阅读说明：本技术 一种检测方法与装置 (Detection method and device ) 是由 胡伟鹏 于 2019-09-18 设计创作，主要内容包括：本发明提供一种检测装置及方法,用于检测摄像模组异常,包括以下步骤：获取待测摄像模组对准光源装置摄取的光源图像；处理所述光源图像而获取光强成像图；根据所述光强成像图与预设光强成像图,判断所述摄像模组是否成像异常；在判定所述摄像模组为成像异常的情况下,根据所述光强成像图中的光强分布,获取所述摄像模组导致成像异常的异常类型。通过对光强图进行分析,进而检测出待测摄像模组是否异常及异常原因,提高了检测的精确度。(The invention provides a detection device and a detection method, which are used for detecting the abnormity of a camera module and comprise the following steps: acquiring a light source image shot by a camera module to be tested aiming at a light source device; processing the light source image to obtain a light intensity imaging graph; judging whether the camera module is abnormal in imaging or not according to the light intensity imaging graph and a preset light intensity imaging graph; and under the condition that the camera module is judged to be abnormal in imaging, acquiring the abnormal type of the abnormal imaging caused by the camera module according to the light intensity distribution in the light intensity imaging graph. Whether the camera module to be detected is abnormal or not and the reason of the abnormality are detected by analyzing the light intensity diagram, so that the detection accuracy is improved.)

1. A detection method is used for detecting a camera module and is characterized by comprising the following steps:

acquiring a light source image shot by a camera module to be tested aiming at a light source device;

processing the light source image to obtain a light intensity imaging graph;

judging whether the camera module is abnormal in imaging or not according to the light intensity imaging graph and a preset light intensity imaging graph;

and under the condition that the camera module is judged to be abnormal in imaging, acquiring the abnormal type of the abnormal imaging caused by the camera module according to the light intensity distribution in the light intensity imaging graph.

2. The method according to claim 1, wherein after the abnormal type of the abnormal imaging caused by the camera module is obtained according to the light intensity distribution in the light intensity image map when the camera module is determined to be abnormal imaging, the method further comprises the following steps:

processing the light intensity imaging graph to obtain a red light channel light intensity graph, a green light channel light intensity graph and a blue light channel light intensity graph; and

and determining an abnormal light channel and the position of the filtering structure of the camera module according to the red light channel light intensity diagram, the green light channel light intensity diagram and the blue light channel light intensity diagram.

3. The detection method according to claim 1, wherein the acquiring of the abnormal type of the imaging abnormality caused by the camera module comprises: and acquiring a first image defect of the light intensity imaging graph, and determining the corresponding abnormal type of the camera module according to the first image defect.

4. The inspection method according to claim 3, wherein the first image defect includes a light source shape defect, a light source edge dark line defect, and a light source internal dark line defect, the anomaly types include a first anomaly type, a second anomaly type, and a third anomaly type, the light source shape defect corresponds to the first anomaly type, the light source edge dark line defect corresponds to the second anomaly type, and the light source internal dark line defect corresponds to the third anomaly type,

the first abnormal type is position deviation between a lens and an image sensor, the second abnormal type is lens edge defect, and the third abnormal type is filtering structure abnormality.

5. The method as claimed in claim 1, wherein said determining whether the image of the camera module is abnormal according to the light intensity image and a predetermined light intensity image comprises: and matching the light intensity imaging graph with a preset light intensity graph, and judging that the camera module is abnormal in imaging when the matching degree is smaller than a set threshold value.

6. The utility model provides a detection device for detect the module of making a video recording, its characterized in that includes:

a light source device for generating detection light;

a processing apparatus, comprising:

the acquisition unit is used for acquiring a light source image shot by the camera module to be tested aiming at the light source device;

the first processing unit is used for processing the light source image to obtain a light intensity imaging image and judging whether the camera module is abnormal in imaging or not according to the light intensity imaging image and a preset light intensity imaging image; and under the condition that the camera module is judged to be abnormal in imaging, acquiring the abnormal type of the abnormal imaging caused by the camera module according to the light intensity distribution in the light intensity imaging graph.

7. The detecting device for detecting the rotation of a motor rotor as claimed in claim 6, wherein the processing device further comprises a second processing unit for processing the light intensity imaging graph to obtain a red light channel light intensity graph, a green light channel light intensity graph and a blue light channel light intensity graph; and determining abnormal light channels and positions thereof in the filtering structure of the camera module according to the red light channel light intensity diagram, the green light channel light intensity diagram and the blue light channel light intensity diagram.

