CN110493595B - Camera detection method and device, storage medium and electronic device - Google Patents
Camera detection method and device, storage medium and electronic device Download PDFInfo
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Abstract
The invention discloses a camera detection method and device, a storage medium and an electronic device. Wherein, the method comprises the following steps: acquiring a first image obtained by shooting a test card by a target camera, wherein the test card comprises a standard test card, a chromaticity test card and a gray level test card; identifying the standard test card in the first image, and identifying the chromaticity test card and the gray scale test card through the standard test card; determining the target image quality characteristic of the first image according to the standard test card, the chromaticity test card and the gray scale test card; the imaging quality detection result of the first image is determined according to the target image quality characteristic and the predetermined image quality standard, so that the technical problem of how to evaluate the imaging quality of the camera under the condition of monitoring the complex background scene in the prior art is solved, and the detection of the imaging quality of the camera under the complex background is realized.
Description
Technical Field
The invention relates to the field of computers, in particular to a detection method and device of a camera, a storage medium and an electronic device.
Background
The camera captures scene information through the photosensitive element at the front end, and different camera parameters can directly influence the imaging effect of the camera. The existing algorithm for evaluating the imaging quality of the camera takes a test card as a main part, and the image information in the test card can be obtained by positioning and analyzing the test card in front of the lens and converted into the parameter information of the camera through a related algorithm.
The existing test card evaluation scheme is basically only for a self-shooting camera, and because the self-shooting camera has higher requirement on imaging quality and is closer to a shooting object, the detail information of the test card is better captured. In a monitoring scene, the camera is far away from a target object, so that the positioning difficulty of the test card is high, and the detailed information is difficult to capture, so that the matched technical scheme is less.
In view of the above problems, no effective solution has been proposed.
Disclosure of Invention
The embodiment of the invention provides a detection method and device of a camera, a storage medium and an electronic device, and at least solves the technical problem of how to evaluate the imaging quality of the camera in the monitoring of a complex background scene in the prior art.
According to an aspect of the embodiments of the present invention, there is also provided a method for detecting a camera, including:
acquiring a first image obtained by shooting a test card by a target camera, wherein the test card comprises a standard test card, a chromaticity test card and a gray level test card;
identifying the standard test card in the first image, and identifying the chromaticity test card and the gray scale test card through the standard test card;
determining the target image quality characteristic of the first image according to the standard test card, the chromaticity test card and the gray scale test card;
and determining the imaging quality detection result of the first image according to the target image quality characteristic and a predetermined image quality standard.
According to another aspect of the embodiments of the present invention, there is also provided a detection apparatus for a camera, including:
the device comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring a first image obtained by shooting a test card by a target camera, and the test card comprises a standard test card, a chromaticity test card and a gray level test card;
the identification module is used for identifying the standard test card in the first image and identifying the chromaticity test card and the gray scale test card through the standard test card;
the first determining module is used for determining the target image quality characteristic of the first image according to the standard test card, the chromaticity test card and the gray scale test card;
and the second determining module is used for determining the imaging quality detection result of the first image according to the target image quality characteristic and a predetermined image quality standard.
According to another aspect of the embodiments of the present invention, there is also provided a computer-readable storage medium, in which a computer program is stored, where the computer program is configured to execute the detection method of the camera when running.
According to another aspect of the embodiments of the present invention, there is also provided an electronic apparatus, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the method for detecting the camera by using the computer program.
In the embodiment of the invention, the standard test card is used for positioning and identifying the standard test card, the chromaticity test card and the gray scale test card are identified according to the standard test card, and the image quality characteristics are determined according to the standard test card, the chromaticity test card and the gray scale test card, so that the imaging quality of the camera is evaluated, the positioning of the test card can be rapidly completed under complex backgrounds such as indoor, outdoor, over-bright and over-dark, the imaging quality of the camera can be detected under the complex background, and the problem of how to evaluate the imaging quality of the camera under the complex background scene monitoring in the prior art can be solved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
FIG. 1 is a schematic diagram of an image quality testing system according to an embodiment of the present invention;
fig. 2 is a flowchart of a detection method of a camera according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a test card according to an embodiment of the present invention;
FIG. 4 is a flow diagram of image feature extraction according to an embodiment of the invention;
FIG. 5 is a flow chart of test card positioning according to an embodiment of the present invention;
FIG. 6 is a diagram illustrating binding of test card power to a human face, according to an embodiment of the invention;
fig. 7 is a block diagram of a detection apparatus of a camera according to an embodiment of the present invention;
fig. 8 is a first block diagram of a detection device of a camera according to a preferred embodiment of the invention;
FIG. 9 is a block diagram II of a detection device of a camera according to a preferred embodiment of the present invention;
fig. 10 is a schematic structural diagram of an alternative electronic device according to an embodiment of the invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in other sequences than those illustrated or described herein. Moreover, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Fig. 1 is a schematic diagram of an image quality testing system according to an embodiment of the present invention, such as fig. 1, an image quality testing system 10 for testing the imaging quality of an image capturing device 20, including an image display device 1, a display control device 2, a test card selection device 3, and an image quality analyzing device 4;
an image display device 1 for displaying digital test cards, which can display desired test cards in a single body or in an array;
the display control device 2 is used for controlling the display state of the image display device 1, for example, controlling the display of the digital test card in the image display device 1, and adjusting the brightness, saturation, contrast, specific gray scale and the like of the image display device 1, and is not exhaustive, and the device is used for replacing an illumination facility in the conventional paper test card, providing a set shooting environment for the image acquisition device 20 during shooting, and measuring various image quality parameters of the image acquisition device 20 without replacing the device;
the test card selecting device 3 is used for controlling and replacing the digital test card, namely switching the display picture of the image display device 1, and of course, the test card selecting device 3 comprises a storage medium, the test cards with different parameters are stored in the storage medium, and when a certain test card needs to be switched, the test card selecting device 3 searches the test card and provides the address of the test card in the storage medium for the image display device 4 or the display control device 2 to read;
the image quality analysis device 4 is used for analyzing the image shot by the image acquisition device 20 to obtain the parameters of the shot image so as to obtain the shooting quality of the image acquisition device 20;
after the image capturing device 20 captures the display screen of the image display device 1, the captured image is sent to the image quality analyzing device 4 for analysis, so as to determine the imaging quality.
