CN116823683A - Lens detection method, detection device and computer device - Google Patents
Lens detection method, detection device and computer device Download PDFInfo
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Abstract
The application relates to a lens detection method, detection equipment and computer equipment. The detection method of the lens is applied to detection equipment and comprises the following steps: acquiring a plurality of images to be detected, which are shot by a lens to be detected under different focal lengths, determining a target focal length based on the images to be detected, and adjusting the focal length of the lens to be the target focal length; acquiring a dark angle detection image shot by the lens under the target focal length, and performing dark angle detection based on the dark angle detection image; acquiring a dirt detection image shot by the lens under the target focal length, and performing dirt detection based on the dirt detection image; and if the detection result of the lens is qualified through the dark angle detection and the dirt detection. By adopting the method, a plurality of indexes can be detected by one detection device, the detection process is simple, the detection efficiency is improved, and the detection cost is reduced.
Description
Technical Field
The present application relates to the field of computer vision, and in particular, to a method and apparatus for detecting a lens, and a computer apparatus.
Background
In the production process of the lens, multiple indexes of the lens need to be detected, for example, focusing, dirt, dark angles and the like of the lens need to be detected, so that imaging quality of the lens after leaving a factory is ensured. However, in the existing lens detection, multiple indexes are required to be detected through different detection equipment on different detection pipelines, the detection process is complex, and the detection efficiency is low.
Disclosure of Invention
In view of the foregoing, it is necessary to provide a lens detection method, a detection device, and a computer device that have a simple detection process and high detection efficiency.
In a first aspect, the present application provides a method for detecting a lens, which is applied to a detecting device, including:
acquiring a plurality of images to be detected, which are shot by a lens to be detected under different focal lengths, determining a target focal length based on the images to be detected, and adjusting the focal length of the lens to be the target focal length;
acquiring a dark angle detection image shot by the lens under the target focal length, and performing dark angle detection based on the dark angle detection image;
and if the detection result passes through the dirty detection, determining that the detection result of the lens is qualified.
In one embodiment, the acquiring a plurality of images to be detected, which are shot by the lens to be detected under different focal lengths, and determining the target focal length based on the plurality of images to be detected includes:
sequentially adjusting the focal length of the lens according to a preset sequence, and acquiring an image to be detected, which is shot under the current focal length, after each focal length adjustment;
responding to each acquired image to be detected, carrying out shielding detection on the image to be detected, and determining the definition of the image to be detected after the image to be detected passes through shielding detection;
and selecting the highest definition from all the determined definitions, and taking the focal length of the image to be detected corresponding to the highest definition as a target focal length.
In one embodiment, the performing occlusion detection on the image to be detected includes:
acquiring a reference image corresponding to the focal length of the image to be detected;
intercepting a plurality of boundary areas of the reference image to obtain a reference boundary image, intercepting a plurality of boundary areas of the image to be detected to obtain a boundary image to be detected, wherein the coordinate values of all pixel points included in the plurality of boundary areas of the reference image are respectively the same as the coordinate values of all pixel points included in the plurality of boundary areas of the plurality of images to be detected;
And calculating the similarity between the reference boundary image and the boundary image to be detected, and if the similarity is larger than a preset similarity threshold value, detecting the image to be detected through shielding.
In one embodiment, the performing the dark angle detection based on the dark angle detection image includes:
determining four dark angle detection sub-images and an optical center detection image in the dark angle detection images;
determining the average brightness value of the four dark angle detection sub-images and the optical center brightness value of the optical center detection image;
and if the difference value between the average brightness value and the optical center brightness value is smaller than a preset dark angle threshold value, detecting through a dark angle.
In one embodiment, before the dark angle detection based on the dark angle detection image, the method further includes:
acquiring a light center point with the maximum brightness value in the dark angle detection image and a center point of the dark angle detection image;
and if the distance between the center point and the optical center point is smaller than a preset deviation threshold value, detecting through optical center deviation.
In one embodiment, the performing the contamination detection based on the contamination detection image includes:
determining a binarized image corresponding to the dirt detection image;
Processing the binarized image through an expansion algorithm and a corrosion algorithm to obtain a processed image;
and determining the area of the dirty area based on the processed image, and if the area of the dirty area is smaller than a preset dirty threshold value, detecting the dirty area.
In a second aspect, the present application also provides a detection apparatus, including:
the focusing module is used for acquiring a plurality of images to be detected, which are shot by a lens to be detected under different focal lengths, determining a target focal length based on the images to be detected, and adjusting the focal length of the lens to be the target focal length;
the dark angle detection module is used for acquiring a dark angle detection image shot by the lens under the target focal length and carrying out dark angle detection based on the dark angle detection image;
the dirt detection module is used for acquiring a dirt detection image shot by the lens under the target focal length if the dirt detection module passes through the dark angle detection, carrying out dirt detection based on the dirt detection image, and determining that the detection result of the lens is qualified if the dirt detection module passes through the dirt detection.
In a third aspect, the present application also provides a computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program:
Acquiring a plurality of images to be detected, which are shot by a lens to be detected under different focal lengths, determining a target focal length based on the images to be detected, and adjusting the focal length of the lens to be the target focal length;
acquiring a dark angle detection image shot by the lens under the target focal length, and performing dark angle detection based on the dark angle detection image;
and if the detection result passes through the dirty detection, determining that the detection result of the lens is qualified.
In a fourth aspect, the present application also provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:
acquiring a plurality of images to be detected, which are shot by a lens to be detected under different focal lengths, determining a target focal length based on the images to be detected, and adjusting the focal length of the lens to be the target focal length;
acquiring a dark angle detection image shot by the lens under the target focal length, and performing dark angle detection based on the dark angle detection image;
And if the detection result passes through the dirty detection, determining that the detection result of the lens is qualified.
