CN110738606A - Image correction method, device, terminal and storage medium for multi-light source system - Google Patents
Image correction method, device, terminal and storage medium for multi-light source system Download PDFInfo
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- CN110738606A CN110738606A CN201910841368.3A CN201910841368A CN110738606A CN 110738606 A CN110738606 A CN 110738606A CN 201910841368 A CN201910841368 A CN 201910841368A CN 110738606 A CN110738606 A CN 110738606A
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- 238000000034 method Methods 0.000 title claims abstract description 49
- 238000003702 image correction Methods 0.000 title claims abstract description 35
- 238000001514 detection method Methods 0.000 claims abstract description 67
- 238000004590 computer program Methods 0.000 claims description 11
- 238000007689 inspection Methods 0.000 claims description 9
- 238000004364 calculation method Methods 0.000 claims description 7
- 238000010586 diagram Methods 0.000 description 7
- 238000003384 imaging method Methods 0.000 description 5
- 230000007547 defect Effects 0.000 description 3
- 238000003708 edge detection Methods 0.000 description 3
- 239000011521 glass Substances 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 2
- 230000001360 synchronised effect Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000007796 conventional method Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000003631 expected effect Effects 0.000 description 1
- 239000005338 frosted glass Substances 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
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- G06T5/90—
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20081—Training; Learning
Abstract
The embodiment of the invention discloses a image correction method, a device, a terminal and a storage medium of a multi-light-source system, which are applied to a detection system, wherein the detection system comprises at least detection stations, a camera device corresponding to the detection stations and a plurality of groups of light sources correspondingly arranged, the method comprises the steps of collecting training images corresponding to the detection stations under every groups of light sources through the camera device, calculating and storing correction coefficients corresponding to every groups of light sources based on the training images, collecting target images corresponding to products to be detected through the camera device, and correcting the target images according to the correction coefficients.
Description
Technical Field
The invention relates to the technical field of machine vision, in particular to an image correction method, an image correction device, an image correction terminal and a storage medium for multi-light-source systems.
Background
In the manufacturing process of products, in order to ensure the quality of the products after output, generally needs to perform quality detection operation on the products, for example, defect detection on mobile phone glass cover plates by a machine vision technology, in the detection process, the products may have a plurality of defects, at this time, the detection operation is realized by adding detection stations or combining different detection stations in detection stations in the conventional method , but because the types and the set angles of the groups of light sources of different detection stations may be different, at this time, because the groups of light sources in different detection stations affect each other in the detection process, the imaging of the products to be detected required for detection cannot reach the expected effect, and the quality detection effect of the products at the later stage is affected.
Disclosure of Invention
In view of the above, the present invention provides image correction methods, apparatuses, terminals and storage media for multi-light source systems, which are used to solve the problem of poor detection quality caused by the mutual influence among multiple stations in the prior art, and the present invention proposes image correction methods, apparatuses, terminals and storage media for multi-light source systems:
, the embodiment of the invention provides a image correction method of a multi-light source system, which is applied to a detection system, wherein the detection system comprises at least detection stations, a camera device corresponding to the detection stations and a plurality of group light sources arranged correspondingly, the method comprises the following steps:
acquiring training images corresponding to the detection stations under each groups of light sources through the camera device;
calculating and saving a correction coefficient corresponding to the group of light sources based on the training image;
and acquiring a target image corresponding to a product to be detected through the camera device, and correcting the target image according to the correction coefficient.
Preferably, the acquiring, by the camera device, a training image corresponding to the detection station under each groups of light sources includes:
and acquiring a white field image corresponding to the detection station under a preset group of light sources, and taking the white field image as the training image.
Preferably, the calculating and saving the correction coefficient corresponding to the set of light sources based on the training image includes:
extracting pixel data of each pixel point in the training image, and determining the pixel point of the maximum pixel data in the training image according to the pixel data;
and determining the correction coefficient according to the pixel data and the maximum pixel data of each pixel point.
Preferably, the extracting pixel data of each pixel point in the training image and determining the pixel point of the maximum pixel data in the training image according to the pixel data includes:
extracting gray pixel data of the training image, and determining a pixel point of the maximum gray pixel data in the training image according to the gray pixel data;
and determining the correction coefficient according to the gray pixel data and the maximum gray pixel data of each pixel point.