In an embodiment of the present invention, the image display device 1 includes a tablet computer, a portable computer, a display screen, or the like.
In one embodiment of the present invention, in order to obtain a more accurate test result, the image quality analyzer 4 may analyze the image acquired by the image capturing device 20, and determine whether or not the accuracy of the test result and the test card are suitable for the image capturing device 1.
Based on the above framework, an embodiment of the present invention provides a method for detecting a camera, and fig. 2 is a flowchart of the method for detecting a camera according to the embodiment of the present invention, as shown in fig. 2, including the following steps:
step S202, acquiring a first image obtained by shooting a test card by a target camera, wherein the test card comprises a standard test card, a chromaticity test card and a gray level test card;
in a specific implementation, the first image may be captured by an image capturing device such as a camera, and the number of captured first images is not fixed. The number of first images acquired may be different in different application scenarios.
The test card in the embodiment of the invention can adopt a digital test card or a paper test card, when the test card is a digital test card, the display state of the image display device and the displayed test card picture are controlled by the display control device and the test card selection device, namely, the image display device displays the digital test card with various parameters under the set environments of brightness, gray scale and the like, so that the image acquisition device can shoot various images under different environments to obtain the shooting quality of the digital test card.
Step S204, identifying the standard test card in the first image, and identifying the chromaticity test card and the gray scale test card through the standard test card;
specifically, the step S204 may specifically include:
positioning a standard test card in the first image, wherein the standard test card comprises information capable of being positioned so as to determine the position of the standard test card and identify the standard test card; for example, the standard test card is a two-dimensional code, and the following description will be given by taking the standard test card as the two-dimensional code as an example to position the standard test card and identify the standard test card.
Firstly, locating angular points of three corners of the two-dimensional code are searched, smooth filtering and binarization are carried out on a first image, a contour is searched, the characteristics of two sub-contours in the contour are screened, and 3 locating angular points which are two-dimensional codes and have the closest areas are found from the screened contour. And judging the position of the 3 corner points, mainly used for carrying out perspective correction on the first image, judging the point of the upper left corner of the two-dimensional code of the maximum corner technology of the triangle surrounded by the 3 corner points, then determining the lower left position and the upper right position of the other two intersection points according to the angle difference of the two called sides, and identifying the range of the two-dimensional code according to the feature.
Specifically, the distance between the standard test card and the chromaticity test card and the distance between the standard test card and the gray scale test card in the test card are fixed, for example, in the test card, the chromaticity test card is positioned 2cm above the standard test card, the gray scale test card is positioned 2cm below the standard test card, and the chromaticity test card and the gray scale test card are identified from the positions of the chromaticity test card and the gray scale test card according to the ratio of the size of the test card to the actual size of the test card in the shot image, so that the positions of the chromaticity test card and the gray scale test card can be determined according to the position of the standard test card in the first image, and the chromaticity test card and the gray scale test card can be identified.
Further, when the position of the standard test card in the test card is identified, retrieving the image outline of the first image, specifically, removing the rest part of the test card according to the amount of image information to determine the target area containing the first test card image in the first image; judging whether the first test card image is rectangular or not through multi-level logic; if the judgment result is yes, converting the first test card image in the target area to obtain a converted second test card image; and positioning the standard test card in the second test card image to determine the position of the standard test card.
Further, the first image is subjected to area division to obtain the target area. In the specific implementation, the detection of the complete first image usually requires a long time, and also has a high requirement on the computing power of hardware. In the embodiment of the invention, the first image is subjected to region division, and the target region obtained after the region division is detected, so that the detection time can be shortened, and the requirement on the computing capacity of hardware can be reduced.
In the embodiment of the present invention, the first image is cropped according to the size of the first image and the information amount of each area of the first image to obtain the target area.
In a specific implementation, one of the considerations for performing the area division on the first image is an information amount of the first image, and a target area obtained after the area division includes most of the information amount of the first image, that is, a target area includes a main image feature of the first image, that is, includes the annotation card.