In a fifth aspect, the present application also provides a computer program product comprising a computer program which when executed by a processor performs the steps of:
acquiring a plurality of images to be detected, which are shot by a lens to be detected under different focal lengths, determining a target focal length based on the images to be detected, and adjusting the focal length of the lens to be the target focal length;
acquiring a dark angle detection image shot by the lens under the target focal length, and performing dark angle detection based on the dark angle detection image;
and if the detection result passes through the dirty detection, determining that the detection result of the lens is qualified.
The detection method of the lens, the detection equipment, the computer equipment, the storage medium and the computer program product are applied to the detection equipment, a plurality of images to be detected under different focal lengths are shot through the lens, a target focal length is determined according to the plurality of images to be detected, the focal length of the lens is adjusted to the target focal length so as to complete focusing of the lens, a dark angle detection image shot by the lens under the target focal length is acquired, dark angle detection is carried out according to the dark angle detection image, a dirty detection image shot by the lens under the target focal length is acquired, and dirty detection is carried out according to the dirty detection image; after the lens passes through the dark angle detection and the dirt detection, the detection result of the lens is determined to be qualified, and through the detection method of the lens, a plurality of indexes can be detected through one detection device, the detection process is simple, and the detection efficiency is improved.
Drawings
FIG. 1 is a flow chart of a method for detecting a lens in an embodiment;
FIG. 2 is a flowchart of a method for detecting a lens in an embodiment;
FIG. 3 is a block diagram of the detection device in one embodiment;
fig. 4 is an internal structural diagram of a computer device in one embodiment.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
In one embodiment, as shown in fig. 1, a method for detecting a lens is provided, and this embodiment is exemplified by the method being applied to a detecting device. In this embodiment, the method includes the steps of:
s101, acquiring a plurality of images to be detected, which are shot by a lens to be detected under different focal lengths, determining a target focal length based on the images to be detected, and adjusting the focal length of the lens to be the target focal length.
The focal lengths of the plurality of images to be detected are different from each other. The plurality of images to be detected are images obtained by shooting a focusing plate after the focal length of the lens is adjusted each time, and the focusing plate is provided with focusing patterns; the lens can shoot a clear image under the target focal length. The lens may be an infrared binocular camera.
Specifically, the focal length of the lens is adjusted according to a preset sequence, and after each focal length adjustment, the lens is controlled to shoot a focusing plate, so that an image to be detected is obtained; acquiring a plurality of shot images to be detected, determining the definition of each image to be detected, determining the highest definition in the definition of each image to be detected, taking the focal length corresponding to the highest definition as a target focal length, and adjusting the focal length of the lens to the target focal length.
The determining the definition of each image to be detected may be determining the definition of the image to be detected in real time after each image to be detected is obtained, or may be determining the definition of each image to be detected after a plurality of images to be detected are obtained.
S102, acquiring a dark angle detection image shot by the lens under the target focal length, and performing dark angle detection based on the dark angle detection image.
The dark angle detection image may be one of the multiple images to be detected, in which the focal length is the image to be detected corresponding to the target focal length, or may be a dark angle detection image that controls the lens to re-shoot under the target focal length. The vignetting detection is used for detecting whether the vignetting correction of the lens is effective, and if the vignetting detection of the lens does not pass, a vignetting correction algorithm of the lens needs to be modified.
And acquiring four sub-images of the dark angle detection image at four corners of the dark angle detection image, wherein the sub-images of the dark angle detection image are the dark angle detection sub-images, calculating average brightness values of the four dark angle detection sub-images, determining optical center brightness values of the dark angle detection image, and if the difference value between the optical center brightness values and the average brightness values is smaller than a preset dark angle threshold value, the lens passes through the dark angle detection, wherein the preset dark angle threshold value can be an empirical value of the dark angle detection, or the preset dark angle threshold value can be set according to actual requirements.
If the difference between the optical center brightness value and the average brightness value is greater than or equal to a preset dark angle threshold, judging that the lens fails to pass the dark angle detection, sending a first prompt and ending the lens detection flow, wherein the first prompt is used for reflecting the detection result of the lens as follows: the dark angle detection fails.
And S103, acquiring a dirt detection image of the lens shot under the target focal length if the camera lens passes through the dark angle detection, performing dirt detection based on the dirt detection image, and determining that the detection result of the camera lens is qualified if the camera lens passes through the dirt detection.
The dirt detection image is an image obtained by shooting a whiteboard with uniform light filling by the lens under a target focal length, and the distance between the whiteboard and the lens is the same as the distance between the focusing plate and the lens. The dirt detection is used for detecting whether dirt exists on the lens, and if the dirt exists on the lens, the dirt can be displayed on an image obtained by shooting the whiteboard.
Specifically, determining a binary image of the dark angle detection image, if dirt exists on the lens, displaying a dirt area by the binary image, and if the dirt area does not exist in the binary image, detecting the dirt by the lens; so far, the lens has completed focusing, and through the dark angle detection and the dirt detection, the detection result of the lens can be determined to be qualified.
If the lens fails to pass the dirt detection, a second prompt is sent out and the lens detection flow is ended, wherein the second prompt is used for reflecting the detection result of the lens as follows: the smudge detection fails.
