CN111292344A

CN111292344A - Detection method of camera module

Info

Publication number: CN111292344A
Application number: CN201811494065.0A
Authority: CN
Inventors: 张倍铭; 赵保忠; 许世杰; 黄伟隆
Original assignee: Primax Electronics Ltd
Current assignee: Primax Electronics Ltd
Priority date: 2018-12-07
Filing date: 2018-12-07
Publication date: 2020-06-16

Abstract

The invention provides a detection method of a camera module, which is applied to the camera module with a camera lens and a photosensitive element, and comprises the following steps: (A) acquiring an original image by using a camera lens and a photosensitive element; (B) converting an original image into a gray image; (C) converting the gray image into a binary image according to a critical gray value; (D) obtaining boundary contours of a plurality of pixels in a binary image, wherein the gray value of the pixels is greater than or equal to a critical gray value; (E) obtaining a contour center of the boundary contour; and (F) judging whether the optical axis of the camera lens is opposite to the imaging center of the photosensitive element or not according to the imaging center and the outline center of the photosensitive element.

Description

Detection method of camera module

Technical Field

The invention relates to the field of optics, in particular to a detection method of a camera module.

Background

In recent years, with the evolution of the electronic industry and the vigorous development of industrial technology, the trend of designing and developing various electronic devices is gradually moving toward portable and easy-to-carry, so as to facilitate users to apply to mobile commerce, entertainment, leisure and other purposes anytime and anywhere. For example, various camera modules are widely applied to various fields, such as the field of portable electronic devices, such as smart phones and wearable electronic devices, and have the advantages of small size and portability, so that people can take out images at any time when in use, acquire and store the images, or further upload the images to the internet through a mobile network, thereby not only having important commercial value, but also enabling the daily life of the general public to be more colorful. Of course, camera modules are widely used not only in the field of portable electronic devices but also in the field of vehicle electronics where safety is important.

Please refer to fig. 1, which is a conceptual diagram of a conventional camera module. The camera module 1 includes a camera lens 11 and a photosensitive element 12, the photosensitive element 12 is used for sensing an external light beam passing through the camera lens 11 and projected thereon to obtain an image, wherein whether an optical axis 111 of the camera lens 11 can be aligned with an imaging center 121 of the photosensitive element 12 is an important key for affecting the imaging quality of the camera module 1. Therefore, how to effectively detect whether the optical axis 111 of the camera lens 11 is aligned with the imaging center 121 of the photosensitive element 12 in the production and assembly processes of the camera module 1 has become an issue to be researched.

Disclosure of Invention

The present invention is directed to a method for detecting a camera module, and more particularly to a method for detecting whether an optical axis of a camera lens is aligned with an imaging center of a photosensitive element.

In a preferred embodiment, the present invention provides a method for detecting a camera module, which is applied to a camera module having a camera lens and a photosensitive element, and includes:

(A) acquiring an original image by using the camera lens and the photosensitive element;

(B) converting the original image into a gray scale image (gray scale image);

(C) converting the gray image into a binary image (binary image) according to a threshold gray value;

(D) obtaining a boundary contour of a plurality of pixels which are greater than or equal to (greater than or equal to) the critical gray value in the binary image;

(E) obtaining a contour center of the boundary contour; and

(F) and judging whether an optical axis of the camera lens is aligned with the imaging center of the photosensitive element or not according to the imaging center of the photosensitive element and the outline center.

Drawings

FIG. 1: is a conceptual diagram of an existing camera module.

FIG. 2: is a preferred method flowchart of the detection method of the camera module of the present invention.

FIG. 3: is a conceptual diagram of the original image acquired through step S1 shown in fig. 2.

FIG. 4: is a conceptual diagram illustrating the gray scale image obtained from the original image shown in fig. 3 through the step S2 shown in fig. 2.

FIG. 5: is a preferred execution flow chart of step S3 shown in fig. 2.

FIG. 6A: is a conceptual diagram of each gray scale value and the corresponding number of pixels in the gray scale image shown in fig. 4.

FIG. 6B: is a preferred cumulative distribution function plot for the gray scale image shown in fig. 4.

FIG. 7: the concept of converting the gray image shown in fig. 4 into a binary image through steps S31 and S32 shown in fig. 5 is illustrated.

FIG. 8: is a conceptual diagram for obtaining the boundary contour for the binary image shown in fig. 7 through step S4 shown in fig. 2.

FIG. 9: is a conceptual diagram illustrating the boundary contour shown in fig. 8 obtained the contour center through step S5 shown in fig. 2.