8. The inspection device according to claim 6, wherein the first processing unit is configured to obtain a first image defect of the light intensity profile and determine the corresponding abnormal type of the camera module according to the first image defect.

9. The detecting device for detecting the abnormal imaging of the camera module according to claim 6, wherein the first processing unit is used for matching the light intensity image with a preset light intensity image, and when the matching degree is smaller than a set threshold value, the camera module is determined to be abnormal in imaging.

10. The detecting device for detecting the rotation of a motor rotor as claimed in claim 6, wherein the light source device includes a first light source, a second light source and a light source mixing component, the light source mixing component includes a light incident surface and a light emergent surface which are oppositely disposed, the first light source and the second light source are disposed toward the light incident surface of the light source mixing component, and the light source mixing component is configured to uniformly mix the light incident from the light incident surface of the first light source and the light incident from the second light source to form a uniform light beam and emit the uniform light beam from the light emergent surface.

Technical Field

The invention relates to the technical field of detection, in particular to a detection method and a detection device, which are used for detecting a camera module.

Background

Along with the development of technique and the requirement that should multiple field development, the module of making a video recording needs to be used in more and more fields.

The current detection method of the camera module is to determine whether the camera module is abnormal by using a Spatial Frequency Response (SFR) value. With the development of the technology, the detected SFR value can be converted into a thermodynamic diagram to judge the optical performance of the general position of the camera module more intuitively. However, the detected SFR values are detected by fixed-point detection in each field, and these predetermined detection points are not comprehensive, which easily causes missing detection and results in low detection accuracy.

Disclosure of Invention

In order to solve the above problem, embodiments of the present invention provide a method and a device for detecting a camera module, which can improve detection accuracy.

The invention provides a detection method for detecting the abnormity of a camera module, which comprises the following steps: acquiring a light source image shot by a camera module to be tested aiming at a light source device; processing the light source image to obtain a light intensity imaging graph; judging whether the camera module is abnormal in imaging or not according to the light intensity imaging graph and a preset light intensity imaging graph; and under the condition that the camera module is judged to be abnormal in imaging, acquiring the abnormal type of the abnormal imaging caused by the camera module according to the light intensity distribution in the light intensity imaging graph.

In an embodiment, after the abnormal type of the abnormal imaging caused by the camera module is obtained according to the light intensity distribution in the light intensity imaging graph under the condition that the camera module is determined to be abnormal in imaging, the detection method further includes the following steps: and processing the light intensity imaging graph to obtain a red light channel light intensity graph, a green light channel light intensity graph and a blue light channel light intensity graph. And determining an abnormal light channel and the position of the filtering structure of the camera module according to the red light channel light intensity diagram, the green light channel light intensity diagram and the blue light channel light intensity diagram.

In an embodiment, the obtaining of the abnormal type of the imaging abnormality caused by the camera module includes: and acquiring a first image defect of the light intensity imaging graph, and determining the corresponding abnormal type of the camera module according to the first image defect.

In an embodiment, the first image defect includes a light source shape defect, a light source edge dark line defect, and a light source internal dark line defect, the anomaly types include a first anomaly type, a second anomaly type, and a third anomaly type, the light source shape defect corresponds to the first anomaly type, the light source edge dark line defect corresponds to the second anomaly type, and the light source internal dark line defect corresponds to the third anomaly type. The first abnormal type is position deviation between a lens and an image sensor, the second abnormal type is lens edge defect, and the third abnormal type is filtering structure abnormality.

In one embodiment, the determining whether the image of the camera module is abnormal according to the light intensity image and a preset light intensity image includes: and matching the light intensity imaging graph with a preset light intensity graph, and judging that the camera module is abnormal in imaging when the matching degree is smaller than a set threshold value.

The invention also provides a detection device for detecting the camera module, which comprises a light source device and a processing device. And the light source device is used for generating detection light. The processing device comprises an acquisition unit and a first processing unit. And the acquisition unit is used for acquiring a light source image shot by the camera module to be tested and aiming at the light source device. The first processing unit is used for processing the light source image to obtain a light intensity imaging image, judging whether the camera module is abnormal in imaging according to the light intensity imaging image and a preset light intensity imaging image, and obtaining an abnormal type of imaging abnormality caused by the camera module according to light intensity distribution in the light intensity imaging image when the camera module is judged to be abnormal in imaging.

