CN114677441A - Optical center testing method, optical center testing device and electronic equipment - Google Patents

Abstract

The optical center testing method comprises the steps of firstly, obtaining a target board image of a testing target board, wherein the testing target board comprises a plurality of feature points with equal intervals, then, transforming the target board image into an anti-distortion image domain to correct the image in an anti-distortion correction mode, and then, evaluating and verifying a preset optical center to determine a final optical center. Therefore, the optical center test method improves the accuracy of the optical center test in an anti-distortion correction mode, constructs an evaluation mode for evaluating the accuracy of the preset optical center, and can further improve the accuracy of the optical center test.

Description

Optical center testing method, optical center testing device and electronic equipment

Technical Field

The present disclosure relates to a camera module, and more particularly, to an optical center testing method and an optical center testing apparatus for a camera module, and an electronic device.

Background

With the popularization of mobile electronic devices, technologies related to camera modules used in mobile electronic devices for helping users acquire images (e.g., videos or images) have been rapidly developed and advanced, and in recent years, camera modules have been widely used in many fields such as medical treatment, security, industrial production, and the like.

The optical system of the camera module mainly comprises an optical lens and a photosensitive chip, imaging light rays pass through the optical lens of the optical lens and then reach the photosensitive chip, and a photosensitive area of the photosensitive chip receives the imaging light rays and then converts optical signals into electric signals and images through an imaging circuit.

In the imaging process, the optical center of the camera module (optical center of the optical lens) needs to be aligned with the center of the photosensitive area of the photosensitive chip, and the shift of the optical center causes the problems of partial image deletion of an initial image, the position shift of a characteristic part of the image and the like. Accordingly, the accuracy of the optical center test will affect the degree of reflection of the image on the real features of the subject. However, the conventional optical center test method has a problem of low test accuracy.

Therefore, a new optical center testing method is desired to improve the accuracy of the optical center testing.

Disclosure of Invention

One advantage of the present application is to provide an optical center testing method, an optical center testing apparatus, and an electronic device, wherein the optical center testing method improves the accuracy of an optical center test by performing an inverse distortion correction.

Another advantage of the present application is to provide an optical center testing method, an optical center testing apparatus, and an electronic device, wherein the optical center testing method constructs an evaluation manner for evaluating accuracy of a preset optical center, and can determine a final optical center by using the evaluation manner to improve accuracy of an optical center test.

To achieve at least one of the above advantages or other advantages and objects, according to one aspect of the present application, there is provided an optical center testing method including:

step 1: acquiring a target image of a test target, wherein the test target comprises a plurality of feature points with equal intervals;

step 2: identifying the plurality of feature points from the target image;

and step 3: presetting an optical center and respectively calculating Euclidean distances between the optical center and the plurality of characteristic points;

and 4, step 4: generating an anti-distortion distance coefficient based on Euclidean distances between the optical center and the plurality of feature points;

and 5: transforming the target image into an anti-distortion image domain based on Euclidean distances between the optical center and the plurality of feature points and the anti-distortion distance coefficient to respectively obtain corresponding anti-distortion coordinates of the plurality of feature points in the anti-distortion image domain;

step 6: generating a characteristic value for representing the distribution uniformity of the plurality of characteristic points in the anti-distortion image domain based on the Euclidean distance between each characteristic point in the plurality of characteristic points and other characteristic points in the anti-distortion image domain; and

and 7: presetting a new optical center and iteratively executing the steps 3 to 6 to obtain a plurality of characteristic values, and determining the optical center corresponding to the minimum one of the characteristic values as the final optical center.

In the optical center testing method according to the present application, generating a feature value indicating a degree of uniformity of distribution of each of the plurality of feature points in the undistorted image domain based on a euclidean distance between each of the plurality of feature points and other feature points in the undistorted image domain includes: determining a plurality of first distance characterizing values based on the Euclidean distance between each feature point in the plurality of feature points and at least two other feature points in the anti-distortion image domain, wherein each first distance characterizing value is used for characterizing the average level of the Euclidean distance between each feature point and each feature point in a test group formed by each feature point and at least two other feature points in the anti-distortion image domain; determining a plurality of second distance-characterizing values based on the plurality of first distance-characterizing values, wherein each of the second distance-characterizing values is used for characterizing a difference between each two of the first distance-characterizing values; and determining a characteristic value for representing the distribution uniformity of the plurality of characteristic points in the anti-distortion image domain based on the plurality of second distance characterization values.

In the optical center testing method according to the present application, each of the first pitch characterizing values is a median of at least two pitches of each feature point in the anti-distortion image domain and between at least two other feature points.

In the optical center testing method according to the present application, each of the second distance characteristic values is an absolute value of a difference between each two of the first distance characteristic values.

In the optical center testing method according to the present application, the characteristic value is a minimum value among the plurality of second pitch characterizing values.