Preferably, the calculating and saving the correction coefficient corresponding to the set of light sources based on the training image further includes:
judging whether all the group light sources acquire the corresponding correction coefficients, if the correction coefficients of the group light sources are not calculated, relighting the group light sources, and
acquiring training images under the irradiation of the group of light sources through the camera device, and calculating correction coefficients of the corresponding group of light sources according to the training images;
and storing the correction coefficient to the detection system corresponding to each group of light sources.
Preferably, the correcting the target image according to the correction coefficient includes:
determining a group light source corresponding to the target image;
and acquiring a correction coefficient corresponding to the determined group of light sources, and correcting the target image according to the target coefficient.
Preferably, the correcting the target image according to the target coefficient includes:
traversing all pixel points in the target image;
and correcting all the pixel points in the target image according to the correction coefficient.
In a second aspect, an embodiment of the present invention provides kinds of image correction apparatuses for a multi-light-source system, including:
the acquisition module is used for acquiring training images corresponding to each groups of light sources and acquiring target images corresponding to a product to be detected;
a calculation module for calculating correction coefficients corresponding to each of the groups of light sources from the training images;
a correction module for correcting the target image according to the correction coefficients corresponding to each of the groups of light sources.
In a third aspect, an embodiment of the present invention further provides terminals, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor, when executing the computer program, implements the image correction method for the multi-light-source system as described above.
In a fourth aspect, embodiments of the present invention further provide computer-readable storage media, which include computer instructions, which when executed on a computer, cause the computer to execute the method for image correction of a multi-light source system as described above.
The embodiment of the invention has the following beneficial effects:
after the image correction method, the device, the terminal and the storage medium of the multi-light-source system are adopted, specifically, a training image of each groups of light sources in each detection station is collected through a camera device, a correction coefficient corresponding to each group of light sources is obtained according to the training image, the corresponding correction coefficient is obtained based on the light emitting characteristics of the light sources, and the correction coefficient and each groups of light sources are correspondingly stored in the detection system.
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 embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Wherein:
FIG. 1 is a schematic flow chart of an image correction method of the multi-light-source system in embodiments;
FIG. 2 is a schematic view of the calculation process of the correction coefficients in embodiments;
FIG. 3 is a schematic diagram of an actual application flow of embodiments of group illuminant correction performed by the correction coefficients;
FIG. 4 is a schematic diagram of the mode in which the correction coefficients are stored in the detection system;
FIG. 5 is a schematic diagram of exemplary embodiments of the correction operation using the correction coefficients;
FIG. 6 is a schematic structural diagram of an image correction apparatus of the multi-light-source system in embodiments;
fig. 7 is a schematic diagram of the internal structure of embodiments of a computer device for executing the image correction method of the multi-light-source system.
Detailed Description
The technical solutions in the embodiments of the present invention will be described clearly and completely with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only partial embodiments of of the present invention, rather than all embodiments.
In order to solve the problem of the conventional technology that the glass quality cannot be efficiently and accurately inspected in the quality inspection process of the product to be inspected by using the inspection system, in this embodiment, image correction methods of a multi-light source system are proposed, and the implementation of the methods can depend on a computer program which can run on a computer system based on the von Neumann system.
In this embodiment, the inspection system includes at least inspection stations, a camera device corresponding to the inspection stations, and a plurality of groups of light sources correspondingly disposed, and in step , the camera device may be a camera, a camera head, or other equipment having an image capturing function.
Specifically, as shown in fig. 1, the method for calibrating the multiple light source systems includes the following steps S102 to S106:
step S102, collecting training images corresponding to the detection stations under each groups of light sources through the camera device;
in the specific implementation, in order to obtain a correction coefficient of the detection system for the image under each group of light sources, specifically, the detection station only starts group light sources every times, obtains an image corresponding to the detection station under the condition of irradiation of the started group light sources, marks the image as a training image, and then calculates the correction coefficient corresponding to each group of light sources based on the training image, , in this embodiment, a white field image corresponding to the detection station is obtained under a preset group light source background, wherein the white field image refers to an image whose image content or image background is white, for example, the white field image may be a picture obtained by shooting white paper or frosted glass by a camera device, and the white field image is used as the training image to further calculate the correction coefficient of the corresponding image under each group of light sources, and the obtained white field image can exclude the influence of the background on imaging, so that the training image more conforming to the actual condition of the detection station can be obtained, that a better image correction coefficient corresponding to each group of light sources can be obtained.