In an embodiment, the processing device further includes a second processing unit, configured to process the light intensity imaging graph to obtain a red light channel light intensity graph, a green light channel light intensity graph, and a blue light channel light intensity graph, and determine an abnormal channel and a position thereof in the filter structure of the camera module according to the red light channel light intensity graph, the green light channel light intensity graph, and the blue light channel light intensity graph.

In an embodiment, the first processing unit is configured to acquire a first image defect of the light intensity imaging graph, and determine an abnormal type of the corresponding camera module according to the first image defect.

In an embodiment, the first processing unit is configured to match the light intensity imaging graph with a preset light intensity graph, and when a matching degree is smaller than a set threshold, determine that the camera module is abnormal in imaging.

In an embodiment, the light source device includes a first light source, a second light source, and a light source mixing component, where the light source mixing component includes a light incident surface and a light emitting surface that are opposite to each other, the first light source and the second light source are disposed toward the light incident surface of the light source mixing component, and the light source mixing component is configured to uniformly mix light incident from the light incident surface of the first light source and the second light source to form a uniform light beam and emit the uniform light beam from the light emitting surface.

The detection method and the detection device provided by the invention are used for detecting the imaging performance of the camera module to be detected and the abnormal type causing imaging abnormity by analyzing the light intensity imaging graph. In addition, through the light intensity imaging graph, the imaging performance of the camera module and the part which causes imaging abnormity are reflected, the condition of missing detection caused by fixed-point detection of the SFR value is avoided, and the detection accuracy is improved.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.

Fig. 1 is a schematic structural diagram of a detection apparatus according to an embodiment of the present invention.

Fig. 2 is a schematic structural diagram of the camera module.

Fig. 3 is a schematic view of a first filtering structure of the camera module shown in fig. 2.

Fig. 4 is a schematic diagram of a sensor structure of the camera module shown in fig. 2.

FIG. 5a is a diagram of an image of a predetermined light intensity according to an embodiment of the present invention.

FIG. 5b is a light intensity image with a defect in the shape of the light source according to an embodiment of the present invention.

FIG. 5c is a light intensity image of a dark fringe defect with a light source edge according to an embodiment of the present invention.

FIG. 5d is a light intensity image of a dark streak defect inside a light source according to an embodiment of the present invention.

FIG. 6a is a graph of visible light intensity imaging provided in an embodiment of the present invention.

FIG. 6b is a diagram of the intensity of the red light channel according to an embodiment of the present invention.

FIG. 6c is a graph of the intensity of the first green channel according to one embodiment of the present invention.

FIG. 6d is a graph of the intensity of a second green channel according to one embodiment of the present invention.

Fig. 6e is a graph of the intensity of the blue light channel according to an embodiment of the invention.

Fig. 7 is a schematic diagram of the detection device detecting the imaging performance of the camera module.

Fig. 8 is a schematic flow chart of a detection method according to an embodiment of the present invention.

Fig. 9 is a schematic flow chart of a detection method according to another embodiment of the present invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

Referring to fig. 1, fig. 1 is a schematic structural diagram of a detection device according to a first embodiment of the present invention.

A detection device 100 is used for detecting a camera module 200. The detection apparatus 100 includes: a light source device 10 and a processing device 50. The light source device 10 is used to generate detection light. The processing device 50 is used for acquiring the light source image captured by the camera module 200 to be tested and aligning the light source image with the light source device 10, and processing the light source image to detect the imaging performance of the camera module 200. The processing device 50 is in communication with the camera module 200, so that the processing device 50 obtains the light source image captured by the camera module 200.

It should be understood that the communication connection between the processing device 50 and the camera module 200 is for transmitting the light source image captured by the camera module 200, and the connection between the processing device 50 and the camera module 200 is not limited, for example, the processing device 50 and the camera module 200 may be connected by a wired or wireless connection, such as a bluetooth connection or a data line connection.