In the optical center testing method according to the present application, the characteristic value is an average value of the plurality of second interval characterization values.

In the optical center testing method according to the present application, the coordinates of the ith feature point are (Xi, Yi), the coordinates of the preset optical center are (Cx, Cy), one optical center is preset, and euclidean distances between the optical center and the plurality of feature points are respectively calculated, including: calculating Euclidean distances between the optical center and the plurality of feature points by the following formula: di ═ sqrt ((Xi-Cx) × (Xi-Cx) + (Yi-Cy) × (Yi-Cy)), where Di represents the euclidean distance between the optical center and the i-th feature point; wherein generating an anti-distortion distance coefficient based on Euclidean distances between the optical center and the plurality of feature points comprises: calculating the anti-distortion distance coefficient by the following formula: ri ═ abs ((K1 × pow (Di, (n-1)) + K2 × pow (Di, (n-2)) + … … + K (n-1) × pow (Di,1) + Kn), where Ri denotes the i-th inverse distortion distance coefficient corresponding to the Euclidean distance between the optical center and the i-th feature point, and K1, K2, … …, K (n-1), Kn denote n-number of inverse distortion parameters.

According to another aspect of the present application, there is provided an optical center testing apparatus, comprising:

an image acquisition unit for performing step 1: obtaining a target image of a test target, wherein the test target comprises a plurality of feature points with equal intervals;

a feature point identification unit, configured to perform step 2: identifying the plurality of feature points from the target image;

a first distance determination unit for performing step 3: presetting an optical center and respectively calculating Euclidean distances between the optical center and the plurality of characteristic points;

a second distance determination unit for performing step 4: generating an anti-distortion distance coefficient based on Euclidean distances between the optical center and the plurality of feature points;

an image domain transformation unit for performing step 5: transforming the target image into an anti-distortion image domain based on Euclidean distances between the optical center and the plurality of feature points and the anti-distortion distance coefficient to respectively obtain corresponding anti-distortion coordinates of the plurality of feature points in the anti-distortion image domain;

an evaluation unit for performing step 6: generating a characteristic value for representing the distribution uniformity of the plurality of characteristic points in the anti-distortion image domain based on the Euclidean distance between each characteristic point in the plurality of characteristic points and other characteristic points in the anti-distortion image domain; and

an authentication unit for performing step 7: presetting a new optical center and iteratively executing the steps 3 to 6 to obtain a plurality of characteristic values, and determining the optical center corresponding to the minimum one of the characteristic values as the final optical center.

In the optical center testing apparatus according to the present application, the evaluation unit is further configured to: determining a plurality of first distance characterizing values based on the Euclidean distance between each feature point in the plurality of feature points and at least two other feature points in the anti-distortion image domain, wherein each first distance characterizing value is used for characterizing the average level of the Euclidean distance between each feature point and each feature point in a test group formed by each feature point and at least two other feature points in the anti-distortion image domain; determining a plurality of second pitch-characterizing values based on the plurality of first pitch-characterizing values, wherein each of the second pitch-characterizing values is used for characterizing a difference between each two of the first pitch-characterizing values; and determining a characteristic value for representing the distribution uniformity of the plurality of characteristic points in the anti-distortion image domain based on the plurality of second distance characterization values.

According to yet another aspect of the present application, there is provided an electronic device including:

a memory; and

a processor having stored in the memory computer program instructions which, when executed by the processor, cause the processor to perform the optical core testing method as described above.

Further objects and advantages of the present application will become apparent from an understanding of the ensuing description and drawings.

These and other objects, features and advantages of the present application will become more fully apparent from the following detailed description, the accompanying drawings and the claims.

Drawings

These and/or other aspects and advantages of the present application will become more apparent and more readily appreciated from the following detailed description of the embodiments of the present application, taken in conjunction with the accompanying drawings of which:

FIG. 1 illustrates a flow chart of a method of optical core testing according to an embodiment of the present application.

FIG. 2 illustrates a schematic diagram of a target according to an embodiment of the present application.

FIG. 3 illustrates a schematic diagram of a reticle image according to an embodiment of the present application.

FIG. 4 illustrates a schematic diagram of an ideal, anti-distorted image according to an embodiment of the present application.

Detailed Description

The following description is presented to disclose the application and to enable any person skilled in the art to practice the application. The embodiments in the following description are given by way of example only, and other obvious variations will occur to those skilled in the art. The underlying principles of the application, as defined in the following description, may be applied to other embodiments, variations, modifications, equivalents, and other technical solutions without departing from the spirit and scope of the application.

Summary of the application

As described above, in the imaging process, the optical center of the camera module (optical center of the optical lens) needs to be aligned with the center of the photosensitive area of the photosensitive chip, and the shift of the optical center causes problems such as missing of a partial image of the initial image, and shift of the position of a characteristic portion of the image. Accordingly, the accuracy of the optical center test will affect the degree of reflection of the image on the real features of the subject. However, the conventional optical center test method has a problem of low test accuracy.

