation as a gray value of the lingemann blackness level pattern, obtain a gray value of each lingemann blackness level pattern, establish a mapping relationship between the gray value of each lingemann blackness level pattern and a lingemann blackness standard value of a corresponding level, and establish a calibration curve by using the mapping relationship;
the detection module 43 collects M frames of images of the exhaust to be detected by using the camera, performs gray value calculation on all pixel points of each frame of image of the exhaust to be detected, uses the average value of the gray values of the M frames of images of the exhaust to be detected as the gray value of the image of the exhaust to be detected, substitutes the gray value of the image of the exhaust to be detected into the calibration curve, and performs inversion to obtain the lingermann blackness of the exhaust to be detected.
The ringer man blackness detection and calibration device for motor vehicle exhaust comprises a camera, a ringer man blackness standard plate, an automatic calibration module and a detection module. The Lingemann blackness standard plate comprises 11 pictures, wherein black and white reference patterns and 10 grades of Lingemann blackness standard patterns are respectively arranged from left to right, and the 10 grades of Lingemann blackness standard patterns correspond to 0.00 grade patterns, 0.75 grade patterns, 1 grade patterns, 1.25 grade patterns, 1.50 grade patterns, 1.75 grade patterns, 2.00 grade patterns, 3.00 grade patterns, 4.00 grade patterns and 5.00 grade patterns.
As an implementation manner of the present invention, the calibration and detection apparatus further includes a camera parameter adjustment module, which automatically adjusts parameters of the camera according to the image quality of the reference pattern in the ringelman blackness standard board acquired each time, and sets the adjusted camera parameters as the optimal imaging parameters of the camera when the image quality of the reference pattern meets a preset condition.
As an implementation manner of the present invention, the calibration and detection device further includes a transmission device, and the lingemann blackness standard plate is disposed on the transmission device and used for moving the lingemann blackness standard plate. The transmission means is for example a belt. The calibration and detection device further comprises a positioning device, and each Ringelmann blackness grade pattern in the Ringelmann blackness standard plate is positioned in the same view field range of the camera through a control signal output by the positioning device. The positioning device is for example a positioning sensor.
Setting parameters of a camera as optimal imaging parameters, driving a Ringelmann blackness standard board by a transmission device, positioning each Ringelmann blackness grade pattern in the same field range of the camera by a positioning device, shooting each Ringelmann blackness grade pattern by the camera, collecting N frames of images by each Ringelmann blackness grade pattern in total, calculating gray values of all pixel points of each frame of image, selecting an effective calculation area of each frame of image, extracting R, G, B components of each pixel point in the effective calculation area of each frame of image, and taking the minimum value in R, G, B components of each pixel point as the gray value of the pixel point to obtain the gray value of each pixel point in each frame of image. And counting the number of pixel points corresponding to each gray value in each frame of image, and taking the gray value corresponding to the mode of the pixel points as the gray value of the frame of image. And accumulating and summing the gray values corresponding to each frame of image in the N frames of images, and calculating the average value to be used as the gray value of the Ringelmann blackness grade pattern. And establishing a mapping relation between the gray value of each Ringelmann blackness grade pattern and the Ringelmann blackness standard value of the corresponding grade, and establishing a calibration curve according to the mapping relation.
Setting parameters of a camera as optimal imaging parameters, driving a ringer Mannesmia standard plate by a transmission device, positioning 0.00-level patterns in the ringer Mannesmia standard plate in a field range of the camera by a positioning device, acquiring M frames of exhaust gas images to be detected by collecting exhaust gas videos to be detected, selecting an effective calculation area of each frame of exhaust gas images to be detected, extracting R, G, B components of each pixel point in the effective calculation area of each frame of exhaust gas images to be detected, acquiring a gray value of each pixel point in each frame of exhaust gas images to be detected by taking the minimum value in R, G, B components of each pixel point as the gray value of the pixel point, counting the number of the pixel points corresponding to each gray value in each frame of exhaust gas images to be detected, taking the gray value corresponding to the mode of the pixel points as the gray value of the exhaust gas images to be detected, accumulating and carrying out mean value calculation on the gray values corresponding to each frame of images in the M exhaust gas images to be detected, substituting the gray value of the tail gas image to be detected into the calibration curve as the gray value of the tail gas image to be detected, and performing inversion to obtain the Ringelmann blackness of the tail gas to be detected so as to obtain the Ringelmann blackness grade of the tail gas to be detected.