Specifically, the light source device 10 includes a first light source 11, a second light source 13, and a light source mixing member 15. The light source mixing component 15 includes a light incident surface 151 and a light emitting surface 153, which are disposed opposite to each other, and the first light source 11 and the second light source 13 are disposed facing the light incident surface 151 of the light source mixing component 15. The light source mixing member 15 is configured to uniformly mix the light entering from the light entering surface 151 of the first light source 11 and the second light source 13 to form a uniform light beam, and to emit the uniform light beam from the light emitting surface 153. Emergent light from the first light source 11 and the second light source 13 is uniformly mixed by the light source mixing component 15, so that the quality of a light source image collected by the camera module 200 is ensured, and the detection precision is ensured. In the present embodiment, the first light source 11 is a D50 light source, and the second light source 13 is an a light source. The D50 light source is a light source conforming to a color temperature of 5000K. The light source A is tungsten mercerized light, namely a light source conforming to the color temperature of 2856K.

The processing device 50 includes an acquisition unit 51, a first processing unit 52, and a second processing unit 53.

The obtaining unit 51 is configured to obtain a light source image captured by the camera module 200 aligned with the light emitting surface 153 of the light source device 10.

The first processing unit 52 is configured to process the light source image to obtain a light intensity imaging image, and determine whether the camera module 200 is abnormal in imaging according to the light intensity imaging image; under the condition that it is abnormal to judge that the module of making a video recording 200 is the formation of image, according to the light intensity distribution in the light intensity image graph, obtain the abnormal type that the module of making a video recording 200 leads to the formation of image unusually, the abnormal type includes the module of making a video recording 200 and leads to the unusual part of formation of image. Since the first processing unit 52 detects the imaging performance of the camera module 200 by the light intensity in the light intensity imaging diagram, rather than fixed point detection, the detection accuracy is improved.

In this embodiment, the first processing unit 52 matches the preset light intensity image by the light intensity image, and determines that the imaging of the camera module 200 is abnormal when the matching degree is smaller than the set threshold. In the case where it is determined that the camera module 200 is abnormal in imaging, the first processing unit 52 acquires the component of the camera module 200 that causes the abnormal imaging according to the light intensity image. It should be understood that the first processing unit 52 does not limit whether the imaging of the camera module 200 is abnormal or not by matching the light intensity image with the preset light intensity image, and may also determine according to other manners, for example, according to the preset light intensity value corresponding to each pixel, and the like.

The quality of the light intensity image is related to the imaging performance of the light source device 10 and the camera module 200. The imaging performance of the camera module 200 is associated with the structure of the camera module 200.

Referring to fig. 2, fig. 2 is a schematic structural diagram of a camera module. In the camera module 200, the structure associated with the imaging performance thereof includes: a lens 31, a first filter structure 33 and a sensor 35. The first filter structure 33 is located between the lens 31 and the image sensor 35. The lens 31, the first filter structure 33, and the sensor 35 are stacked in this order. The first filter structure 33 is used for filtering the light entering the camera module 200 through the lens 31. The image sensor 35 is configured to receive light from the first filtering structure 33, and convert the received light into an electrical signal, that is, perform photoelectric conversion, and complete a photosensitive action.

Referring to fig. 3, fig. 3 is a schematic view of a first filtering structure of the camera module shown in fig. 2. The first filter structure 33 includes a red light channel 331 (labeled R in fig. 3), a green light channel 333 (labeled G in fig. 3), and a blue light channel 335 (labeled B in fig. 3). The red channel 331 is for passing red light, the green channel 333 is for passing green light, and the blue channel 335 is for passing blue light.

Referring to fig. 4, fig. 4 is a schematic diagram of a sensor structure of the camera module shown in fig. 2. The image sensor 35 has a second filter structure 350 on a surface facing the first filter structure 33, and the second filter structure 350 includes a red light channel 351, a green light channel 353, and a blue light channel 355. Correspondingly, red channel 351 is for passing red light, green channel 353 is for passing green light, and blue channel 355 is for passing blue light.

Specifically, the first processing unit 52 is further configured to obtain a first image defect of the light intensity profile, and obtain an abnormal type of the camera module 200 corresponding to the first image defect.

In this embodiment, fig. 5a is a predetermined light intensity image, which is obtained from a light source image collected by a normal camera module. In this embodiment, the light source in the predetermined light intensity image is circular, and the light intensity decreases from the center of the circle to the outside. The normal module of making a video recording is the unusual module of making a video recording of non-, accords with the qualified requirement of product promptly. It can be understood that the preset light intensity imaging graph can be set according to the required normal camera module.