According to the detection method of the lens, a plurality of images to be detected under different focal lengths are shot through the lens, the target focal length is determined according to the plurality of images to be detected, the focal length of the lens is adjusted to the target focal length to finish focusing of the lens, the dark angle detection image shot by the lens under the target focal length is obtained, dark angle detection is carried out according to the dark angle detection image, after the lens passes through the dark angle detection, the dirt detection image shot by the lens under the target focal length is obtained, dirt detection is carried out according to the dirt detection image, after the lens passes through the dark angle detection and the dirt detection, the detection result of the lens is determined to be qualified, and through the detection method of the lens, a plurality of indexes can be detected through one detection device, the detection process is simple, the detection efficiency is improved, and the detection cost is reduced.
In one embodiment, in S101, the obtaining a plurality of images to be detected that are captured by the lens to be detected under different focal lengths, and determining the target focal length based on the plurality of images to be detected includes:
and S111, sequentially adjusting the focal length of the lens according to a preset sequence, and acquiring an image to be detected, which is shot under the current focal length, after each focal length adjustment.
Specifically, the preset sequence may be a sequence from small to large in focal length, that is, the focal length of the lens is firstly adjusted to the minimum focal length, and the focal length of the lens is adjusted for multiple times according to the sequence from small to large in focal length until the focal length is adjusted to the maximum focal length; alternatively, the preset sequence may be a sequence of focal lengths from large to small, that is, the focal length of the lens is firstly adjusted to the maximum focal length, and the focal length of the lens is adjusted for multiple times according to the sequence of focal lengths from large to small until the focal length is adjusted to the minimum focal length; the maximum focal length is a maximum value in a focal length adjustable range of the lens, and the minimum focal length is a minimum value in the focal length adjustable range of the lens.
After the focal length is adjusted each time, the lens is controlled to shoot an image to be detected under the current focal length, and the image to be detected is obtained to obtain a plurality of images to be detected.
S112, responding to each acquired image to be detected, carrying out shielding detection on the image to be detected, and determining the definition of the image to be detected after the image to be detected passes through shielding detection.
Specifically, in adjusting the focal length of the lens, there may be a case where an object blocks the lens, for example, when the focal length of the lens is manually adjusted, a finger blocks the lens, or the mounting of a member for fixing the lens is not standardized, resulting in a lens having a block, or the like.
The high-definition image has sharp edges, so that the gradient of the high-definition image is large, if the image is blocked, the blocking area in the image can cause the gradient of the image to be small, so that the definition of the image with the blocking is recognized to be low, in fact, the definition of the image with the blocking can be high, so that the definition of the image with the blocking is recognized inaccurately, that is, if the image to be detected is blocked, the definition of the image to be detected is inaccurate, therefore, the detection image with the blocking needs to be removed, and the blocking is prompted.
In one embodiment, since occlusion generally occurs at an edge position of an image, in order to reduce the amount of computation of occlusion detection, a boundary image to be detected of the image to be detected is truncated, and occlusion detection is performed through the boundary image to be detected, S112 includes:
S1121, obtaining a reference image corresponding to the focal length of the image to be detected.
Specifically, if the image to be detected is an image obtained by shooting a focusing plate, the reference image is also an image obtained by shooting an adjusting plate, the view angle range of a reference lens for shooting the reference image is the same as that of the lens, and when the reference lens shoots the reference image, the position of the reference image relative to the shooting object is the same as that of the lens when shooting the image to be detected, so that the picture content of the reference image is consistent with the picture content of the object to be detected; there is no occlusion in the reference image.
S1122, a plurality of boundary areas of the reference image are intercepted to obtain a reference boundary image, and a plurality of boundary areas of the image to be detected are intercepted to obtain the boundary image to be detected.
Wherein the plurality of boundary regions includes: an upper boundary region, a lower boundary region, a left boundary region, and a right boundary region. The coordinate values of all the pixel points included in the plurality of boundary areas of the reference image are respectively the same as the coordinate values of all the pixel points included in the plurality of boundary areas of the plurality of images to be detected. The coordinate values of all the pixels included in the upper boundary region of the reference image are respectively the same as the coordinate values of all the pixels included in the upper boundary region of the image to be detected.
For example, the coordinate values of the pixel points at the upper left corners of the reference image and the detection image are set to be (1, 1), the coordinate values of all the pixel points in the upper boundary area of the reference image are set to be (a, b), 1.ltoreq.a.ltoreq.20, 1.ltoreq.b.ltoreq.20, the coordinate values of all the pixel points in the upper boundary area of the image to be detected are set to be (c, d), 1.ltoreq.c.ltoreq.20, 1.ltoreq.d.ltoreq.20; for any pixel point in the upper boundary region of the reference image, in the upper boundary region of the image to be detected, there is a pixel point having the same coordinate value as the any pixel point. It can be seen that the coordinate values of all the pixel points in the upper boundary region of the reference image are the same as the coordinate values of all the pixel points in the upper boundary region of the image to be detected.
Specifically, an upper boundary region, a lower boundary region, a left boundary region and a right boundary region in the reference image are intercepted to obtain a reference boundary image, and the upper boundary region, the lower boundary region, the left boundary region and the right boundary region in the image to be detected are intercepted to obtain the boundary image to be detected.
And determining an upper boundary region, a lower boundary region, a left boundary region and a right boundary region according to preset boundary widths, wherein the boundary widths can be represented by the number of pixel points and can be set according to actual requirements.
For example, the boundary width is 50, the dimensions of the reference image and the image to be detected are 400×400, all pixels of the row coordinates 1 to 50 are regarded as pixels of the upper boundary region, all pixels of the row coordinates 351 to 400 are regarded as pixels of the lower boundary region, all pixels of the column coordinates 1 to 50 are regarded as pixels of the left boundary region, all pixels of the column coordinates 351 to 400 are regarded as pixels of the lower boundary region, the boundary image including all pixels of the reference image having row coordinates 1 to 50 and 351 to 400 and column coordinates 1 to 50 and 351 to 400, and all pixels of the image to be detected including all pixels of the image to be detected having row coordinates 1 to 50 and 351 to 400 and column coordinates 1 to 50 and 351 to 400.