In one embodiment, the size of the first image is a factor in dividing the area. According to the size of the first image, two thirds of the first image can be used as the target area, and one half of the first image can be used as the target area.
In a specific implementation, the first image may be divided into regions to obtain the target region according to a size of the first image and an information amount of each region.
In an alternative embodiment, image blur detection may also be performed on the target region. In a specific implementation, the image blur detection is used to detect whether the first image is blurred, that is, whether the first image can meet the minimum required sharpness requirement, and if the first image cannot pass the image blur detection, which indicates that the first image is blurred, the image quality of the first image may be determined to be not qualified without further detecting the first image.
In specific implementation, compared with other detection methods, the image blur detection process has shorter time and lower calculation requirements on hardware, so that the image blur detection is used as the first step of the imaging quality detection process, a part of images to be detected are screened out by a simpler detection method, and the detection efficiency is further improved.
Step S206, determining the target image quality characteristics of the first image according to the standard test card, the chromaticity test card and the gray scale test card;
in an embodiment of the present invention, the step S206 may specifically include:
s2061, the size of the face collected by the target camera can be estimated according to the identified standard test card; specifically, the size of the standard test card is obtained, and the product of the size of the standard test card and the ratio of the size of the standard test card to the size of the standard face stored in advance is determined as the face size of the face acquired by the target camera.
S2062, the brightness value of the target camera can be determined according to the identified gray-scale test card;
specifically, the brightness value of the target camera can be determined according to the gray-scale test card in the following manner: positioning the gray scales in the gray scale test card, and determining the position information of each gray scale; acquiring the weight and brightness of each gray scale grid according to the position information of each gray scale grid; and determining the sum of the products of the weight and the brightness of each gray grid as the brightness value of the target camera.
S2063, determining the definition of the target camera according to the chromaticity test card, and determining the color saturation of the target camera according to the brightness value of the target camera and the chromaticity test card, wherein the target image quality characteristics comprise the definition, the face size, the color saturation and the brightness value.
Specifically, the definition of the target camera can be determined according to the chromaticity test card in the following manner: positioning all the chequers in the chromaticity test card, and determining the position information of each chequer; determining the pixel value of each checkerboard according to the position information of each checkerboard; calculating the mean value or the variance of the pixel values of all the chequers in the chromaticity test card according to the pixel value of each chequer; and determining the definition of the target camera corresponding to the mean value or the variance of the pixel values of all the checkerboards in the chroma test card according to the pre-stored mapping relation between the mean value or the variance of the pixel values of the chroma test card and the definition of the camera.
Specifically, the color saturation of the target camera may be determined according to the luminance value of the target camera and the chromaticity test card in the following manner:
determining the chroma value of the target camera according to the chroma test card in the following mode:
wherein, the
Respectively, colorimetric values corresponding to color opponent dimensions a and b in a color opponent space (Lab) space from the RGB space to the first image,
chromatic values corresponding to color opposite dimensions a and b of the standard image in an LAB space;
determining a difference between the chromatic value and the luminance value of the target camera as a color saturation of the target camera, i.e., color saturation = chromatic value-luminance value.
In step S208, an imaging quality detection result of the first image is determined according to the target image quality characteristic and a predetermined image quality standard.
Through the steps S202 to S208, the standard test card is positioned and identified, the chromaticity test card and the gray scale test card are identified according to the standard test card, and the image quality characteristics are determined according to the standard test card, the chromaticity test card and the gray scale test card, so that the imaging quality of the camera is evaluated.
In the embodiment of the present invention, before a first image including a test card is acquired by a target camera, an image including the test card, a target object (a face of the target object) and a face image is shot by the camera to determine a range of image quality characteristics in the image quality standard, and specifically, a plurality of second images shot by the target camera on the test card, one or more face images and the target object are acquired under different shooting conditions;
respectively obtaining the image quality characteristics of each second image in the plurality of second images through the test card, wherein the image quality characteristics comprise the definition, the face size, the color saturation and the brightness value; for each second image, the definition, the face size, the color saturation, the brightness and the like of the second image are determined in the above manner, and the determination manner is the same as that of the determination of the image quality characteristics of the first image, which is not repeated herein.
Respectively carrying out face recognition on the plurality of second images to obtain a first face feature of the target object and second face features of the one or more face images; performing face recognition on each second image, specifically, performing face image feature extraction on the second image, where the extracted features may include: visual features, pixel statistical features, face image transformation coefficient features, face image kangaroo features and the like. Some characteristics of the human face are extracted, and a characterization method based on knowledge or a characterization method based on algebraic characteristics or statistical learning can be used. Then, matching and identifying the extracted image features, and respectively determining first similarity between the first face features of the target object in the plurality of second images and the standard face features corresponding to the target, and second similarity between the second face features of the one or more face images and the standard face features of the one or more face images; calculating the average similarity of the first similarity and the second similarity in the plurality of second images respectively; determining a range of image quality features in the image quality criterion based on the average similarity in the plurality of second images.