In this embodiment, the first image defect includes a light source shape defect, a light source edge dark fringe defect, and a light source internal dark fringe defect. The first processing unit 52 compares and analyzes the light intensity image with the preset light intensity image, if the imaging of the camera module 200 is abnormal, the light source in the light intensity image has a first image defect, and the light intensity of the first image defect region is lower than the corresponding region in the preset light intensity image. It can be understood that the first processing unit 52 processes the light intensity image to obtain the light intensities of different regions of the light intensity image, and compares and analyzes the light intensities of the different regions with the light intensities of corresponding regions in the preset light intensity image to determine the first image defect, i.e. the corresponding abnormal type.

The light source shape defect is that the light source in the light intensity image is not fully imaged, i.e. the light source is only partially imaged. For example, the light source shape in the light intensity image shown in FIG. 5b is not circular but is substantially elliptical. The reason why the camera module 200 causes the defect of the light source shape may be that the position between the lens 31 and the image sensor 35 is shifted, so that only a part of the light source is imaged on the image sensor 35.

The light source edge dark stripe defect is a dark stripe with darker color (weaker light intensity distribution) at the edge of the light source in the light intensity image. For example, the edge portion of the light source in the light intensity imaging diagram shown in FIG. 5c appears dark-striped. The reason why the camera module 200 causes the dark streak defect at the edge of the light source may be that the edge of the lens 31 is defective.

The dark stripe defect inside the light source is a dark stripe with a darker color (with a weaker light intensity distribution) inside the light source in the light intensity image. For example, the light source in the light intensity image shown in FIG. 5d exhibits dark fringes inside. The reason why the camera module 200 causes the dark streak defect at the edge of the light source may be that the optical channel of the first filter structure 33 and/or the second filter structure 350 is abnormal, i.e. the optical channel coating layer disposed on the first filter structure 33 and/or the second filter structure 350 has a defect.

The exception type is pre-stored in a memory device connected to the processing means 50. The exception types include a first exception type, a second exception type, and a third exception type. The first abnormality type is a positional shift between the lens 31 and the image sensor 35. The second anomaly type is a lens 31 edge defect. The third anomaly type is an optical channel anomaly of the first filter structure 33 and/or the second filter structure 350. The shape defect of the light source corresponds to a first abnormal type, the dark fringe defect at the edge of the light source corresponds to a second abnormal type, and the dark fringe defect in the interior of the light source corresponds to a third abnormal type. It can be understood that the exception types are not limited to include a first exception type, a second exception type and a third exception type, but may also include one exception type, two exception types or more than three exception types, and the user may perform the setting as needed.

Since the light channels of the first filter structure 33 and the second filter structure 350 include a red light channel, a green light channel, and a blue light channel, when the first processing unit 52 determines that the camera module 200 is of the third abnormal type, it cannot determine that the abnormal position is the abnormal position of the first filter structure 33 and/or the second filter structure 350.

The second processing unit 53 is configured to process the light intensity imaging graph to obtain a red light channel light intensity graph, a green light channel light intensity graph, and a blue light channel light intensity graph when the camera module 200 is determined to be of the third abnormal type, and determine an abnormal light channel and an abnormal position thereof of the first filter structure 33 and/or the second filter structure 350 in the camera module 200 according to each light channel light intensity graph.

In this embodiment, the second processing unit 53 compares and analyzes the acquired red light channel intensity map with a preset red light channel intensity map, compares and analyzes the acquired green light channel intensity map with a preset green light channel intensity map, and compares and analyzes the acquired blue light channel intensity map with a preset blue light channel intensity map, thereby determining abnormal light channel intensity maps in the red light channel intensity map, the green light channel intensity map, and the blue light channel intensity map. The abnormal light intensity map of the light channel is that a second image defect appears in the light intensity map of the light channel, and the second image defect comprises stain (dead spot), dark lines and the like. The second processing unit 53 determines the abnormal position of the first filtering structure 33 and/or the second filtering structure 350 according to the position of the second image defect, so as to facilitate subsequent inspection of the cause of the product failure, such as the manufacturing machine, the manufacturing material, and the like. And the preset red light channel light intensity graph, the preset green light channel light intensity graph and the preset blue light channel light intensity graph have no second image defect.

The second processing unit 53 compares and analyzes the acquired red light channel intensity map with a preset red light channel intensity map, and if the second processing unit 53 detects that a certain position in the red light channel intensity map has a stain, it can determine an abnormal red light channel and its position in the first filtering structure 33 and/or the second filtering structure 350 in the camera module 200. Similarly, the second processing unit 53 can determine the abnormal green light channel and the position thereof in the first filter structure 33 and/or the second filter structure 350 in the camera module 200 through the stain and the stain position of the green light channel intensity map; the second processing unit 53 determines the abnormal blue light channel and the position thereof in the first filter structure 33 and/or the second filter structure 350 in the camera module 200 according to the stain and the stain position of the blue light channel intensity map.