S1123, calculating the similarity between the reference boundary image and the boundary image to be detected, and if the similarity is larger than a preset similarity threshold, detecting the image to be detected through shielding.
Specifically, the preset similarity threshold may be set according to the requirement. And determining a first histogram according to the brightness value of the reference boundary image, determining a second histogram according to the brightness value of the boundary image to be detected, calculating the similarity according to the first histogram and the second histogram, and if the similarity is greater than a preset similarity threshold, detecting the image to be detected through shielding.
If the similarity is not greater than a preset similarity threshold, the image to be detected does not pass the shielding detection, the image to be detected is removed, and a third prompt is sent out, wherein the third prompt is used for reflecting that the lens is shielded.
And S113, selecting the highest definition from all the determined definitions, and taking the focal length of the image to be detected corresponding to the highest definition as a target focal length.
Specifically, the focal length corresponding to the highest definition among all the resolutions is taken as the target focal length.
In one embodiment, S101 includes:
and sequentially adjusting the focal length of the lens according to a preset sequence, acquiring an image to be detected photographed under the current focal length after adjusting the focal length each time, carrying out shielding detection on the image to be detected in response to the image to be detected acquired each time, determining the definition of the image to be detected after the image to be detected passes through shielding detection, and taking the focal length corresponding to the determined definition as a target focal length if the determined definition is larger than a preset definition threshold.
For example, the focal length of the lens is adjusted to f1, an image P1 to be detected, which is shot by the lens under f1, is obtained, if P1 passes the occlusion detection, the definition s1 of P1 is determined, if s1 is not greater than a preset definition threshold, the focal length of the lens is adjusted to f2, an image P2 to be detected, which is shot by the lens under f2, is obtained, if P2 passes the occlusion detection, the definition s2 of P2 is determined, if s2 is not greater than the preset definition threshold, the focal length of the lens is adjusted to f3, an image P3 to be detected, which is shot by the lens under f3, if P3 passes the occlusion detection, the definition s3 of P1 is determined, and if s3 is greater than the preset definition threshold, the target focal length is determined to be f3.
In one embodiment, in S102, the performing, based on the vignetting detection image, vignetting detection includes:
s1021, four dark angle detection sub-images, and a light center detection image are determined in the dark angle detection image.
Specifically, the four dark angle detection sub-images are a first dark angle detection sub-image, a second dark angle detection sub-image, a third dark angle detection sub-image and a fourth dark angle detection sub-image respectively; determining a first dark angle detection sub-image according to the pixel point of the first corner of the dark angle detection image and the preset side length, determining a second dark angle detection sub-image according to the pixel point of the second corner of the dark angle detection image and the preset side length, determining a third dark angle detection sub-image according to the pixel point of the third corner of the dark angle detection image and the preset side length, and determining a fourth dark angle detection sub-image according to the pixel point of the fourth corner of the dark angle detection image and the preset side length. And the center of the optical center detection image is the optical center of the dark angle detection image, and the optical center detection image is determined according to the optical center and the preset side length. The optical center detection image has the same size as any one of the dark angle detection sub-images.
For example, assuming that the preset side length is 50 pixel points, the pixel points of the four corners of the dark corner detection image include: (1, 1), (1, 400), (400,1), (400 ), the first dark angle detection sub-image includes all pixel points having a row coordinate of 1 to 50 and a column coordinate of 1 to 50, the second dark angle detection sub-image includes all pixel points having a row coordinate of 351 to 400 and a column coordinate of 1 to 50, the third dark angle detection sub-image includes all pixel points having a row coordinate of 1 to 50 and a column coordinate of 351 to 400, and the fourth dark angle detection sub-image includes all pixel points having a row coordinate of 351 to 400 and a column coordinate of 351 to 400.
S1022, determining average brightness values of the four dark angle detection sub-images and the light center brightness value of the light center detection image.
S1023, if the difference value between the average brightness value and the optical center brightness value is smaller than a preset dark angle threshold value, the dark angle detection image passes through dark angle detection.
Specifically, the preset dark angle threshold may be set according to actual requirements, and if the difference is smaller than the preset dark angle threshold, the lens passes through dark angle detection. If the difference value is not smaller than the preset dark angle threshold value, the lens does not pass the dark angle detection, a first prompt is sent out, and the lens detection flow is ended.
Before S1021, further comprising;
and S01, acquiring a light center point with the maximum brightness value in the dark angle detection image and a center point of the dark angle detection image.
Specifically, the brightness value of each pixel point in the dark angle detection image is determined, the point with the maximum brightness value is taken as the optical center point of the dark angle detection image, and the center point is determined according to the coordinate value of each pixel point in the dark angle detection image.
S02, if the distance between the center point and the optical center point is smaller than a preset deviation threshold value, detecting through optical center deviation.
Specifically, a center coordinate value of the center point and a light center coordinate value of the light center point are determined, a distance between the center coordinate value and the light center coordinate value is calculated, and if the distance is smaller than a preset deviation threshold value, the lens passes through light center deviation detection. The preset offset threshold value can be set according to actual requirements.
If the distance is not smaller than the preset offset distance, judging that the lens does not pass through the optical center offset detection, sending a fourth prompt and ending the lens detection flow, wherein the fourth prompt is used for reflecting the detection result of the lens as follows: the optical center shift detection fails.