Specifically, the conventional optical center testing method mainly includes a light source method and a mark method. The light source method mainly determines the optical center of the camera module through the point with the strongest light induction of the light-sensitive chip. The mark method mainly determines the optical center of the camera module by determining the center of the characteristic point of the target image and the corresponding position of the photosensitive chip.

The light source method is limited by the uniformity of incident light, and when the incident light is not uniform, the accuracy of the optical center determined by the point with the strongest light induction of the photosensitive chip is lower. In addition, the light source method is limited by the testing distance, and when the testing target is far away, the testing difficulty of the optical center is increased, and the precision is reduced.

The mark method is limited by the prior calibration of the measurement system for testing the optical center, and has extremely high requirements on the position accuracy of the measurement system, for example, the plane offset and the angle offset between the test platform and the target plate of the test system have great influence on the test result. In addition, in practical application, due to the inherent characteristics of the optical lens of the camera module, the initial image collected by the camera module is inevitably distorted, so that image distortion is caused, and the accuracy of the optical center of the camera module determined by the center of the characteristic point of the target image and the corresponding position of the photosensitive chip is further reduced.

The inventor of the application carries out distortion correction on the initial image through anti-distortion correction to obtain an image which can reflect the real characteristics of a shot object as much as possible, and determines the position of the optical center to improve the test accuracy of the optical center.

Based on this, the present application provides an optical center testing method, which includes: step 1: obtaining a target image of a test target, wherein the test target comprises a plurality of feature points with equal intervals; step 2: identifying the plurality of feature points from the target image; and 3, step 3: presetting an optical center and respectively calculating Euclidean distances between the optical center and the plurality of characteristic points; and 4, step 4: generating an anti-distortion distance coefficient based on Euclidean distances between the optical center and the plurality of feature points; and 5: transforming the target image into an anti-distortion image domain based on Euclidean distances between the optical center and the plurality of feature points and the anti-distortion distance coefficient to respectively obtain corresponding anti-distortion coordinates of the plurality of feature points in the anti-distortion image domain; step 6: generating a characteristic value for representing the distribution uniformity of the plurality of characteristic points in the anti-distortion image domain based on the Euclidean distance between each characteristic point in the plurality of characteristic points and other characteristic points in the anti-distortion image domain; and, step 7: presetting a new optical center and iteratively executing the steps 3 to 6 to obtain a plurality of characteristic values, and determining the optical center corresponding to the minimum one of the characteristic values as the final optical center.

Moreover, the present application also provides an optical center testing apparatus, which includes: an image acquisition unit for performing step 1: obtaining a target image of a test target, wherein the test target comprises a plurality of feature points with equal intervals; a feature point identification unit, configured to perform step 2: identifying the plurality of feature points from the target image; a first distance determination unit for performing step 3: presetting an optical center and respectively calculating Euclidean distances between the optical center and the plurality of characteristic points; a second distance determination unit for performing step 4: generating an anti-distortion distance coefficient based on Euclidean distances between the optical center and the plurality of feature points; an image domain transformation unit for performing step 5: transforming the target image into an anti-distortion image domain based on Euclidean distances between the optical center and the plurality of feature points and the anti-distortion distance coefficient to respectively obtain corresponding anti-distortion coordinates of the plurality of feature points in the anti-distortion image domain; an evaluation unit for performing step 6: generating a characteristic value for representing the distribution uniformity of the plurality of characteristic points in the anti-distortion image domain based on the Euclidean distance between each characteristic point in the plurality of characteristic points and other characteristic points in the anti-distortion image domain; and a verification unit for performing step 7: presetting a new optical center and iteratively executing the steps 3 to 6 to obtain a plurality of characteristic values, and determining the optical center corresponding to the minimum one of the characteristic values as the final optical center.

The present application also provides an electronic device, which includes: a memory; and a processor having stored in the memory computer program instructions which, when executed by the processor, cause the processor to perform the optical core testing method as described above.

Having described the general principles of the present application, various non-limiting embodiments of the present application will now be described with reference to the accompanying drawings.