In a specific embodiment, or more individual light sources may be disposed in each group of light sources, and the setting may be specifically performed according to the actual situation, which is not limited and fixed in this application.
Step S104: calculating and saving a correction coefficient corresponding to the group of light sources based on the training image;
in specific implementation, after obtaining the training image corresponding to the detection station, in order to obtain the correction coefficient of the light source corresponding to the corresponding group through the training image calculation, in this embodiment, pixel data of all pixel points in the training image needs to be extracted, and a pixel point of the maximum pixel data in the training image is determined according to the extracted pixel data, so that the correction coefficient of the training image is determined according to the pixel data of each pixel point and the maximum pixel data, step , in this embodiment, a pixel point of the maximum gray pixel data in the training image is determined according to the gray pixel data by extracting the gray pixel data of the training image.
Specifically, in practical application, the pixel point of the maximum gray pixel data corresponds to the maximum light-transmitting position in the training image, so that the pixel point of the maximum gray pixel in the training image can be used as a reference point for image correction; the method comprises the steps of determining the relationship between the pixel point of the maximum gray pixel and the gray levels of all other pixel points by traversing all pixel points in a training image, and determining a correction coefficient under a corresponding group of light sources according to the relationship, so that an image with uniform light transmission can be obtained after correction.
In embodiments, as shown in fig. 2, since the correction coefficients of all the groups of light sources in the detection station need to be calculated, in order to ensure that all the groups of light sources in the detection station can perform the correction operation during the calculation of the correction coefficients, the present application needs to determine whether all the groups of light sources in the detection station acquire the corresponding image correction coefficients, and if the correction coefficients of the groups of light sources are not calculated, re-light the groups of light sources that do not acquire the corresponding correction coefficients, acquire the training images under the irradiation of the groups of light sources, and calculate the correction coefficients of the training images under the corresponding groups of light sources according to the above-mentioned manner.
Step S106: and acquiring a target image corresponding to a product to be detected through the camera device, and correcting the target image according to the correction coefficient.
In a specific embodiment, as shown in fig. 3, in order to perform the correction operation of the corresponding group of light sources in each detection process, the correction coefficient obtained by calculation is stored in the detection system, specifically, in order to ensure that the correction coefficient corresponding to the group of light sources which is being turned on is used in the correction operation of the image under each group of light sources, after the correction coefficient corresponding to a certain group of light sources is obtained, the correction coefficient is stored in correspondence with the corresponding group of light sources .
In embodiments, as shown in fig. 4, assuming that 3 groups of light sources are disposed in the inspection station, the group light sources can be numbered, that is, the group of light sources is numbered 1, the second group of light sources is numbered 2, and the third group of light sources is numbered 3, after the correction coefficient corresponding to the group of light sources is obtained by the above method, the group light sources and the correction coefficient are stored in the inspection system as shown in fig. 4.
And , if the detection system does not need to continue the detection operation of the product to be detected, i.e. does not need to collect the target image of the product to be detected for detection operation, ending the detection operation.
In the specific embodiment, because each photosensitive unit in the imaging device corresponds to correction coefficients, the present application calculates the correction coefficient corresponding to each group of light sources according to the above-mentioned maximum gray pixel data as a reference, so that when the imaging device collects an image, the detection system will perform a correction operation on the target image obtained under each group of light sources according to the correction coefficients to ensure that a target image with uniform brightness is obtained, as shown in fig. 5, where a represents the original image data, i.e. the original image of the product to be inspected obtained by the imaging device at the detection station, B represents the correction data, i.e. the corresponding correction coefficients, and C represents the image obtained after correction, and the three satisfy the condition that dst represents src ＊ scale + off, where dst represents the corrected image data, src represents the original image data, and scale and off represent the correction data.
By adopting the image correction method of the multi-light-source system in the embodiment, in the process of detecting a product to be detected by the detection system, the target image obtained under the irradiation condition of different light sources can be corrected according to the correction coefficient corresponding to each groups of light sources, so that an image with uniform brightness is obtained, and the detection precision of the detection system in the product detection process can be improved.