Further, the imaging quality of the second image with the largest average similarity is the best, and the image quality characteristic corresponding to the largest average similarity in the plurality of second images is determined as the first standard image quality characteristic, that is, the image quality characteristic with the best imaging quality is set as the maximum image quality characteristic in the image quality standard; on the contrary, the imaging quality of the second image with the minimum average similarity is the worst, the image quality feature corresponding to the minimum average similarity in the plurality of second images is determined as the second standard image quality feature, that is, the image quality feature with the worst imaging quality is set as the minimum image quality feature in the image quality standard, and finally, the range of the image quality feature in the image quality standard is determined to be greater than or equal to the second standard image quality feature and less than or equal to the first standard image quality feature, that is, the maximum image quality feature of the image quality standard is the first standard image quality feature, and the minimum image quality feature is the second standard image quality feature.
According to the embodiment of the invention, the imaging quality of the camera used in large-scale deployment can be checked and accepted according to the actual application requirements, and meanwhile, because the standard of the imaging quality of the camera is mainly visual sense in the actual use, no standard exists, and the human face recognition friendliness and the imaging quality of the camera can be associated. And a set of camera imaging standards with human face recognition friendliness is formulated according to the project characteristics of human face recognition. The test card positioning algorithm under the complex background realizes the automatic positioning of the algorithm and calculates corresponding camera parameters, and the actual use can accurately position scenes such as indoor, outdoor, over-bright, over-dark and the like. The human face recognition friendliness concept of camera imaging is provided, camera imaging parameters are mapped to the human face recognition friendliness, a standard with semantic meaning is provided for camera imaging quality, the camera can be guaranteed to achieve the maximum recognition friendliness under the parameters, and the problem that the acceptance standard of camera imaging is difficult is solved.
Fig. 3 is a schematic diagram of a test card according to an embodiment of the present invention, and as shown in fig. 3, in order to meet the requirement of a monitoring scene, a handheld monitoring scene test card suitable for a face recognition task is designed, and the test card is shot by a camera to obtain a first image, and an image feature of the camera is determined according to the first image. Fig. 4 is a flowchart of image feature extraction according to an embodiment of the present invention, as shown in fig. 4, including:
step S401, inputting a first image which is acquired by a camera and comprises a test card;
step S402, positioning the standard test card in the first image to obtain the position of the standard test card;
step S403, detecting the definition and the face size of the first image; specifically, the size of the human face can be calculated by calculating the size of the test card on the image.
Step S404, determining the position of the chromaticity test card according to the position of the standard test card, and calculating the chromaticity value Chroma of the chromaticity test card;
the Chroma value Chroma may be calculated by the following formula:
wherein, the first and the second end of the pipe are connected with each other,
the square of the color block corresponding to the color block being calculated,
for the square of the color block corresponding to the color block being calculated,
to calculate the corresponding square of the template color block,
to calculate the square of the template patch correspondence.
Step S405, determining the position of the gray test card according to the position of the standard test card, calculating the brightness value of the gray test card, and determining the difference between the chromatic value and the brightness value as the saturation;
the test algorithm of the brightness of the camera is as follows:
wherein n is a gray scale, a i Is the weight of the ith bin, L i The luminance of the ith cell. The definition test card calculates the mean value and the variance of each checkerboard by positioning the positions of the checkerboards, wherein the higher the definition is, the larger the variance is, the lower the definition is, and the smaller the variance is.
Step S406, outputting the definition, face size, brightness value, chroma value, and saturation of the first image.
Because the background of an image under a monitoring camera is complex and the image is handheld, the embodiment of the invention provides a detection algorithm with extremely high scene robustness. However, in practical use, since the test card is held by hand, there are many offsets that result in inaccurate final test card scores, and therefore, the operations of rotation and fine positioning are added, and fig. 5 is a flowchart of test card positioning according to an embodiment of the present invention, as shown in fig. 5, including the following steps:
step S501, inputting an image, namely inputting the first image;
step S502, setting a binary threshold value;
step S503, judging whether the test card contour is detected, if so, executing step S504, otherwise, executing step S502;
step S504, judge whether the outline is a rectangle, in the case of judging the result is yes, carry out step S505, otherwise carry out step S502;
step S505, the test card is rotated, specifically, the rotated test card image can be obtained by converting the matrix as follows:
wherein x and y are original coordinates, and theta is a rotation angle. And then, fine positioning is carried out on the calibration point by searching gradient information near the detection point, so that more accurate angular point positioning is obtained.
Step S506, carrying out secondary retrieval on the test card image after the rotation;
step S507, the test card in the test card image after the rotation is finely positioned;
step S508, reading the relevant parameters of the test card, and outputting the result.
The embodiment of the invention can also bind the imaging quality of the camera and the friendliness of face recognition, and after the relevant parameters of the imaging quality of the camera are obtained through the test card, how to formulate the acceptance criteria is an extremely important link. The international universal image quality standard never considers the friendliness of the imaging quality of the camera to face recognition, and the imaging quality of the camera is bound with the face recognition through the similarity between the face quality and the face recognition. The specific implementation steps are as follows:
step 1, placing two face photos beside a test card and standing by a real person for comparison, wherein fig. 6 is a schematic diagram of binding the degree of the test card and the face according to the embodiment of the invention, and as shown in fig. 6, the purpose is to place the face and the test card in the same environment for detection, and bind the read number of the test card and the friendly degree of face recognition.