Exemplary Stent

As shown in fig. 1 to 4, an optical center test method according to an embodiment of the present application is illustrated. As shown in fig. 1, the optical center testing method includes: step 1, obtaining a target image of a test target, wherein the test target comprises a plurality of feature points with equal intervals; step 2, identifying the plurality of feature points from the target image; step 3, presetting an optical center and respectively calculating Euclidean distances between the optical center and the plurality of characteristic points; step 4, generating an anti-distortion distance coefficient based on Euclidean distances between the optical center and the plurality of feature points; step 5, transforming the target image into an inverse distortion image domain based on Euclidean distances between the optical center and the plurality of feature points and the inverse distortion distance coefficient so as to respectively obtain corresponding inverse distortion coordinates of the plurality of feature points in the inverse distortion image domain; step 6, generating a characteristic value for representing the distribution uniformity of the plurality of characteristic points in the anti-distortion image domain based on the Euclidean distance between each characteristic point in the plurality of characteristic points and other characteristic points in the anti-distortion image domain; and 7, presetting a new optical center, iteratively executing the steps 3 to 6 to obtain a plurality of characteristic values, and determining the optical center corresponding to the minimum one of the characteristic values as the final optical center.

In step 1, a target image of a test target is obtained. Specifically, as shown in fig. 2, the test target includes a plurality of feature points that are equally spaced from each other, that is, the spacing between every two adjacent feature points is equal to the same value. In the embodiment of the present application, the plurality of feature points have the same shape, and preferably, the shape of the feature point is a centrosymmetric shape. The plurality of feature points are uniformly distributed in at least two regions of the target, the at least two regions being symmetric with respect to a geometric center of the target.

As described above, due to the inherent characteristics of the optical lens of the camera module, the reticle image collected by the camera module is inevitably distorted, resulting in image distortion, as shown in fig. 3. In order to acquire an image that can reflect the true features of a target (i.e., a subject) as much as possible, the image needs to be corrected. In the embodiment of the application, the corrected image is obtained in an anti-distortion correction mode, and the position of the optical center is determined, so that the accuracy of the optical center test is improved.

In the process of acquiring a corrected image by means of inverse distortion correction, the target image needs to be transformed into an inverse distortion image domain. Specifically, first, a plurality of feature points need to be identified; then, acquiring Euclidean distances between the characteristic points in the target plate image and a preset optical center; then, converting Euclidean distances between the characteristic points in the target image and a preset optical center into an inverse distortion domain to obtain an inverse distortion distance coefficient; then, obtaining corresponding anti-distortion coordinates of the plurality of feature points in the anti-distortion image domain through the Euclidean distance and the anti-distortion distance coefficient so as to realize the transformation from the target image to the anti-distortion image domain.

Accordingly, first, in step 2, the plurality of feature points are identified from the target image. The shape of the plurality of feature points in the reticle image is distorted relative to the shape in the reticle, and the relative position of the plurality of feature points in the reticle image changes relative to the relative position in the reticle, as shown in fig. 3.

Then, in step 3, an optical center is preset and euclidean distances between the optical center and the plurality of feature points are respectively calculated. Specifically, the coordinates of the ith feature point in the reticle image are (Xi, Yi), the coordinates of the preset optical center are (Cx, Cy), and the euclidean distance between the optical center and the ith feature point in the reticle image is represented by Di. The euclidean distances between the optical center and the plurality of feature points may be calculated by the following formula: di ═ sqrt ((Xi-Cx) × (Xi-Cx) + (Yi-Cy) × (Yi-Cy)), where sqrt ((Xi-Cx) × (Xi-Cx) + (Yi-Cy) × (Yi-Cy)) represents a value obtained by cutting ((Xi-Cx) × (Xi-Cx) + (Yi-Cy) (-Yi-Cy)).

Correspondingly, step 3, presetting an optical center and respectively calculating euclidean distances between the optical center and the plurality of feature points, includes:

calculating Euclidean distances between the optical center and the plurality of feature points by the following formula: di ═ sqrt ((Xi-Cx) × (Xi-Cx) + (Yi-Cy) × (Yi-Cy)), where Di represents the euclidean distance between the optical center and the i-th feature point.

It is worth mentioning that, in the embodiment of the present application, in the process of correcting the target image by means of inverse distortion correction, a preset optical center is used to realize the transformation of the target image into the inverse distortion image domain. That is, the predetermined optical center is not necessarily the final optical center, and the position of the optical center is predetermined several times, and the predetermined optical center is evaluated to determine the final optical center. Accordingly, the optical center testing method of the embodiment of the application constructs an evaluation mode for evaluating the accuracy of the preset optical center, and the final optical center can be determined by using the evaluation mode. This section will be developed in the detailed description of the evaluation mode.

Then, in step 4, an anti-distortion distance coefficient is generated based on the euclidean distances between the optical center and the plurality of feature points. The anti-distortion distance coefficient may specifically be calculated by the following formula: ri ═ abs ((K1 × (Di), (n-1)) + K2 × (Di, (n-2)) + … … + K (n-1) × (Di,1) + Kn), wherein Ri represents the i-th inverse distortion distance coefficient corresponding to the Euclidean distance between the optical center and the i-th feature point, K1, K2, … …, K (n-1), Kn represent the 1 st, 2 nd, … … th, (n-1) th, n-th inverse distortion parameters, pow (Di, (n-1)) represents the (n-1) th power of Di, pow (Di, (n-2) represents the (n-2) th power of Di, pow (Di,1) represents the 1 st power of ABs ((K1 × (Di, (n-1) × pow (Di), (n-1)) + K28 (n-38n-1) + (K-38n-58) + K-1 (58), 1) + Kn represents the absolute value of ((K1 + pow (Di, (n-1)) + K2 + pow (Di, (n-2)) + … … + K (n-1) + pow (Di,1) + Kn).