In one embodiment, the green light channel includes a first green light (Gr) channel and a second green light (Gb) channel, and the green light channel intensity map includes a first green light (Gr) channel intensity map and a second green light (Gb) channel intensity map. Referring to fig. 6a-6e, fig. 6a is a visible light intensity image according to an embodiment of the present invention, wherein a region a in fig. 6a has a stain. In the light intensity maps of the light channels shown in fig. 6 b-6 e, stains appear in the corresponding areas, and the second processing unit 53 determines the abnormality of the first filter structure 33 and/or the second filter structure 350. Fig. 6a-6e are exemplary only, and are not diagrams of the various primary light channels in actual use.

It can be understood that if one of the red channel intensity map, the blue channel intensity map and the green channel intensity map has a second image defect with a relatively obvious appearance, the second processing unit 53 determines the abnormal light channel and the position of the first filter structure 33 and/or the second filter structure 350. For example, the second processing unit 53 determines the position of the abnormal green light channel of the first filter structure 33 and/or the second filter structure 350 when the green light channel intensity map has a second image defect more obvious than the red light channel intensity map and the blue light channel intensity map.

In an embodiment, the second processing unit 53 is not limited to process the light intensity imaging graph to obtain the red light channel light intensity graph, the green light channel light intensity graph and the blue light channel light intensity graph when the camera module 200 is determined to be the third abnormal type, and the second processing unit 53 may process the light intensity imaging graph to obtain the red light channel light intensity graph, the green light channel light intensity graph and the blue light channel light intensity graph after the first processing unit 52 obtains the light intensity imaging graph, so as to accelerate the processing speed of the processing apparatus 100.

In the present embodiment, the distance between the light emitting surface 153 of the light source device 10 and the image pickup module 200 is 5 mm. It can be understood that the distance between the light-emitting surface 153 and the camera module 200 is not limited to 5mm, and the light-emitting surface can obtain the detection light generated by the light source device 10.

It is to be understood that the kind and number of the light sources in the light source device 10 are not limited, for example, the light source of the light source device 10 may adopt at least one of a D50 light source, a D65 light source, a D75 light source or an a light source, and the homogeneous mixing component 15 in the light source device 10 may be omitted.

Furthermore, in order to avoid interference of other light rays in the external environment, the detection device provided by the invention is used for detecting the camera module in a dark environment. In the present embodiment, as shown in fig. 7, the light source device 10 and the camera module 200 to be tested are placed in the dark box 70 to eliminate the interference of the external ambient light. It is to be understood that the light source device 10 and the camera module 200 to be tested are not limited to be placed in the dark box 70, and for example, the detection device may be placed in a dark room.

The detection of the camera module 200 by the detection device 100 will be further described below. The light source device 10 emits detection light. The camera module 200 aims at the light source device 10 to capture a light source image. The acquisition unit 51 of the processing device 50 acquires the light source image captured by the camera module 200. The first processing unit 52 of the processing device 50 processes the light source image to obtain a light intensity image. The first processing unit 52 determines whether the image of the camera module 200 is abnormal according to the light intensity imaging image.

In the present embodiment, the first processing unit 52 determines whether the image of the camera module 200 is abnormal by matching the light intensity imaging image with a preset light intensity map. When the matching degree of the light intensity imaging image and the preset light intensity image is smaller than the set threshold value, it is determined that the imaging of the camera module 200 is abnormal. In the case where it is determined that the camera module 200 is abnormal in imaging, the first processing unit 52 acquires the abnormality type of the camera module 200, the abnormality type including the component of the camera module 200 that causes the imaging abnormality.

The second processing unit 53 processes the light intensity imaging graph to obtain a red light channel light intensity graph, a green light channel light intensity graph and a blue light channel light intensity graph, and determines the light channel position of the filtering structure in the camera module 200 according to each light channel light intensity graph.