And 2, respectively reading the parameter information of the camera from the test card, acquiring the face characteristics from the face image, and binding the image quality of the test card with the face image quality through the concepts of face quality scores and face recognition similarity.
And 3, according to the steps 1 and 2, the reading numbers and the face quality scores of the test cards corresponding to different parameters under the same camera condition can be obtained, and according to the bound result, the range of the camera parameters can be determined, the face recognition friendliness is optimal, and therefore the camera acceptance standard is formulated.
The embodiment of the invention can be used for large-scale acceptance of camera deployment of camera imaging quality, and the parameters of camera brightness, chroma, definition, human face size and saturation are fully automatically acquired through the gray scale, definition and chroma test card; under the environment with a complex monitoring scene background, a brand-new test card calibration algorithm is designed, and the algorithm can capture the position of the test card in a complex scene and automatically perform secondary correction of the position.
The embodiment of the invention provides a camera imaging quality standard of face recognition friendliness, and the camera imaging quality can be guaranteed to be most friendly to a face recognition algorithm through the standard; for the scheme which runs for a period of time, the problem that some extreme scenes of the detection algorithm cannot be detected is corrected, a multi-scene standard is provided, and reusability of a large-scale acceptance scheme is guaranteed; the algorithm ensures face recognition and passenger flow filing, provides high-quality videos for the back-end algorithm and meets the algorithm requirements, and accordingly improves the algorithm effect from the source.
An embodiment of the present invention further provides a detection apparatus for a camera, and fig. 7 is a block diagram of the detection apparatus for a camera according to the embodiment of the present invention, as shown in fig. 7, including:
the first obtaining module 72 is configured to obtain a first image obtained by shooting a test card by a target camera, where the test card includes a standard test card, a chromaticity test card, and a gray level test card;
the identification module 74 is configured to identify the standard test card in the first image, and identify the chrominance test card and the grayscale test card through the standard test card;
a first determining module 76, configured to determine a target image quality characteristic of the first image according to the standard test card, the chromaticity test card, and the gray scale test card;
a second determining module 78, configured to determine an imaging quality detection result of the first image according to the target image quality characteristic and a predetermined image quality standard.
Fig. 8 is a first block diagram of a detection device of a camera according to a preferred embodiment of the present invention, and as shown in fig. 8, the identification module 74 includes:
a first identification submodule 82, configured to locate the standard test card in the first image, to determine a position of the standard test card, and identify the standard test card;
a first determining sub-module 84, configured to determine the location of the chroma test card and the location of the gray test card according to the location of the standard test card;
the second identifying submodule 86 is configured to identify the chroma test card according to the location of the chroma test card, and identify the gray test card according to the location of the gray test card.
Optionally, the first identification submodule 82 includes:
the retrieval unit is used for retrieving the image contour of the first image so as to determine a target area containing a first test card image in the first image;
the judging unit is used for judging whether the first test card image is rectangular or not through multi-level logic;
the conversion unit is used for converting the first test card image in the target area under the condition that the judgment result is yes to obtain a converted second test card image;
and the first positioning unit is used for positioning the standard test card in the second test card image so as to determine the position of the standard test card.
Fig. 9 is a block diagram ii of a detection device of a camera according to a preferred embodiment of the present invention, and as shown in fig. 9, the first determination module 76 includes:
the estimation submodule 92 is used for estimating the size of the face of the target camera acquired according to the standard test card;
a second determining submodule 94, configured to determine a brightness value of the target camera according to the gray test card;
the third determining submodule 96 is configured to determine the sharpness of the target camera according to the chromaticity test card, and determine the color saturation of the target camera according to the brightness value of the target camera and the chromaticity test card, where the target image quality characteristics include the sharpness, the face size, the color saturation, and the brightness value.
Optionally, the estimator module 92 includes:
the first obtaining unit is used for obtaining the size of the standard test card;
and the first determining unit is used for determining the product of the size of the standard test card and the ratio of the size of the standard test card to the size of the standard human face, which is stored in advance, as the size of the human face of the target camera for collecting the human face.
Optionally, the third determining submodule 96 includes:
the second positioning unit is used for positioning all the chequers in the chromaticity test card and determining the position information of each chequer;
a second determining unit for determining a pixel value of each of the checkerboards according to the position information of each of the checkerboards;
the calculation unit is used for calculating the mean value or the variance of the pixel values of all the chequers in the chromaticity test card according to the pixel value of each chequer;
and the third determining unit is used for determining the definition of the target camera corresponding to the mean value or the variance of the pixel values of all the checkerboards in the chroma test card according to the mapping relation between the pre-stored mean value or variance of the pixel values of the chroma test card and the definition of the camera.
Optionally, the second determining submodule 94 includes:
the third positioning unit is used for positioning the gray scales in the gray scale test card and determining the position information of each gray scale;
the second acquisition unit is used for acquiring the weight and the brightness of each gray grid according to the position information of each gray grid;
and the fourth determining unit is used for determining the sum of the products of the weight and the brightness of each gray grid as the brightness value of the target camera.