That is, step 4, generating an anti-distortion distance coefficient based on euclidean distances between the optical center and the plurality of feature points, includes:

calculating the anti-distortion distance coefficient by the following formula: ri ═ abs ((K1 × pow (Di, (n-1)) + K2 × pow (Di, (n-2)) + … … + K (n-1) × pow (Di,1) + Kn), where Ri denotes the i-th inverse distortion distance coefficient corresponding to the Euclidean distance between the optical center and the i-th feature point, and K1, K2, … …, K (n-1), Kn denote n-number of inverse distortion parameters.

It is worth mentioning that the inverse distortion distance coefficient is obtained by calculating an inverse distortion model, and the number of the inverse distortion parameters and the value of the inverse distortion parameters are determined according to the inverse distortion model.

In a specific example of the present application, the number of the anti-distortion parameters is 5. Correspondingly, step 4, generating an anti-distortion distance coefficient based on the euclidean distances between the optical center and the plurality of feature points, includes:

calculating the anti-distortion distance coefficient by the following formula: ri ═ abs ((K1 × pow (Di,4) + K2 × pow (Di,3) + K3 × pow (Di,2) + K4 × pow (Di,1) + K5), where Ri denotes the i-th inverse distortion distance coefficient corresponding to the euclidean distance between the optical center and the i-th feature point, and K1, K2, K3, K4, K5 denote 5 inverse distortion parameters.

Next, in step 5, the reticle image is transformed into an inverse distorted image domain based on the euclidean distances between the optical center and the plurality of feature points and the inverse distorted distance coefficients to obtain corresponding inverse distorted coordinates of the plurality of feature points in the inverse distorted image domain, respectively. Specifically, the corresponding anti-distortion coordinates of the plurality of feature points in the anti-distortion image domain can be obtained according to the functional relationship between the euclidean distance between the optical center and the plurality of feature points and the anti-distortion distance coefficient.

In a specific embodiment of the present application, the corresponding anti-distortion coordinates of the plurality of feature points in the anti-distortion image domain may be obtained according to a ratio between the euclidean distance between the optical center and the plurality of feature points and the anti-distortion distance coefficient. It should be understood that, the corresponding inverse distortion coordinates of the plurality of feature points in the inverse distortion image domain may also be obtained according to other functional relationships between the euclidean distances between the optical center and the plurality of feature points and the inverse distortion distance coefficients, which is not limited by this application.

In the embodiment of the present application, the target image may be transformed into the anti-distortion image domain through steps 2 to 5. As described above, in the embodiment of the present application, in the process of correcting the target image by means of the anti-distortion correction, the preset optical center is used to realize the transformation of the target image into the anti-distortion image domain. That is, the predetermined optical center is not necessarily the final optical center, and the position of the optical center is predetermined several times, and the predetermined optical center is evaluated to determine the final optical center. The optical center testing method provided by the embodiment of the application establishes an evaluation mode for evaluating the accuracy of the preset optical center, and can determine the final optical center by utilizing the evaluation mode so as to improve the accuracy of the optical center testing.

Specifically, in theory, when the precision of the preset optical center is high, under the preset condition, the distribution features of the plurality of feature points in the anti-distortion image domain should be close to the distribution features of the plurality of feature points on the target, that is, the mutual distances are equal, as shown in fig. 4. Therefore, in the embodiment of the present application, the precision of the preset optical center is evaluated by the distribution uniformity of the plurality of feature points in the anti-distortion image domain.

In step 6, a feature value representing the degree of uniformity of the distribution of the plurality of feature points in the undistorted image domain is generated based on the euclidean distance between each of the plurality of feature points and the other feature points in the undistorted image domain.

In a specific example of the present application, first, a plurality of first distance characterization values are determined based on the euclidean distance between each feature point in the plurality of feature points and at least two other feature points spaced from the feature point in the undistorted image domain, where the number of feature points spaced from the at least two other feature points may be 0, 1, 2, or other values, and when the number of feature points spaced from the at least two other feature points is 0, it indicates that the at least two other feature points are adjacent to the feature point, and each first distance characterization value is used to characterize an average level of the euclidean distances between each feature point and each of the feature points in the test group formed by the at least two other feature points in the undistorted image domain; then, determining a plurality of second distance characterization values based on the plurality of first distance characterization values, wherein each second distance characterization value is used for characterizing the difference between every two first distance characterization values; then, a feature value representing the distribution uniformity of the plurality of feature points in the anti-distortion image domain is determined based on the plurality of second distance characterization values.