In one embodiment, in S103, the performing the contamination detection based on the contamination detection image includes:
s1031, determining a binarized image corresponding to the dirt detection image.
Specifically, as the gradual change shadow exists in the lens, the gradual change shadow is relatively close to the dirt of the lens, so that the dirt is not easy to separate from the shadow in the common binarization processing, the dirt detection image is subjected to the self-adaptive binarization processing to obtain a binarized image, wherein the self-adaptive binarization processing is to obtain a binarization threshold value suitable for the dirt detection image according to the gray level histogram of the image, and then obtain the binarization image according to the binarization threshold value and the dirt detection image.
S1032, processing the binarized image through an expansion algorithm and a corrosion algorithm to obtain a processed image.
Specifically, in the binarized image, white areas may be dirty areas and black areas may not be dirty areas. And (3) performing white point supplementation on the periphery of a plurality of fine white points in the binary image through an expansion algorithm, realizing connection between the similar fine white points, obtaining an expansion image, processing the expansion image through a corrosion algorithm, so that the white area obtained by connection is reduced, the area of the reduced white area is the same as the area occupied before the connection of the plurality of fine white points, and obtaining a processed image.
S1033, determining the area of the dirty area based on the processed image, and if the area of the dirty area is smaller than a preset dirty threshold value, detecting the dirty.
Specifically, the area of the white area in the processed image is calculated to obtain the area of the dirty area, and the area of the white area can be calculated by an opencv self-contained edge area calculation method. The preset dirt threshold can be set according to actual requirements, and if the area of the dirt area is smaller than the preset dirt threshold, dirt detection is passed.
Although in the embodiments of the above-described lens inspection method, the steps are written in order from the small to the large, the steps are not necessarily performed in order from the small to the large, and in fig. 1 related to the above-described lens inspection method, the steps are displayed in order indicated by the arrows, but the steps are not necessarily performed in order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders.
In a specific embodiment, referring to fig. 2, the method for detecting the lens includes:
a1, starting detection;
a2, acquiring an image to be detected, which is shot by a lens, and carrying out shielding detection on the image to be detected;
a3, judging whether the shielding detection passes or not, if not, entering a4, and if so, entering a5;
a4, eliminating the image to be detected, and entering a6;
a5, determining the definition of the image to be detected, and entering a6;
a6, judging whether the focal length of the lens is the maximum value of the focal length adjustable range, if not, entering a7, and if so, entering a8;
a7, adjusting the focal length of the lens according to a preset sequence, and entering a2;
a8, taking the focal length of the image to be detected corresponding to the highest definition as a target focal length;
a9, adjusting the lens to a target focal length;
a10, acquiring a dark angle detection image shot by the lens at a target focal length, and detecting optical center offset according to the dark angle detection image;
a11, judging whether the optical center deviation detection is passed or not, and if the optical center deviation detection is not passed, entering a12; if the optical center deviation detection passes, entering a13;
a12, prompting that the optical center deviation detection is not passed, wherein the detection result of the lens is unqualified;
a13, detecting the dark angle according to the dark angle detection image;
a14, judging whether the dark angle detection is passed or not, if the dark angle detection is not passed, entering a15, and if the dark angle detection is passed, entering a16;
a15, prompting that the dark angle detection does not pass, wherein the detection result of the lens is unqualified;
a16, acquiring a dirt detection image shot by the lens at a target focal length;
a17, performing dirt detection according to the dirt detection image;
a18, judging whether the dirt detection is passed or not, if the dirt detection is not passed, entering a19, and if the dirt detection is passed, entering a20;
a19, prompting that the dirt detection is not passed, wherein the detection result of the lens is unqualified;
and a20, detecting results of the lens are qualified.
According to the lens detection method, after successful lens focusing, optical center deviation detection, dark angle detection and dirt detection pass, the detection result of the lens can be determined to be qualified, the quality of lens detection is guaranteed, when a large number of lenses need to be detected, the a1 to a20 can be carried out on each lens, rapid batch detection of the lenses is realized, and the lens detection method is suitable for application scenes of a large number of detection lenses.
Although the embodiment of the above-described lens detection method is implemented according to steps a1 to a20, which are sequentially shown in fig. 2 as indicated by arrows, the steps a1 to a20 are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. For example, a1 to a9 may be performed to adjust the lens to the target focal length, a16 to a19 may be performed to perform the contamination detection, and a10 to a15 may be performed to perform the optical center detection and the vignetting detection.
In this embodiment, a plurality of images to be detected under different focal lengths are shot through a lens, a target focal length is determined according to the plurality of images to be detected, the focal length of the lens is adjusted to the target focal length to complete focusing of the lens, a dark angle detection image shot by the lens under the target focal length is acquired, dark angle detection is performed according to the dark angle detection image, a dirt detection image shot by the lens under the target focal length is acquired, dirt detection is performed according to the dirt detection image, after the lens passes through the dark angle detection and the dirt detection, the detection result of the lens is determined to be qualified, and a plurality of indexes can be detected through one detection device by the detection method of the lens.
It should be understood that at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of execution of the steps or stages is not necessarily sequential, but may be performed in turn or alternately with at least some of the other steps or stages.
Based on the same inventive concept, the embodiment of the application also provides a detection device for realizing the detection method of the lens. The implementation of the solution provided by the detection device is similar to the implementation described in the above method, so the specific limitation in the embodiment of the detection device provided below may refer to the limitation of the detection method for the lens hereinabove, and will not be repeated here.