In addition, based on the same concept of , as shown in fig. 6, the embodiment of the invention provides image correction devices of multi-light source systems.
Specifically, the image correction device of the multi-light source system includes:
the acquisition module 101 is used for acquiring a training image corresponding to each group of light sources and acquiring a target image corresponding to a product to be detected;
a calculating module 102, configured to calculate, according to the training image, a correction coefficient corresponding to each of the group of light sources;
a correction module 103, configured to correct the target image according to the correction coefficient corresponding to each of the groups of light sources.
In the correction method for the multi-light-source system, the image correction device for the multi-light-source system of the embodiment first obtains the training image of the product to be detected under the irradiation of each group of light sources through the acquisition module 101, wherein the training image can be obtained through the camera equipment such as a camera, and then inputs the training image into the calculation module 102, specifically calculates the correction coefficient of the light source group corresponding to the training image and stores the correction coefficient into the detection system, so that in the actual detection process, because the correction coefficient of each light source groups corresponding to the image is obtained, after the target image of the product to be detected is acquired through the acquisition module 101 again, the detection system can perform correction operation on the target images under different groups of light sources according to the correction coefficients of the different groups of light sources, thereby ensuring the uniformity of the brightness of the target images required for detection, and facilitating the improvement of the detection precision.
It should be noted that, the implementation of the image correction apparatus of the multiple light source system in this embodiment is similar to the implementation idea of the image correction method of the multiple light source system, and the specific implementation principle thereof is not described herein again, and it can refer to the corresponding content in the method.
After the image correction method and the device of the multi-light-source system are adopted, the training images of each groups of light sources in each detection station are collected through the camera device, the correction coefficient corresponding to each group of light sources is obtained according to the training images, the corresponding correction coefficient is obtained based on the light emitting characteristics of the light sources, and the correction coefficient and each group of light sources are correspondingly stored in the detection system.
Fig. 7 shows an internal structure diagram of computer devices, which may be servers or terminals in particular, according to the embodiments shown in fig. 7, which includes a processor, a memory and a network interface connected through a system bus, wherein the memory includes a nonvolatile storage medium and an internal memory, the nonvolatile storage medium of the computer device stores an operating system and may also store a computer program, which when executed by the processor causes the processor to implement an edge detection method, the internal memory may also store a computer program, which when executed by the processor causes the processor to execute the edge detection method, it will be understood by those skilled in the art that the structure shown in fig. 7 is a block diagram of only a part of the structure related to the aspects of the present application and does not constitute a limitation of the computer devices to which the aspects of the present application are applied, and a particular computer device may include more or fewer parts than those shown in the drawings, or may have a combination of parts, or a different arrangement of parts.
In embodiments, the method of glass boundary defect detection provided herein may be embodied in the form of computer programs that are executable on a computer device such as that shown in FIG. 7. various program modules that make up the edge detection apparatus may be stored in the memory of the computer device. for example, computing module 102, etc.
In embodiments, computer devices are provided, including a memory and a processor, wherein the memory stores a computer program, and the computer program when executed by the processor causes the processor to perform the steps of acquiring a training image corresponding to the inspection station for each groups of light sources by the camera device, calculating and saving a correction coefficient corresponding to the group of light sources based on the training image, acquiring a target image corresponding to a product to be inspected by the camera device, and correcting the target image according to the correction coefficient.
Those of ordinary skill in the art will appreciate that all or a portion of the processes in the methods of the above embodiments may be implemented by a computer program that may be stored in a non-volatile computer readable storage medium that, when executed, may include the processes of the embodiments of the methods described above, wherein any reference to memory, storage, database or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, non-volatile memory may include read-only memory (ROM), programmable ROM (prom), electrically programmable ROM (eprom), electrically erasable programmable ROM (eeprom), or flash memory, volatile memory may include Random Access Memory (RAM) or external cache memory, RAM is available in a variety of forms, such as static RAM (sram), dynamic RAM (dram), synchronous dram (sdram), double data rate sdram (ddr sdram), sdram (sdram), synchronous sdram (sdram), and dynamic RAM (rdram), such as dynamic RAM (sdram), direct memory (dram), and dynamic RAM (rdram) bus (rdram).
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.