In an embodiment, the processing device 50 further includes an output unit, configured to output the light source image, the light intensity imaging graph, and the light intensity imaging graphs of the channels, so as to determine, by human eyes, an abnormal light channel light intensity graph in the red light channel light intensity graph, the green light channel light intensity graph, and the blue light channel light intensity graph, thereby determining a light channel causing imaging abnormality in the filter structure of the camera module 200 and/or the image sensor 35 and a position thereof. The output unit may include a wired interface, a wireless interface, etc. to facilitate deriving the light intensity imaging graph and/or the channel light intensity graph obtained by the first processing unit 52 and/or the second processing unit 53.

In one embodiment, the camera module 200 is an infrared camera module, so that the processing device 200 can omit the second processing unit 53, i.e. perform the optical channel analysis without further processing the optical intensity image. This is because the infrared camera module does not have red light channel, green light channel and blue light channel, but single structure, and the filtering structure in the infrared camera module includes the infrared dot matrix. When the camera module 200 is an infrared camera module, the light source device 10 may use a Dolan light source alone.

In one embodiment, the image capturing module 200 is a black and white image capturing module, so that the processing apparatus 200 can omit the second processing unit 53, i.e. perform the light channel analysis without further processing the light intensity image. This is because the monochrome camera module does not have a red channel, a green channel, and a blue channel, but has a single structure. When the camera module 200 is a monochrome camera module, the light source device 10 can use a D50 light source alone.

In an embodiment, the camera module 200 may omit the first filtering structure 33, so that the abnormal light path and the position thereof on the second filtering structure 350 can be directly determined by the first processing unit 52 and the second processing unit 53.

In one embodiment, the first filter structure 33 and the image sensor 35 in the camera module 200 can be tested separately, for example, when the first filter structure 33 in the camera module 200 needs to be tested, the image sensor 35 is replaced with a normal image sensor (an image sensor meeting the product requirements); when the second filter structure 350 of the image sensor 35 in the camera module 200 needs to be tested, the first filter structure 33 is replaced with a normal filter structure (a filter structure meeting the product requirements).

Referring to fig. 8, fig. 8 is a schematic flow chart of a detection method according to an embodiment of the invention. The invention also provides a detection method for detecting the camera module, which comprises the following steps:

and S11, acquiring a light source image shot by the camera module to be tested aiming at the light source device.

And S12, processing the light source image to obtain a light intensity imaging graph.

S13, judging whether the camera module is abnormal or not according to the light intensity imaging graph and the preset light intensity graph, if so, performing the step S14, namely, the camera module is abnormal in imaging; if not, the imaging of the camera module is not abnormal, and then the process is finished.

In this embodiment, match through light intensity imaging graph and predetermine light intensity imaging graph, when the matching degree is less than the settlement threshold value, then judge the module of making a video recording formation of image unusual.

And S14, determining the abnormal type of the imaging abnormality caused by the camera module according to the light intensity of the light intensity imaging graph.

Comparing and analyzing the light intensity imaging graph and the preset light intensity imaging graph, because the camera module is abnormal in imaging, a first image defect exists in a light source in the light intensity imaging graph, and the light intensity of a first image defect area is lower than a corresponding area in the preset light intensity imaging graph.

The first image defects comprise light source shape defects, light source edge dark line defects and light source internal dark line defects. The light source shape defect is that the light source in the light intensity image is not fully imaged, i.e. the light source is only partially imaged, for example, the light source shape in the light intensity image shown in fig. 5b is not circular but is substantially elliptical. The reason why the camera module causes the defect of the shape of the light source may be that the lens of the camera module is offset from the image sensor of the camera module, so that only part of the light source forms an image on the image sensor.

The light source edge dark fringe defect is a dark fringe with a darker color (with a weaker light intensity distribution) at the edge of the light source in the light intensity image, for example, the light source edge portion in the light intensity image shown in fig. 5c shows a dark fringe. The reason why the camera module causes dark fringe defects at the edge of the light source may be that the edge of the lens of the camera module is defective.

The dark stripe defect in the middle of the light source is a dark stripe with a darker color (with a weaker light intensity distribution) inside the light source in the light intensity image, for example, the light source inside the light intensity image shown in fig. 5d shows a dark stripe. The reason why the camera module causes dark fringe defects at the edge of the light source may be that the filter structure of the camera module and/or the optical channel of the image sensor are abnormal, that is, the optical channel coating layer disposed on the filter structure and/or the image sensor has defects.