Although the preferred embodiments of the present invention have been disclosed for illustrative purposes, those skilled in the art will appreciate that various modifications, additions and substitutions are possible, without departing from the scope and spirit of the invention as disclosed in the accompanying claims.
Claims (10)
1. A ringelman blackness calibration and detection method for motor vehicle exhaust, the calibration and detection method being used in a motor vehicle exhaust detection device having a camera disposed therein, the calibration and detection method comprising the steps of:
s1, automatically adjusting the parameters of the camera according to the image quality of the reference pattern in the collected Ringelmann blackness standard plate every time, and setting the adjusted camera parameters as the optimal imaging parameters of the camera when the image quality of the reference pattern meets the preset conditions;
s2, collecting N frames of images for each Ringelmann blackness level pattern on the Ringelmann blackness standard board by using the camera, calculating the gray value of all pixel points of each frame of image, taking the average value of the gray values of the N frames of images obtained by calculation as the gray value of the Ringelmann blackness level pattern, and acquiring the gray value of each Ringelmann blackness level pattern;
s3, establishing a mapping relation between the gray value of each Ringelmann blackness grade pattern and the Ringelmann blackness standard value of the corresponding grade, and establishing a calibration curve according to the mapping relation;
s4, collecting M frames of exhaust images to be detected by the camera, calculating gray values of all pixel points of each frame of exhaust image to be detected, and taking the average value of the gray values of the M frames of exhaust images to be detected as the gray value of the exhaust image to be detected;
and S5, substituting the gray value of the exhaust gas image to be detected into the calibration curve, and performing inversion to obtain the Ringelmann blackness of the exhaust gas to be detected.
2. The ringer Mannheim calibration and detection method for motor vehicle exhaust, according to claim 1, wherein the step S1 includes:
collecting reference patterns of the Ringelmann blackness standard plate for multiple times;
calculating the reference pattern acquired each time through a preset image quality evaluation function;
and automatically adjusting camera parameters according to the image quality evaluation parameters obtained by each calculation, and setting the adjusted camera parameters as the optimal imaging parameters of the camera when the calculated image quality evaluation parameters are within a parameter threshold range.
3. The ringelmann blackness calibration and detection method for motor vehicle exhaust of claim 2, wherein the step of automatically adjusting camera parameters specifically comprises:
adjusting the reference pattern of the Ringelmann blackness standard plate to be within the field range of the camera, and setting the parameters of the camera as first camera parameters, wherein the parameters of the camera comprise a brightness value, a gain value, an exposure value and a gamma value;
acquiring a first reference pattern of the Ringelmann blackness standard plate under a first camera parameter of the camera, calculating an image quality evaluation parameter of the first reference pattern according to the image quality evaluation function, and setting the first camera parameter as an optimal imaging parameter of the camera if the image quality evaluation parameter of the first reference pattern is within the parameter threshold range;
if the image quality evaluation parameter of the second reference pattern is not within the parameter threshold range, adjusting the parameter of the camera to be a second camera parameter according to the image quality evaluation parameter of the first reference pattern, acquiring the second reference pattern of the Ringelmann blackness standard plate under the second camera parameter, obtaining the image quality evaluation parameter of the second reference pattern based on the same calculation method, and if the image quality evaluation parameter of the second reference pattern is within the parameter threshold range, setting the second camera parameter as the optimal imaging parameter of the camera;
and if the image quality evaluation parameter is not in the parameter threshold range, repeatedly executing the steps, and adjusting the camera parameters until the obtained image quality evaluation parameter of the reference pattern is in the parameter threshold range, wherein the camera parameters at the moment are set as the optimal imaging parameters of the camera.
4. The ringer Mannheim calibration and detection method for motor vehicle exhaust as claimed in claim 3, wherein the image quality evaluation parameter Q is calculated by an image quality evaluation function of:
wherein G isx(x, y) and Gy(x, y) are gradient values of pixel points of the image in the horizontal direction and the vertical direction, U and V represent the resolution of the image in the horizontal direction and the vertical direction, alpha and beta are weighting factors respectively, and L is0Is the image dark channel norm.