In one embodiment, as shown in fig. 3, there is provided a detection apparatus including:
the focusing module 100 is configured to obtain a plurality of images to be detected, which are shot by a lens to be detected under different focal lengths, determine a target focal length based on the plurality of images to be detected, and adjust the focal length of the lens to the target focal length;
the dark angle detection module 200 is configured to obtain a dark angle detection image captured by the lens under the target focal length, and perform dark angle detection based on the dark angle detection image;
the contamination detection module 300 is configured to obtain a contamination detection image of the lens captured under the target focal length if the contamination detection module passes the dark angle detection, perform contamination detection based on the contamination detection image, and determine that the detection result of the lens is qualified if the contamination detection module passes the contamination detection.
In one embodiment, the focusing module includes:
the focusing unit is used for sequentially adjusting the focal length of the lens according to a preset sequence and acquiring an image to be detected, which is shot under the current focal length, after each focal length adjustment;
the shielding detection unit is used for responding to the image to be detected obtained each time, carrying out shielding detection on the image to be detected, and determining the definition of the image to be detected after the image to be detected passes through shielding detection;
and the target focal length determining unit is used for selecting the highest definition from all the determined definitions and taking the focal length of the image to be detected corresponding to the highest definition as the target focal length.
In one embodiment, the occlusion detection unit comprises:
the first processing unit is used for acquiring a reference image corresponding to the focal length of the image to be detected;
the second processing unit is used for intercepting a plurality of boundary areas of the reference image to obtain a reference boundary image, intercepting a plurality of boundary areas of the image to be detected to obtain a boundary image to be detected, wherein the coordinate values of all pixel points included in the plurality of boundary areas of the reference image are respectively the same as the coordinate values of all pixel points included in the plurality of boundary areas of the image to be detected;
And the third processing unit is used for calculating the similarity between the reference boundary image and the boundary image to be detected, and if the similarity is larger than a preset similarity threshold value, the image to be detected passes the shielding detection.
In one embodiment, the vignetting detection module includes:
an image determining unit configured to determine four dark angle detection sub-images, and an optical center detection image, among the dark angle detection images;
a luminance value determining unit configured to determine an average luminance value of the four dark angle detection sub-images and a light center luminance value of the light center detection image;
and the dark angle detection unit is used for detecting the dark angle if the difference value between the average brightness value and the optical center brightness value is smaller than a preset dark angle threshold value.
In one embodiment, the detection device further comprises:
the optical center offset detection module is used for acquiring an optical center point with the maximum brightness value in the dark angle detection image and a center point of the dark angle detection image; and if the distance between the center point and the optical center point is smaller than a preset deviation threshold value, detecting through optical center deviation.
In one embodiment, the soil detection module comprises:
The binarization processing unit is used for determining a binarization image corresponding to the dirt detection image;
the expansion corrosion processing unit is used for processing the binarized image through an expansion algorithm and a corrosion algorithm to obtain a processed image;
and the dirty detection unit is used for determining the area of the dirty area based on the processed image, and if the area of the dirty area is smaller than a preset dirty threshold value, the dirty detection is carried out.
The respective modules in the above detection device may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a terminal, and the internal structure of which may be as shown in fig. 4. The computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless mode can be realized through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. The computer program, when executed by a processor, implements a method of detecting a lens. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, can also be keys, a track ball or a touch pad arranged on the shell of the computer equipment, and can also be an external keyboard, a touch pad or a mouse and the like.
It will be appreciated by persons skilled in the art that the architecture shown in fig. 4 is merely a block diagram of some of the architecture relevant to the present inventive arrangements and is not limiting as to the computer device to which the present inventive arrangements are applicable, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
In one embodiment, a computer device is provided comprising a memory and a processor, the memory having stored therein a computer program, the processor when executing the computer program performing the steps of:
acquiring a plurality of images to be detected, which are shot by a lens to be detected under different focal lengths, determining a target focal length based on the images to be detected, and adjusting the focal length of the lens to be the target focal length;
acquiring a dark angle detection image shot by the lens under the target focal length, and performing dark angle detection based on the dark angle detection image;
and if the detection result passes through the dirty detection, determining that the detection result of the lens is qualified.
In one embodiment, the processor when executing the computer program further performs the steps of:
acquiring a plurality of images to be detected, which are shot by a lens to be detected under different focal lengths, and determining a target focal length based on the images to be detected, wherein the method comprises the following steps:
sequentially adjusting the focal length of the lens according to a preset sequence, and acquiring an image to be detected, which is shot under the current focal length, after each focal length adjustment;
responding to each acquired image to be detected, carrying out shielding detection on the image to be detected, and determining the definition of the image to be detected after the image to be detected passes through shielding detection;
and selecting the highest definition from all the determined definitions, and taking the focal length of the image to be detected corresponding to the highest definition as a target focal length.
In one embodiment, the processor when executing the computer program further performs the steps of:
the shielding detection of the image to be detected comprises the following steps:
acquiring a reference image corresponding to the focal length of the image to be detected;
intercepting a plurality of boundary areas of the reference image to obtain a reference boundary image, intercepting a plurality of boundary areas of the image to be detected to obtain a boundary image to be detected, wherein the coordinate values of all pixel points included in the plurality of boundary areas of the reference image are respectively the same as the coordinate values of all pixel points included in the plurality of boundary areas of the plurality of images to be detected;
And calculating the similarity between the reference boundary image and the boundary image to be detected, and if the similarity is larger than a preset similarity threshold value, detecting the image to be detected through shielding.