Optionally, the third determining submodule 96 includes:
a fifth determining unit, configured to determine a chroma value of the target camera according to the chroma test card in the following manner:
wherein, the
Respectively chrominance values corresponding to the color opponent dimensions a, b in the conversion of the first image from RGB space to LAB space,
chromatic values corresponding to color opposite dimensions a and b of the standard image in an LAB space;
a sixth determining unit, configured to determine a difference between the chrominance value and the luminance value of the target camera as a color saturation of the target camera.
Optionally, the apparatus further comprises:
the second acquisition module is used for acquiring a plurality of second images which are obtained by shooting the test card, one or more face images and a target object by the target camera under different shooting conditions;
a third obtaining module, configured to obtain, through the test card, an image quality feature of each of the plurality of second images, where the image quality feature includes the sharpness, the face size, the color saturation, and the brightness value;
the face recognition module is used for respectively carrying out face recognition on the plurality of second images to obtain a first face feature of the target object and second face features of the one or more face images;
a third determining module, configured to determine first similarities between the first facial features of the target object in the plurality of second images and the standard facial features corresponding to the target object, and second similarities between the second facial features of the one or more facial images and the standard facial features of the one or more facial images, respectively;
a calculating module, configured to calculate an average similarity between the first similarity and the second similarity in the plurality of second images, respectively;
a fourth determining module, configured to determine a range of image quality features in the image quality standard according to the average similarity in the plurality of second images.
Optionally, the fourth determining module includes:
the fourth determining submodule is used for determining the image quality characteristic corresponding to the maximum average similarity in the plurality of second images as the first standard image quality characteristic;
a fifth determining submodule, configured to determine, as a second standard image quality feature, an image quality feature corresponding to the minimum average similarity in the plurality of second images;
and the sixth determining submodule is used for determining that the range of the image quality characteristic in the image quality standard is greater than or equal to the second standard image quality characteristic and less than or equal to the second standard image quality characteristic.
According to another aspect of the embodiment of the present invention, there is also provided an electronic device for implementing the detection method for a camera, as shown in fig. 10, the electronic device includes a memory 1002 and a processor 1004, the memory 1002 stores a computer program, and the processor 1004 is configured to execute the steps in any one of the method embodiments through the computer program.
Optionally, in this embodiment, the electronic apparatus may be located in at least one network device of a plurality of network devices of a computer network.
Optionally, in this embodiment, the processor may be configured to execute the following steps by a computer program:
s11, acquiring a first image which is obtained by shooting a test card by a target camera, wherein the test card comprises a standard test card, a chromaticity test card and a gray scale test card;
s12, identifying the standard test card in the first image, and identifying the chromaticity test card and the gray scale test card through the standard test card;
s13, determining the target image quality characteristic of the first image according to the standard test card, the chromaticity test card and the gray scale test card;
and S14, determining an imaging quality detection result of the first image according to the target image quality characteristic and a predetermined image quality standard.
Alternatively, it can be understood by those skilled in the art that the structure shown in fig. 10 is only an illustration, and the electronic device may also be a terminal device such as a smart phone (e.g., an android Mobile phone, an iOS Mobile phone, etc.), a tablet computer, a palm top computer, a Mobile Internet device (M id), a PAD, and the like. Fig. 10 is a diagram illustrating a structure of the electronic device. For example, the electronic device may also include more or fewer components (e.g., network interfaces, etc.) than shown in FIG. 10, or have a different configuration than shown in FIG. 10.
The memory 1002 may be used to store software programs and modules, such as program instructions/modules corresponding to the method and apparatus for detecting a camera in the embodiment of the present invention, and the processor 1004 executes various functional applications and data processing by running the software programs and modules stored in the memory 1002, that is, implements the above-described method for detecting a camera. The memory 1002 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 1002 can further include memory located remotely from the processor 1004, which can be coupled to the terminal over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof. The memory 1002 may be specifically, but not limited to, used for information such as an encryption key (including a first encryption key, a second encryption key, etc.) and a decryption key (including a first decryption key, a second decryption key, etc.). As an example, as shown in fig. 10, the memory 1002 may include, but is not limited to, the first obtaining module 72, the identifying module 74, the first determining module 76, and the second determining module 78 in the detection apparatus including the camera. In addition, the detection device may further include, but is not limited to, other module units in the first detection device of the camera, which is not described in detail in this example.
Optionally, the above-mentioned transmission device 1006 is used for receiving or sending data via a network. Examples of the network may include a wired network and a wireless network. In one example, the transmission device 1006 includes a Network adapter (NIC) that can be connected to a router via a Network cable and other Network devices so as to communicate with the internet or a local area Network. In one example, the transmission device 1006 is a Radio Frequency (RF) module, which is used for communicating with the internet in a wireless manner.
In addition, the electronic device further includes: a display 1008 for displaying the media resources; and a connection bus 1010 for connecting the respective module parts in the above-described electronic apparatus.
According to a further aspect of an embodiment of the present invention, there is also provided a computer-readable storage medium having a computer program stored therein, wherein the computer program is arranged to perform the steps of any of the above method embodiments when executed.