Accordingly, step 6, comprises: determining a plurality of first distance characterization values based on Euclidean distances between each feature point in the plurality of feature points and at least two other feature points in the anti-distortion image domain, wherein each first distance characterization value is used for characterizing the average level of the Euclidean distances between each feature point and each feature point in a test group formed by each feature point and at least two other feature points in the anti-distortion image domain

(ii) a Determining a plurality of second distance-characterizing values based on the plurality of first distance-characterizing values, wherein each of the second distance-characterizing values is used for characterizing a difference between each two of the first distance-characterizing values; and determining a characteristic value for representing the distribution uniformity of the plurality of characteristic points in the anti-distortion image domain based on the plurality of second distance characterization values.

Specifically, in one embodiment, each of the first-interval-characterizing values is represented by a median of at least two intervals between each of the feature points in the undistorted image domain and at least two other of the feature points. That is, each of the first pitch characterizing values is a median of at least two pitches of each feature point in the undistorted image domain and between at least two other of the feature points.

It should be understood that the first pitch-characterizing value may also be represented by other values capable of characterizing an average level of euclidean distances between each feature point in the undistorted image domain and each of the feature points in the test set of at least two other feature points, for example, an average of at least two pitches between each feature point in the undistorted image domain and each of the other at least two feature points, which is not limited by the present application.

In this particular embodiment, each of the second distance characterising values is represented by the absolute value of the difference between each two of the first distance characterising values (i.e. the difference between the average levels of euclidean distances between the respective feature points in each of the two test sets). That is, each of the second distance-characterizing values is an absolute value of a difference between each two of the first distance-characterizing values.

It should be understood that the second distance characteristic value may be represented by other values capable of characterizing the difference between every two first distance characteristic values, for example, the absolute value of the difference between the ratio of every two first distance characteristic values and 1, which is not limited in this application.

In this embodiment, the minimum value of the second distance characterization values (i.e., the minimum value of the difference between the average levels of the euclidean distances between the feature points in each of the two test sets) is used to represent the distribution uniformity of the feature points in the anti-distortion image domain obtained under the preset condition (optical center). That is, the characteristic value is an average value of the plurality of second pitch characterizing values.

It should be understood that other values may be used to represent the distribution uniformity of the plurality of feature points in the undistorted image domain obtained under the preset condition (optical center), for example, the average value of the plurality of second distance characterization values. Accordingly, in another specific embodiment of the present application, the characteristic value is an average value of the plurality of second pitch characterizing values.

In step 7, a new optical center is preset and steps 3 to 6 are iteratively performed to obtain a plurality of characteristic values, and the optical center corresponding to the minimum one of the plurality of characteristic values is determined as the final optical center. That is, the testing precision of the optical center is improved by presetting a new optical center and evaluating the precision of a plurality of preset optical centers to verify whether the preset optical center is the final optical center.

In summary, the optical center testing method is clarified, the optical center testing method improves the accuracy of the optical center testing in an anti-distortion correction manner, and an evaluation manner for evaluating the accuracy of the preset optical center is constructed to further improve the accuracy of the optical center testing.

Exemplary optical center testing device

According to another aspect of the present application, there is also provided an optical center testing apparatus, which includes: the device comprises an image acquisition unit, a characteristic point identification unit, a first distance determination unit, a second distance determination unit, an image domain transformation unit, an evaluation unit and a verification unit.

Specifically, the image acquisition unit is configured to perform step 1: obtaining a target image of a test target, wherein the test target comprises a plurality of feature points with equal intervals;

the feature point identifying unit is configured to perform step 2: the plurality of feature points are identified from the reticle image.

The first distance determination unit is configured to perform step 3: presetting an optical center and respectively calculating Euclidean distances between the optical center and the plurality of characteristic points.

The second distance determination unit is configured to perform step 4: and generating an anti-distortion distance coefficient based on Euclidean distances between the optical center and the plurality of feature points.

The image domain transformation unit is configured to perform step 5: and transforming the target image into an anti-distortion image domain based on Euclidean distances between the optical center and the plurality of feature points and the anti-distortion distance coefficient so as to respectively obtain corresponding anti-distortion coordinates of the plurality of feature points in the anti-distortion image domain.

The evaluation unit is configured to perform step 6: and generating a characteristic value for representing the distribution uniformity of the plurality of characteristic points in the anti-distortion image domain based on the Euclidean distance between each characteristic point in the plurality of characteristic points and other characteristic points in the anti-distortion image domain.