In one embodiment, the processor when executing the computer program further performs the steps of:
the performing the vignetting detection based on the vignetting detection image includes:
determining four dark angle detection sub-images and an optical center detection image in the dark angle detection images;
determining the average brightness value of the four dark angle detection sub-images and the optical center brightness value of the optical center detection image;
and if the difference value between the average brightness value and the optical center brightness value is smaller than a preset dark angle threshold value, detecting through a dark angle.
In one embodiment, the processor when executing the computer program further performs the steps of:
before the dark angle detection is performed based on the dark angle detection image, the method further comprises:
acquiring a light center point with the maximum brightness value in the dark angle detection image and a center point of the dark angle detection image;
and if the distance between the center point and the optical center point is smaller than a preset deviation threshold value, detecting through optical center deviation.
In one embodiment, the processor when executing the computer program further performs the steps of:
The performing the contamination detection based on the contamination detection image includes:
determining a binarized image corresponding to the dirt detection image;
processing the binarized image through an expansion algorithm and a corrosion algorithm to obtain a processed image;
and determining the area of the dirty area based on the processed image, and if the area of the dirty area is smaller than a preset dirty threshold value, detecting the dirty area.
In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of:
acquiring a plurality of images to be detected, which are shot by a lens to be detected under different focal lengths, determining a target focal length based on the images to be detected, and adjusting the focal length of the lens to be the target focal length;
acquiring a dark angle detection image shot by the lens under the target focal length, and performing dark angle detection based on the dark angle detection image;
and if the detection result passes through the dirty detection, determining that the detection result of the lens is qualified.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring a plurality of images to be detected, which are shot by a lens to be detected under different focal lengths, and determining a target focal length based on the images to be detected, wherein the method comprises the following steps:
sequentially adjusting the focal length of the lens according to a preset sequence, and acquiring an image to be detected, which is shot under the current focal length, after each focal length adjustment;
responding to each acquired image to be detected, carrying out shielding detection on the image to be detected, and determining the definition of the image to be detected after the image to be detected passes through shielding detection;
and selecting the highest definition from all the determined definitions, and taking the focal length of the image to be detected corresponding to the highest definition as a target focal length.
In one embodiment, the computer program when executed by the processor further performs the steps of:
the shielding detection of the image to be detected comprises the following steps:
acquiring a reference image corresponding to the focal length of the image to be detected;
intercepting a plurality of boundary areas of the reference image to obtain a reference boundary image, intercepting a plurality of boundary areas of the image to be detected to obtain a boundary image to be detected, wherein the coordinate values of all pixel points included in the plurality of boundary areas of the reference image are respectively the same as the coordinate values of all pixel points included in the plurality of boundary areas of the plurality of images to be detected;
And calculating the similarity between the reference boundary image and the boundary image to be detected, and if the similarity is larger than a preset similarity threshold value, detecting the image to be detected through shielding.
In one embodiment, the processor when executing the computer program further performs the steps of:
the performing the vignetting detection based on the vignetting detection image includes:
determining four dark angle detection sub-images and an optical center detection image in the dark angle detection images;
determining the average brightness value of the four dark angle detection sub-images and the optical center brightness value of the optical center detection image;
and if the difference value between the average brightness value and the optical center brightness value is smaller than a preset dark angle threshold value, detecting through a dark angle.
In one embodiment, the computer program when executed by the processor further performs the steps of:
before the dark angle detection is performed based on the dark angle detection image, the method further comprises:
acquiring a light center point with the maximum brightness value in the dark angle detection image and a center point of the dark angle detection image;
and if the distance between the center point and the optical center point is smaller than a preset deviation threshold value, detecting through optical center deviation.
In one embodiment, the computer program when executed by the processor further performs the steps of:
The performing the contamination detection based on the contamination detection image includes:
determining a binarized image corresponding to the dirt detection image;
processing the binarized image through an expansion algorithm and a corrosion algorithm to obtain a processed image;
and determining the area of the dirty area based on the processed image, and if the area of the dirty area is smaller than a preset dirty threshold value, detecting the dirty area.
In one embodiment, a computer program product is provided comprising a computer program which, when executed by a processor, performs the steps of:
acquiring a plurality of images to be detected, which are shot by a lens to be detected under different focal lengths, determining a target focal length based on the images to be detected, and adjusting the focal length of the lens to be the target focal length;
acquiring a dark angle detection image shot by the lens under the target focal length, and performing dark angle detection based on the dark angle detection image;
and if the detection result passes through the dirty detection, determining that the detection result of the lens is qualified.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring a plurality of images to be detected, which are shot by a lens to be detected under different focal lengths, and determining a target focal length based on the images to be detected, wherein the method comprises the following steps:
sequentially adjusting the focal length of the lens according to a preset sequence, and acquiring an image to be detected, which is shot under the current focal length, after each focal length adjustment;
responding to each acquired image to be detected, carrying out shielding detection on the image to be detected, and determining the definition of the image to be detected after the image to be detected passes through shielding detection;
and selecting the highest definition from all the determined definitions, and taking the focal length of the image to be detected corresponding to the highest definition as a target focal length.
In one embodiment, the computer program when executed by the processor further performs the steps of:
the shielding detection of the image to be detected comprises the following steps:
acquiring a reference image corresponding to the focal length of the image to be detected;
intercepting a plurality of boundary areas of the reference image to obtain a reference boundary image, intercepting a plurality of boundary areas of the image to be detected to obtain a boundary image to be detected, wherein the coordinate values of all pixel points included in the plurality of boundary areas of the reference image are respectively the same as the coordinate values of all pixel points included in the plurality of boundary areas of the plurality of images to be detected;
And calculating the similarity between the reference boundary image and the boundary image to be detected, and if the similarity is larger than a preset similarity threshold value, detecting the image to be detected through shielding.