Wherein the reference numerals are as follows:

1 Camera Module

2 original image

3 Gray scale image

4 binary image

11 image pickup lens

12 photosensitive element

41 boundary profile

42 optical circle

43 center of contour

44 center of binary image

111 optical axis

121 center of imaging

Step S1

Step S2

Step S3

Step S4

Step S5

Step S6

Step S31

Step S32

Detailed Description

First, it is described that the detection method of the camera module of the present disclosure can be applied to the camera module 1 shown in fig. 1, and is applied to a production line of the camera module 1, generally, the light source density on the photosensitive element 12 is higher as approaching to the optical axis 111 of the camera lens 11, so the detection method of the camera module of the present disclosure uses the luminance values (Intensity) of a plurality of pixels on the photosensitive element 12 to find the position (optical center) on the photosensitive element 12 corresponding to the optical axis 111 of the camera lens 11, and then compares the position with the distance between the imaging center 121 of the photosensitive element 12 to determine whether the optical axis 111 of the camera lens 11 is aligned with the imaging center 121 of the photosensitive element 12. In a preferred embodiment, the photosensitive element 12 can be a Complementary Metal-Oxide-Semiconductor (CMOS) or a Charge Coupled Device (CCD), and the imaging center 121 is located at the center of the entire photosensitive element 12, but not limited thereto.

Please refer to fig. 2, which is a flowchart illustrating a preferred method of detecting a camera module according to the present invention. The detection method of the camera module comprises the following steps: step S1, acquiring an original image by using the camera lens and the photosensitive element; step S2, converting the original image into a gray scale image (gray scale image); step S3, converting the gray image into a binary image (binary image) according to a threshold gray value; step S4, obtaining a boundary contour of a plurality of pixels which are greater than or equal to (greater than or equal to) the critical gray value in the binary image; step S5, obtaining the contour center of the boundary contour; in step S6, it is determined whether the optical axis of the imaging lens is aligned with the imaging center of the photosensitive element according to the imaging center of the photosensitive element and the contour center of the boundary contour.

The following describes the steps S1 to S6 with a preferred embodiment, and is assisted by the contents shown in fig. 3 to 9. Fig. 3 shows the original image 2 obtained in step S1 shown in fig. 2, which may be an RGB type color image or a CMYK type color image. Fig. 4 is a gray scale image 3 obtained from the original image shown in fig. 3 through step S2 shown in fig. 2, wherein each pixel in the gray scale image 3 is represented by a gray scale value of 0-255, and the different gray scale values represent different brightness respectively.

Furthermore, fig. 5 illustrates a preferred execution flowchart of step S3 shown in fig. 2, which includes: step S31, obtaining a critical gray value corresponding to a specific coverage rate by using a Cumulative Distribution Function (CDF); in step S32, each pixel in the grayscale image that is greater than or equal to (≧) the critical grayscale value is classified as a high-luminance pixel, and each pixel in the grayscale image that is less than (<) the critical grayscale value is classified as a low-luminance pixel, so as to binarize the grayscale image.

Further, referring to fig. 6A and 6B, fig. 6A illustrates the number of pixels (vertical axis) corresponding to each gray level (horizontal axis) in the gray image, and the cumulative distribution function shown in fig. 6B can be obtained by performing step S31, where the cumulative distribution function is defined as: f_X(x) P (X ≦ X), P is the coverage, X is the grayscale value, and X is a random variable. In the preferred embodiment, the specific coverage is set to 0.4, but the practical application is not limited thereto, and as shown in fig. 6B, the threshold gray level value corresponding to the specific coverage 0.4 is 120, i.e., in the preferred embodiment, the threshold gray level value 120 can be obtained through the step S31 shown in fig. 5.

In addition, the cumulative distribution function is an integral of the probability density function, and can completely describe the probability distribution of a random variable X, which is known to those skilled in the art, and therefore will not be described herein again.

In the present preferred embodiment, step S32 is executed to convert the gray-scale image 3 shown in fig. 4 into the binary image 4 shown in fig. 7 by setting each pixel in the gray-scale image 3 that is greater than or equal to (≧) the critical gray-scale value 120 to the maximum gray-scale value (e.g., 255) and each pixel in the gray-scale image 3 that is less than (<) the critical gray-scale value 120 to the minimum gray-scale value (e.g., 0), wherein the pixel in the binary image 4 shown in fig. 7 that is set to the maximum gray-scale value (e.g., 255) is indicated by a black dot for clarity.