In particular, the evaluation unit is further configured to: determining a plurality of first distance characterizing values based on the Euclidean distance between each feature point in the plurality of feature points and at least two other feature points in the anti-distortion image domain, wherein each first distance characterizing value is used for characterizing the average level of the Euclidean distance between each feature point and each feature point in a test group formed by each feature point and at least two other feature points in the anti-distortion image domain; determining a plurality of second distance-characterizing values based on the plurality of first distance-characterizing values, wherein each of the second distance-characterizing values is used for characterizing a difference between each two of the first distance-characterizing values; and determining a characteristic value for representing the distribution uniformity of the plurality of characteristic points in the anti-distortion image domain based on the plurality of second distance characteristic values.

The verification unit is configured to perform step 7: presetting a new optical center and iteratively executing the steps 3 to 6 to obtain a plurality of characteristic values, and determining the optical center corresponding to the minimum one of the characteristic values as the final optical center.

Here, steps 1 to 7 have been described in detail in the above description of the optical center testing method illustrated with reference to fig. 1 to 4, and thus, a repetitive description thereof will be omitted.

In summary, the optical center testing device is illustrated, which can improve the accuracy of optical center testing by an optimized optical center testing method.

Exemplary embodiments of the inventionElectronic device

According to yet another aspect of the present application, there is also provided an electronic device including: a memory in which are stored computer program instructions which, when executed by the processor, cause the processor to perform the optical centre testing method illustrated with reference to figures 1 to 4. Here, steps 1 to 7 have been described in detail in the above description of the optical center testing method illustrated with reference to fig. 1 to 4, and thus, a repetitive description thereof will be omitted.

In summary, the electronic device is stated that can perform an optimized optical center testing method to improve the accuracy of the optical center testing.

Exemplary target

According to yet another aspect of the present application, there is also provided a test target, as shown in fig. 2, which includes a substrate and a plurality of first test patterns (first feature points) disposed on the substrate and having equal mutual intervals, that is, every two adjacent first test patterns have equal intervals.

In the embodiment of the present application, the plurality of first test patterns have the same shape, and preferably, the shape of the first test pattern is a centrosymmetric shape. In one specific example of the present application, the shape of the first test pattern is a circle, and in other specific examples, the shape of the first test pattern may be other shapes. The plurality of first test patterns are uniformly distributed in at least two areas of the target, and the at least two areas are symmetrical relative to the geometric center of the target.

It is worth mentioning that the test target can also be used for testing a Spatial Frequency Response (SFR) test of the camera module. Correspondingly, the target further comprises a plurality of second test patterns with equal mutual spacing of second test patterns (second feature points) for space frequency response testing, wherein the substrate is provided with at least one substrate edge, the second test patterns are provided with at least one test edge, and the at least one test edge is inclined relative to the at least one substrate edge.

Specifically, the plurality of second test patterns includes a central test pattern distributed in a central region of the target and a plurality of peripheral test patterns symmetrically distributed with respect to a center of the target, wherein a center of the central test pattern is aligned with a center of the target.

It is worth mentioning that the test target can be used for space frequency response test and optical center test, and the design can reduce the influence of machine station difference on the test result and improve the test accuracy. In the packaging process of the camera module, firstly, the test target is used for correcting the tilt (tilt) of the spatial frequency response, and then active calibration is carried out according to the relative positions of the optical center (distortion center) and the photosensitive chip, so that the distortion center is aligned with the center of the photosensitive chip.

In summary, the test target is clarified, and the test target can reduce the influence of machine station difference on the space frequency response test and the optical center test, and improve the test precision.

It will be appreciated by persons skilled in the art that the embodiments of the present application described above and illustrated in the drawings are given by way of example only and are not limiting of the present application. The objectives of the present application have been fully and effectively attained. The functional and structural principles of the present application have been shown and described in the examples, and any variations or modifications of the embodiments of the present application may be made without departing from the principles.

Claims (10)

1. An optical center testing method, comprising:

step 1: obtaining a target image of a test target, wherein the test target comprises a plurality of feature points with equal intervals;

and 2, step: identifying the plurality of feature points from the target image;

and step 3: presetting an optical center and respectively calculating Euclidean distances between the optical center and the plurality of characteristic points;

and 4, step 4: generating an anti-distortion distance coefficient based on Euclidean distances between the optical center and the plurality of feature points;

and 5: transforming the target image into an anti-distortion image domain based on Euclidean distances between the optical center and the plurality of feature points and the anti-distortion distance coefficient to respectively obtain corresponding anti-distortion coordinates of the plurality of feature points in the anti-distortion image domain;

step 6: generating a characteristic value representing the distribution uniformity of the plurality of characteristic points in the anti-distortion image domain based on the Euclidean distance between each characteristic point in the plurality of characteristic points and other characteristic points in the anti-distortion image domain; and

and 7: presetting a new optical center and iteratively executing the steps 3 to 6 to obtain a plurality of characteristic values, and determining the optical center corresponding to the minimum one of the characteristic values as the final optical center.