5. The ringer Mannheim calibration and detection method for motor vehicle exhaust as set forth in claim 2, wherein the step S2 comprises:
automatically rotating the Ringelmann blackness standard plate, adjusting each Ringelmann blackness grade pattern in the Ringelmann blackness standard plate to be within the field range of the camera, and carrying out image acquisition on each Ringelmann blackness grade pattern to obtain N frames of images of the Ringelmann blackness grade pattern, wherein the parameters of the camera are set as optimal imaging parameters;
selecting an effective calculation region of each frame of image, extracting R, G, B components of each pixel point in the effective calculation region of each frame of image, and taking the minimum value in R, G, B components of each pixel point as the gray value of the pixel point to obtain the gray value of each pixel point in each frame of image;
counting the number of pixel points corresponding to each gray value in each frame of image, and taking the gray value corresponding to the mode of the pixel points as the gray value of the frame of image;
accumulating and summing the gray values corresponding to each frame of image in the N frames of images and calculating the average value to be used as the gray value of the Ringelmann blackness grade pattern;
and by analogy, the gray value of each Ringelmann blackness grade pattern is obtained.
6. The ringer Mannheim calibration and detection method for motor vehicle exhaust, according to claim 5, wherein the step S4 includes:
automatically rotating the Ringelmann blackness standard plate, and positioning a 0.00-level pattern in the Ringelmann blackness standard plate in the field range of the camera, wherein the parameters of the camera are set as optimal imaging parameters;
acquiring a tail gas video to be detected to obtain M frames of tail gas images to be detected;
selecting an effective calculation area of each frame of exhaust image to be detected, extracting R, G, B components of each pixel point in the effective calculation area of each frame of exhaust image to be detected, and taking the minimum value in R, G, B components of each pixel point as the gray value of the pixel point to obtain the gray value of each pixel point in each frame of exhaust image to be detected;
counting the number of pixel points corresponding to each gray value in each frame of exhaust image to be detected, and taking the gray value corresponding to the pixel point mode as the gray value of the frame of exhaust image to be detected;
and accumulating and summing the gray values corresponding to each frame of image in the M exhaust images to be detected, and calculating the average value to be used as the gray value of the exhaust image to be detected.
7. A ringelman blackness calibration and detection apparatus for motor vehicle exhaust, the calibration and detection apparatus comprising:
a camera;
the standard plate comprises a reference pattern and a plurality of standard Ringelmann blackness grade patterns;
the automatic calibration module is used for collecting N frames of images for each Ringelmann blackness level pattern on the Ringelmann blackness standard plate by using the camera, calculating the gray value of all pixel points of each frame of image, taking the average value of the gray values of the N frames of images obtained by calculation as the gray value of the Ringelmann blackness level pattern, acquiring the gray value of each Ringelmann blackness level pattern, establishing the mapping relation between the gray value of each Ringelmann blackness level pattern and the Ringelmann blackness standard value of the corresponding level, and establishing a calibration curve according to the mapping relation;
the detection module is used for collecting M frames of tail gas images to be detected by the camera, calculating gray values of all pixel points of each frame of tail gas images to be detected, taking the average value of the gray values of the M frames of tail gas images to be detected as the gray value of the tail gas images to be detected, substituting the gray value of the tail gas images to be detected into the calibration curve, and performing inversion to obtain the Ringelmann blackness of the tail gas to be detected.
8. The ringelman blackness calibration and detection apparatus for a motor vehicle exhaust as claimed in claim 7, wherein the calibration and detection apparatus further comprises a camera parameter adjustment module for automatically adjusting parameters of the camera according to the image quality of the reference pattern in the ringelman blackness standard board acquired each time, and setting the adjusted camera parameters as optimal imaging parameters of the camera when the image quality of the reference pattern meets a preset condition.
9. The ringer Mannheim calibration and detection apparatus for a motor vehicle exhaust as recited in claim 8, further comprising a drive module, wherein the ringer Mannheim standard plate is disposed on the drive assembly for moving the ringer Mannheim standard plate.
10. The ringelmann blackness calibration and detection apparatus for motor vehicle exhaust of claim 9, wherein the calibration and detection apparatus further comprises a positioning means for positioning each of the ringelmann blackness level patterns in the ringelmann blackness standard panel within a field of view of the camera by a control signal output from the positioning means.
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