Please refer to fig. 8, which is a boundary contour of the binary image shown in fig. 7 obtained through the step S4 shown in fig. 2. In the preferred embodiment, step S4 is to obtain the boundary Contour 41 of a plurality of pixels set as the gray maximum (e.g. 255) in the binary image 4 by using an Active Contour Model (Active Contour Model); the active contour model, also called "Snakes", is a structure for extracting object contour lines from a two-dimensional image that may contain noise, and is well known in the art, and therefore, the description thereof is omitted here. Of course, the present disclosure is not limited to the boundary contour obtained by the active contour model, and those skilled in the art can make any equivalent design changes according to the actual application requirements.

Please refer to fig. 9, which illustrates the contour center of the boundary contour shown in fig. 8 obtained through the step S5 shown in fig. 2. In the preferred embodiment, step S5 is to obtain the optical circle 42 Fitting the boundary contour 41 by using an Ellipse Fitting Algorithm (elipse Fitting Algorithm) and use the center of the optical circle 42 as the contour center 43, and since the size of the binary image 4 corresponds to the size of the photosensitive element 12, the contour center 43 obtained in step S5 can represent the position (optical center) of the photosensitive element 12 corresponding to the optical axis 111 of the camera lens 11; the ellipse fitting algorithm is also known by those skilled in the art, and therefore will not be described herein. Of course, the disclosure is not limited to the use of ellipse fitting algorithm to obtain the contour center of the boundary contour, and those skilled in the art can make any equivalent design changes according to the actual application requirements.

Likewise, since the size of the binary image 4 corresponds to the size of the photosensitive element 12, the center 44 of the binary image 4 may represent the imaging center 121 of the photosensitive element 12. In the preferred embodiment, when the distance between the center 44 of the binary image 4 (representing the imaging center 121 of the photosensitive element 12) and the contour center 43 of the boundary contour 41 (representing the position of the photosensitive element 12 corresponding to the optical axis 111 of the camera lens 11) is within a predetermined distance, it is determined that the imaging center 121 of the photosensitive element 12 overlaps or is adjacent to the position of the photosensitive element 12 corresponding to the optical axis 111 of the camera lens 11, it is determined that the optical axis 111 of the camera lens 11 is aligned with the imaging center 121 of the photosensitive element 12, and conversely, when the distance between the center 44 of the binary image 4 (representing the imaging center 121 of the photosensitive element 12) and the contour center 43 of the boundary contour 41 (i.e. the position of the photosensitive element 12 corresponding to the optical axis 111 of the camera lens 11) is greater than or within a predetermined distance, it is determined that the optical axis 111 of the camera lens 11 is not aligned with the imaging center 121 of the photosensitive element 12, at this time, the camera lens 11 and the photosensitive element 12 need to be reassembled or corrected.

The above description is only a preferred embodiment of the present invention and is not intended to limit the scope of the present invention, so that other equivalent changes or modifications without departing from the spirit of the present invention are intended to be included in the appended claims.

Claims

1. A detection method of a camera module is applied to the camera module with a camera lens and a photosensitive element, and comprises the following steps:

(B) converting the original image into a gray scale image (gray scale image);

(E) obtaining a contour center of the boundary contour; and

2. The method for detecting a camera module according to claim 1, wherein the step (C) comprises:

(C1) the threshold gray level corresponding to a specific coverage rate is obtained by using a Cumulative Distribution Function (CDF).

3. The method for inspecting a camera module according to claim 2, wherein the specific cover ratio is 0.4.

4. The method for detecting a camera module according to claim 2, wherein the step (C) further comprises:

(C2) each pixel in the grayscale image that is greater than or equal to (≧) the threshold grayscale value is classified as a high-luminance pixel, and each pixel in the grayscale image that is less than (<) the threshold grayscale value is classified as a low-luminance pixel.

5. The method for detecting a camera module according to claim 1, wherein the step (D) comprises:

the boundary Contour is obtained using an Active Contour Model (Active Contour Model).

6. The method for detecting a camera module according to claim 1, wherein the step (E) comprises:

an Ellipse Fitting Algorithm (Ellipse Fitting Algorithm) is used to obtain an optical circle Fitting the boundary profile and a center of the optical circle is used as the profile center.

7. The method according to claim 1, wherein in the step (F), when the imaging center is overlapped with or adjacent to the contour center, the optical axis is determined to be aligned with the imaging center.

8. The method for inspecting a camera module according to claim 1, which is applied to a production line of the camera module.

9. The method as claimed in claim 1, wherein the photosensitive element is a Complementary Metal-Oxide-Semiconductor (CMOS) or a Charge Coupled Device (CCD).