2. The optical center testing method according to claim 1, wherein generating a feature value representing a degree of uniformity of distribution of the plurality of feature points in the undistorted image domain based on euclidean distances between each feature point of the plurality of feature points and other feature points in the undistorted image domain comprises:

determining a plurality of first distance characterizing values based on the Euclidean distance between each feature point in the plurality of feature points and at least two other feature points in the anti-distortion image domain, wherein each first distance characterizing value is used for characterizing the average level of the Euclidean distance between each feature point and each feature point in a test group formed by each feature point and at least two other feature points in the anti-distortion image domain;

determining a plurality of second pitch-characterizing values based on the plurality of first pitch-characterizing values, wherein each of the second pitch-characterizing values is used for characterizing a difference between each two of the first pitch-characterizing values; and

determining a feature value representing the distribution uniformity of the plurality of feature points in the anti-distortion image domain based on the plurality of second distance characterization values.

3. The optical center testing method of claim 2, wherein each of the first pitch characterizing values is a median of at least two pitches of each feature point in the anti-distorted image domain and between at least two other of the feature points.

4. The optical-center testing method of claim 2, wherein each of the second-pitch-characterizing values is an absolute value of a difference between each two of the first-pitch-characterizing values.

5. The optical center testing method of claim 4, wherein the characteristic value is a minimum value of the plurality of second pitch characterizing values.

6. The optical center testing method of claim 4, wherein the characteristic value is an average of the plurality of second pitch characterizing values.

7. The optical center testing method of claim 1, wherein the coordinates of the ith feature point are (Xi, Yi), the coordinates of the preset optical center are (Cx, Cy), one optical center is preset, and euclidean distances between the optical center and the plurality of feature points are respectively calculated, and the method comprises:

calculating Euclidean distances between the optical center and the plurality of feature points by the following formula: di ═ sqrt ((Xi-Cx) × (Xi-Cx) + (Yi-Cy) × (Yi-Cy)), where Di represents the euclidean distance between the optical center and the i-th feature point;

wherein generating an anti-distortion distance coefficient based on Euclidean distances between the optical center and the plurality of feature points comprises:

calculating the anti-distortion distance coefficient by the following formula: ri ═ abs ((K1 × pow (Di, (n-1)) + K2 × pow (Di, (n-2)) + … … + K (n-1) × pow (Di,1) + Kn), where Ri denotes the i-th inverse distortion distance coefficient corresponding to the Euclidean distance between the optical center and the i-th feature point, and K1, K2, … …, K (n-1), Kn denote n-number of inverse distortion parameters.

8. An optical center testing apparatus, comprising:

an image acquisition unit for performing step 1: obtaining a target image of a test target, wherein the test target comprises a plurality of feature points with equal intervals;

a feature point identification unit, configured to perform step 2: identifying the plurality of feature points from the target image;

a first distance determination unit for performing step 3: presetting an optical center and respectively calculating Euclidean distances between the optical center and the plurality of characteristic points;

a second distance determination unit for performing step 4: generating an anti-distortion distance coefficient based on Euclidean distances between the optical center and the plurality of feature points;

an image domain transformation unit for performing step 5: transforming the target image into an anti-distortion image domain based on Euclidean distances between the optical center and the plurality of feature points and the anti-distortion distance coefficient to respectively obtain corresponding anti-distortion coordinates of the plurality of feature points in the anti-distortion image domain;

an evaluation unit for performing step 6: generating a characteristic value for representing the distribution uniformity of the plurality of characteristic points in the anti-distortion image domain based on the Euclidean distance between each characteristic point in the plurality of characteristic points and other characteristic points in the anti-distortion image domain; and

an authentication unit for performing step 7: presetting a new optical center and iteratively executing the steps 3 to 6 to obtain a plurality of characteristic values, and determining the optical center corresponding to the minimum one of the characteristic values as the final optical center.

9. The optical center testing device of claim 8, wherein the evaluation unit is further configured to:

determining a plurality of first distance characterizing values based on the Euclidean distance between each feature point in the plurality of feature points and at least two other feature points in the anti-distortion image domain, wherein each first distance characterizing value is used for characterizing the average level of the Euclidean distance between each feature point and each feature point in a test group formed by each feature point and at least two other feature points in the anti-distortion image domain;

determining a plurality of second distance-characterizing values based on the plurality of first distance-characterizing values, wherein each of the second distance-characterizing values is used for characterizing a difference between each two of the first distance-characterizing values; and

determining a feature value representing the distribution uniformity of the plurality of feature points in the anti-distortion image domain based on the plurality of second distance characterization values.

10. An electronic device, comprising:

a memory; and

a processor having stored in the memory computer program instructions which, when executed by the processor, cause the processor to perform the optical core testing method of any of claims 1 to 7.

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