In one embodiment, the processor when executing the computer program further performs the steps of:
the performing the vignetting detection based on the vignetting detection image includes:
determining four dark angle detection sub-images and an optical center detection image in the dark angle detection images;
determining the average brightness value of the four dark angle detection sub-images and the optical center brightness value of the optical center detection image;
and if the difference value between the average brightness value and the optical center brightness value is smaller than a preset dark angle threshold value, detecting through a dark angle.
In one embodiment, the computer program when executed by the processor further performs the steps of:
before the dark angle detection is performed based on the dark angle detection image, the method further comprises:
acquiring a light center point with the maximum brightness value in the dark angle detection image and a center point of the dark angle detection image;
and if the distance between the center point and the optical center point is smaller than a preset deviation threshold value, detecting through optical center deviation.
In one embodiment, the computer program when executed by the processor further performs the steps of:
The performing the contamination detection based on the contamination detection image includes:
determining a binarized image corresponding to the dirt detection image;
processing the binarized image through an expansion algorithm and a corrosion algorithm to obtain a processed image;
and determining the area of the dirty area based on the processed image, and if the area of the dirty area is smaller than a preset dirty threshold value, detecting the dirty area.
The user information (including but not limited to user equipment information, user personal information, etc.) and the data (including but not limited to data for analysis, stored data, presented data, etc.) related to the present application are information and data authorized by the user or sufficiently authorized by each party.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magnetic random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (Phase Change Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like. The databases referred to in the embodiments provided herein may include at least one of a relational database and a non-relational database. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processor referred to in the embodiments provided in the present application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, or the like, but is not limited thereto.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The foregoing examples illustrate only a few embodiments of the application and are described in detail herein without thereby limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of the application should be assessed as that of the appended claims.
Claims (10)
1. A method for detecting a lens, applied to a detecting device, comprising:
acquiring a plurality of images to be detected, which are shot by a lens to be detected under different focal lengths, determining a target focal length based on the images to be detected, and adjusting the focal length of the lens to be the target focal length;
acquiring a dark angle detection image shot by the lens under the target focal length, and performing dark angle detection based on the dark angle detection image;
And if the detection result passes through the dirty detection, determining that the detection result of the lens is qualified.
2. The method according to claim 1, wherein the acquiring a plurality of images to be detected taken by a lens to be detected at different focal lengths, determining a target focal length based on the plurality of images to be detected, comprises:
sequentially adjusting the focal length of the lens according to a preset sequence, and acquiring an image to be detected, which is shot under the current focal length, after each focal length adjustment;
responding to each acquired image to be detected, carrying out shielding detection on the image to be detected, and determining the definition of the image to be detected after the image to be detected passes through shielding detection;
and selecting the highest definition from all the determined definitions, and taking the focal length of the image to be detected corresponding to the highest definition as the target focal length.
3. The method according to claim 2, wherein the performing occlusion detection on the image to be detected includes:
acquiring a reference image corresponding to the focal length of the image to be detected;
Intercepting a plurality of boundary areas of the reference image to obtain a reference boundary image, intercepting a plurality of boundary areas of the image to be detected to obtain a boundary image to be detected, wherein the coordinate values of all pixel points included in the plurality of boundary areas of the reference image are respectively the same as the coordinate values of all pixel points included in the plurality of boundary areas of the plurality of images to be detected;
and calculating the similarity between the reference boundary image and the boundary image to be detected, and if the similarity is larger than a preset similarity threshold value, detecting the image to be detected through shielding.
4. The detection method according to claim 1, wherein the performing the dark angle detection based on the dark angle detection image includes:
determining four dark angle detection sub-images and an optical center detection image in the dark angle detection images;
determining the average brightness value of the four dark angle detection sub-images and the optical center brightness value of the optical center detection image;
and if the difference value between the average brightness value and the optical center brightness value is smaller than a preset dark angle threshold value, detecting through a dark angle.
5. The detection method according to any one of claims 1 to 4, characterized by further comprising, before the vignetting detection based on the vignetting detection image:
Acquiring a light center point with the maximum brightness value in the dark angle detection image and a center point of the dark angle detection image;
and if the distance between the center point and the optical center point is smaller than a preset deviation threshold value, detecting through optical center deviation.
6. The detection method according to claim 1, wherein the performing the stain detection based on the stain detection image includes:
determining a binarized image corresponding to the dirt detection image;
processing the binarized image through an expansion algorithm and a corrosion algorithm to obtain a processed image;
and determining the area of the dirty area based on the processed image, and if the area of the dirty area is smaller than a preset dirty threshold value, detecting the dirty area.
7. A detection apparatus, characterized by comprising:
the focusing module is used for acquiring a plurality of images to be detected, which are shot by a lens to be detected under different focal lengths, determining a target focal length based on the images to be detected, and adjusting the focal length of the lens to be the target focal length;
the dark angle detection module is used for acquiring a dark angle detection image shot by the lens under the target focal length and carrying out dark angle detection based on the dark angle detection image;
The dirt detection module is used for acquiring a dirt detection image shot by the lens under the target focal length if the dirt detection module passes through the dark angle detection, carrying out dirt detection based on the dirt detection image, and determining that the detection result of the lens is qualified if the dirt detection module passes through the dirt detection.
8. A computer device comprising a memory storing a computer program and a processor, characterized in that the processor is adapted to implement the steps of the detection method according to any one of claims 1 to 6 when the computer program is executed.
9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the detection method according to any one of claims 1 to 6.
10. A computer program product comprising a computer program, characterized in that the computer program, when executed by a processor, implements the steps of the detection method according to any one of claims 1 to 6.
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