Alternatively, in the present embodiment, the storage medium may be configured to store a computer program for executing the steps of:
s11, acquiring a first image obtained by shooting a test card by a target camera, wherein the test card comprises a standard test card, a chromaticity test card and a gray level test card;
s12, identifying the standard test card in the first image, and identifying the chromaticity test card and the gray scale test card through the standard test card;
s13, determining the target image quality characteristics of the first image according to the standard test card, the chromaticity test card and the gray scale test card;
and S14, determining an imaging quality detection result of the first image according to the target image quality characteristic and a predetermined image quality standard.
Alternatively, in this embodiment, a person skilled in the art may understand that all or part of the steps in the methods of the foregoing embodiments may be implemented by a program instructing hardware associated with the terminal device, where the program may be stored in a computer-readable storage medium, and the storage medium may include: flash disks, read-Only memories (ROMs), random Access Memories (RAMs), magnetic or optical disks, and the like.
The above-mentioned serial numbers of the embodiments of the present invention are only for description, and do not represent the advantages and disadvantages of the embodiments.
The integrated unit in the above embodiments, if implemented in the form of a software functional unit and sold or used as a separate product, may be stored in the above computer-readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing one or more computer devices (which may be personal computers, servers, network devices, etc.) to execute all or part of the steps of the method according to the embodiments of the present invention.
In the above embodiments of the present invention, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the several embodiments provided in the present application, it should be understood that the disclosed client may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one type of division of logical functions, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and amendments can be made without departing from the principle of the present invention, and these modifications and amendments should also be considered as the protection scope of the present invention.
Claims (15)
1. A detection method of a camera is characterized by comprising the following steps:
acquiring a first image obtained by shooting a test card by a target camera, wherein the test card comprises a standard test card, a chromaticity test card and a gray level test card;
identifying the standard test card in the first image, and identifying the chromaticity test card and the gray scale test card through the standard test card;
determining a target image quality characteristic of the first image according to the standard test card, the chromaticity test card and the gray scale test card;
determining an imaging quality detection result of the first image according to the target image quality feature and a predetermined image quality standard, wherein the method comprises the following steps: and under the condition that the imaging quality detection result of the first image is within a preset range of image quality characteristics, determining that the face recognition friendliness of the target camera meets an acceptance criterion, wherein the method for determining the preset range of the image quality characteristics comprises the following steps:
acquiring a plurality of second images obtained by shooting the test card, one or more face images and the target object by the reference camera under different shooting conditions; respectively acquiring the image quality characteristic of each second image in the plurality of second images and a matched face quality score through the test card, wherein the face quality score is used for indicating the imaging quality of the face image acquired by the reference camera; and determining a preset range of the image quality characteristics in the image quality standard according to a plurality of face quality scores in the plurality of second images.
2. The method of claim 1, wherein identifying the standard test card in the first image and identifying the chrominance test card and the grayscale test card via the standard test card comprises:
positioning a standard test card in the first image to determine the position of the standard test card and identify the standard test card;
determining the position of the chromaticity test card and the position of the gray scale test card according to the position of the standard test card;
and identifying the chromaticity test card according to the position of the chromaticity test card, and identifying the gray scale test card according to the position of the gray scale test card.
3. The method of claim 2, wherein identifying the location of a standard test card in the test card comprises:
retrieving an image contour of the first image to determine a target area in the first image containing a first test card image;
judging whether the first test card image is rectangular or not through multi-level logic;
if the judgment result is yes, converting the first test card image in the target area to obtain a converted second test card image;
and positioning the standard test card in the second test card image to determine the position of the standard test card.
4. The method of claim 2, wherein determining the target image quality characteristic of the first image from the test card comprises:
estimating the size of the face collected by the target camera according to the standard test card;
determining the brightness value of the target camera according to the gray level test card;
determining the definition of the target camera according to the chromaticity test card, and determining the color saturation of the target camera according to the brightness value of the target camera and the chromaticity test card, wherein the target image quality characteristics comprise the definition, the face size, the color saturation and the brightness value.
5. The method of claim 4, wherein estimating the size of the face collected by the target camera according to the standard test card comprises:
acquiring the size of the standard test card;
and determining the ratio of the product of the size of the standard test card and the size of the standard human face to the size of the pre-stored standard test card as the size of the human face collected by the target camera.
6. The method of claim 4, wherein determining the sharpness of the target camera from the chrominance test card comprises:
positioning all the chequers in the chromaticity test card, and determining the position information of each chequer;
determining the pixel value of each checkerboard according to the position information of each checkerboard;
calculating the mean value or the variance of the pixel values of all the chequers in the chromaticity test card according to the pixel value of each chequer;
and determining the definition of the target camera corresponding to the mean value or the variance of the pixel values of all the checkerboards in the chromaticity test card according to the pre-stored mapping relation between the mean value or the variance of the pixel values of the chromaticity test card and the definition of the camera.
7. The method of claim 4, wherein determining the brightness value of the target camera from the grayscale test card comprises:
positioning the gray scales in the gray scale test card, and determining the position information of each gray scale;
acquiring the weight and brightness of each gray grid according to the position information of each gray grid;
and determining the sum of the products of the weight and the brightness of each gray grid as the brightness value of the target camera.