The preset exception types include a first exception type, a second exception type and a third exception type. The first abnormal type is a position offset between a lens of the camera module and the image sensor. The second abnormal type is a lens edge defect of the camera module. The third abnormal type is an abnormal light filtering structure of the camera module and/or an abnormal light channel of the image sensor. The shape defect of the light source corresponds to a first abnormal type, the dark fringe defect at the edge of the light source corresponds to a second abnormal type, and the dark fringe defect in the interior of the light source corresponds to a third abnormal type.

In one embodiment, the presence or absence of the first image defect in the intensity profile can be determined directly by the human eye.

S15, processing the light intensity imaging graph to obtain a red light channel light intensity graph, a green light channel light intensity graph and a blue light channel light intensity graph.

And S16, determining the abnormal position of the filter structure of the camera module according to the red light channel light intensity diagram, the green light channel light intensity diagram and the blue light channel light intensity diagram.

In this embodiment, the obtained red light channel intensity map is compared with a preset red light channel intensity map for analysis, the obtained green light channel intensity map is compared with a preset green light channel intensity map for analysis, and the obtained blue light channel intensity map is compared with a preset blue light channel intensity map for analysis, so as to determine abnormal light channel intensity maps in the red light channel intensity map, the green light channel intensity map and the blue light channel intensity map. And the abnormal light channel intensity graph is a second image defect which appears in the light channel intensity graph and comprises stains (dead spots), dark stripes and the like. And determining the position of the abnormal light channel of the light filtering structure and/or the image sensor according to the position of the second image defect, so that the subsequent inspection is facilitated for the reasons causing the poor product, such as manufacturing machine tables, manufacturing materials and the like. And a second image defect does not exist in the preset red light channel light intensity diagram, the preset first green light channel light intensity diagram, the preset second green light channel light intensity diagram and the preset blue light channel light intensity diagram.

In one embodiment, the abnormal light channel intensity maps in the red light channel intensity map, the green light channel intensity map and the blue light channel intensity map can be determined by human eyes, so as to determine the abnormal light channel and the position thereof in the filter structure of the camera module and/or the image sensor.

According to the detection method provided by the embodiment of the invention, whether the camera module is abnormal in imaging and abnormal components causing abnormal imaging of the camera module can be obtained through analysis of the light intensity imaging graph and the light channel light intensity graph, so that the purpose of detecting whether the camera module is abnormal and the reason of the abnormality is achieved, and the accuracy of the detection result is improved.

In an embodiment, steps S15 and S16 may be omitted, for example, in the case where S14 is capable of determining that the abnormal component causing the imaging abnormality of the camera module is the first abnormality type and the second abnormality type.

In one embodiment, when the camera module is an infrared camera module or a monochrome abnormal module, steps S15 and S16 may be omitted.

In an embodiment, referring to fig. 9, a detection method for detecting a camera module includes the following steps:

and S21, acquiring the light source image shot by the camera module to be tested aiming at the light source device.

And S22, processing the light source image to obtain a light intensity imaging graph.

And S23, judging whether the camera module is abnormal or not according to the light intensity imaging graph and the preset light intensity imaging graph.

S24, when the camera module is judged to be abnormal, the abnormal type of the camera module caused by abnormal imaging is obtained according to the light intensity distribution in the light intensity imaging graph.

The invention also provides a processing device for executing the detection method, wherein the processing device comprises an input device, an output device, at least one processor (such as a CPU) and at least one memory. Wherein the components are communicatively coupled via one or more buses. It will be appreciated by those skilled in the art that the configuration of the processing device is not intended to limit embodiments of the present invention, and may be a bus architecture, a star architecture, a combination of more or less components than those shown, or a different arrangement of components. In the embodiment of the present invention, the input device may include a wired interface, a wireless interface, and the like, and may be used to acquire signals, data, and the like. The output means may comprise a wired interface, a wireless interface, etc., and may be used to signal, convey data, etc. to other terminal devices.

In the embodiment of the present invention, the memory may be a high-speed RAM memory, or may be a non-volatile memory (non-volatile memory), such as at least one disk memory. The memory may alternatively be at least one memory device located remotely from the processor. The memory, which is a kind of computer storage medium, may include an operating system, an application program, data, and the like, and the embodiment of the present invention is not limited thereto.

The modules or sub-modules in all embodiments of the present invention may be implemented by a general-purpose Integrated Circuit such as a CPU, or by an ASIC (Application Specific Integrated Circuit).

It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.

The above disclosure is only for the purpose of illustrating the preferred embodiments of the present invention, and it is therefore to be understood that the invention is not limited by the scope of the appended claims.