8. The method of claim 4, wherein determining the color saturation of the target camera according to the luminance value of the target camera and the chroma test card comprises:
determining the colorimetric value of the target camera according to the colorimetric test card in the following way:
wherein, the
Respectively is as followsAn image is converted from RGB space to chrominance values corresponding to the color opponent dimensions a, b in the color opponent space LAB space,
chromatic values corresponding to color opposite dimensions a and b of the standard image in an LAB space;
determining a difference between the chrominance value and the luminance value of the target camera as a color saturation of the target camera.
9. The method of any of claims 1 to 8, wherein prior to acquiring the first image comprising the test card by the target camera, the method further comprises:
acquiring a plurality of second images obtained by shooting the test card, one or more face images and a target object by the target camera under different shooting conditions;
respectively obtaining an image quality characteristic of each second image in the plurality of second images through the test card, wherein the image quality characteristic comprises the definition, the face size, the color saturation and the brightness value;
respectively carrying out face recognition on the plurality of second images to obtain a first face feature of the target object and a second face feature of the one or more face images;
respectively determining a first similarity between a first facial feature of the target object in the plurality of second images and a standard facial feature corresponding to the target object, and a second similarity between a second facial feature of the one or more facial images and the standard facial feature of the one or more facial images;
calculating an average similarity of the first similarity and the second similarity in the plurality of second images, respectively;
determining a range of image quality features in the image quality criterion according to the average similarity in the plurality of second images.
10. The method of claim 9, wherein determining a range of image quality features in the image quality metric based on the average similarity in the plurality of second images comprises:
determining the image quality characteristic corresponding to the maximum average similarity in the plurality of second images as a first standard image quality characteristic;
determining the image quality characteristic corresponding to the minimum average similarity in the plurality of second images as a second standard image quality characteristic;
determining a range of image quality features in the image quality standard to be greater than or equal to the second standard image quality feature and less than or equal to the second standard image quality feature.
11. A detection device for a camera is characterized by comprising:
the device comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring a first image obtained by shooting a test card by a target camera, and the test card comprises a standard test card, a chromaticity test card and a gray level test card;
the identification module is used for identifying the standard test card in the first image and identifying the chromaticity test card and the gray scale test card through the standard test card;
the first determining module is used for determining the target image quality characteristics of the first image according to the standard test card, the chromaticity test card and the gray scale test card;
a second determining module, configured to determine an imaging quality detection result of the first image according to the target image quality feature and a predetermined image quality standard, including: determining that the face recognition friendliness of the target camera meets an acceptance standard under the condition that the imaging quality detection result of the first image is within a preset range of image quality characteristics;
the detection device of the camera is also used for: acquiring a plurality of second images obtained by shooting the test card, one or more face images and the target object by a reference camera under different shooting conditions; respectively acquiring the image quality characteristics of each second image in the plurality of second images and a matched face quality score through the test card, wherein the face quality score is used for indicating the imaging quality of the face image acquired by the reference camera; and determining a preset range of the image quality characteristics in the image quality standard according to a plurality of face quality scores in the plurality of second images.
12. The apparatus of claim 11, wherein the identification module comprises:
the first identification submodule is used for positioning the standard test card in the first image so as to determine the position of the standard test card and identify the standard test card;
the first determining submodule is used for determining the position of the chromaticity test card and the position of the gray scale test card according to the position of the standard test card;
and the second identification submodule is used for identifying the chromaticity test card according to the position of the chromaticity test card and identifying the gray scale test card according to the position of the gray scale test card.
13. The apparatus of claim 12, wherein the first identification submodule comprises:
the retrieval unit is used for retrieving the image contour of the first image so as to determine a target area containing a first test card image in the first image;
the judging unit is used for judging whether the first test card image is rectangular or not through multi-level logic;
the conversion unit is used for converting the first test card image in the target area under the condition that the judgment result is yes, so as to obtain a converted second test card image;
and the first positioning unit is used for positioning the standard test card in the second test card image so as to determine the position of the standard test card.
14. A computer-readable storage medium comprising a stored program, wherein the program when executed performs the method of any of claims 1 to 10.
15. An electronic device comprising a memory and a processor, characterized in that the memory has stored therein a computer program, the processor being arranged to execute the method of any of claims 1 to 10 by means of the computer program.
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| CN111861980B (en) * | 2020-05-29 | 2022-02-01 | 合肥联宝信息技术有限公司 | Imaging detection method, electronic equipment and computer readable storage medium |
| CN112492296B (en) * | 2020-11-12 | 2022-05-10 | 北京环境特性研究所 | Imaging quality evaluation system and imaging quality evaluation method |
| CN112927183A (en) * | 2021-01-13 | 2021-06-08 | 上海商米科技集团股份有限公司 | Lens module detection method and system of specific image recognition equipment |
| CN113705389A (en) * | 2021-08-13 | 2021-11-26 | 北京市商汤科技开发有限公司 | Face recognition module testing method and device, storage medium and electronic equipment |
| CN114125419A (en) * | 2021-11-26 | 2022-03-01 | 西安诺瓦星云科技股份有限公司 | Camera adjusting method and device in multi-camera system and multi-camera system |
| CN115049658B (en) * | 2022-08-15 | 2022-12-16 | 合肥的卢深视科技有限公司 | RGB-D camera quality detection method, electronic device and storage medium |
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