Claims (10)
- The image correction method of kinds of multiple light source system is characterized by that it is used in detection system, said detection system includes at least detection stations, camera device correspondent to said detection station and several groups of light sources which are correspondent to said detection station, and said method includes:acquiring training images corresponding to the detection stations under each groups of light sources through the camera device;calculating and saving a correction coefficient corresponding to the group of light sources based on the training image;and acquiring a target image corresponding to a product to be detected through the camera device, and correcting the target image according to the correction coefficient.
- 2. The image correction method of the multiple light source system according to claim 1, wherein the capturing training images corresponding to the inspection stations for each groups of light sources by the camera device comprises:and acquiring a white field image corresponding to the detection station under a preset group of light sources, and taking the white field image as the training image.
- 3. The image correction method of the multi-light-source system according to claim 2, wherein the calculating and storing the correction coefficients corresponding to the set of light sources based on the training image comprises:extracting pixel data of each pixel point in the training image, and determining the pixel point of the maximum pixel data in the training image according to the pixel data;and determining the correction coefficient according to the pixel data and the maximum pixel data of each pixel point.
- 4. The image correction method of the multiple light source system according to claim 3, wherein the extracting pixel data of each pixel point in the training image and determining the pixel point of the maximum pixel data in the training image according to the pixel data comprises:extracting gray pixel data of the training image, and determining a pixel point of the maximum gray pixel data in the training image according to the gray pixel data;and determining the correction coefficient according to the gray pixel data and the maximum gray pixel data of each pixel point.
- 5. The image correction method of the multi-light-source system according to claim 3, wherein the calculating and saving of the correction coefficient corresponding to the set of light sources based on the training image further comprises:judging whether all the group light sources acquire the corresponding correction coefficients, if the correction coefficients of the group light sources are not calculated, relighting the group light sources, andacquiring training images under the irradiation of the group of light sources through the camera device, and calculating correction coefficients of the corresponding group of light sources according to the training images;and storing the correction coefficient to the detection system corresponding to each group of light sources.
- 6. The image correction method of the multiple light source system according to claim 1, wherein the correcting the target image according to the correction coefficient includes:determining a group light source corresponding to the target image;and acquiring a correction coefficient corresponding to the determined group of light sources, and correcting the target image according to the target coefficient.
- 7. The image correction method of the multiple light source system according to claim 6, wherein the correcting the target image according to the target coefficient includes:traversing all pixel points in the target image;and correcting all the pixel points in the target image according to the correction coefficient.
- An image correction device for a multiple light source system of the type 8, , comprising:the acquisition module is used for acquiring training images corresponding to each groups of light sources and acquiring target images corresponding to a product to be detected;a calculation module for calculating correction coefficients corresponding to each of the groups of light sources from the training images;a correction module for correcting the target image according to the correction coefficients corresponding to each of the groups of light sources.
- A terminal of 9, , comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor when executing the computer program implements the method of any of claims 1-7 as claimed in any of claims .
- 10, computer readable storage medium comprising computer instructions which, when executed on a computer, cause the computer to perform the method of any of claims 1-7 to .
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111681201A (en) * | 2020-04-20 | 2020-09-18 | 深圳市鸿富瀚科技股份有限公司 | Image processing method, image processing device, computer equipment and storage medium |
| CN113179364A (en) * | 2021-04-26 | 2021-07-27 | 上海大学 | Image brightness calibration method for endoscope imaging |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH0996610A (en) * | 1995-09-30 | 1997-04-08 | Tani Denki Kogyo Kk | Illuminating apparatus for visual inspection and its manufacture |
| US20070103893A1 (en) * | 2004-04-22 | 2007-05-10 | Olympus Corporation | Defect inspection device and substrate manufacturing system using the same |
| CN101561948A (en) * | 2008-04-17 | 2009-10-21 | 中国印钞造币总公司 | Automatic coin quality detection device |
| CN102680479A (en) * | 2012-04-27 | 2012-09-19 | 浙江工业大学 | System for detecting quality of carpet threads based on visual method |
| CN103884650A (en) * | 2014-03-28 | 2014-06-25 | 北京大恒图像视觉有限公司 | Multi-photosource linear array imaging system and method |
| CN107071234A (en) * | 2017-01-23 | 2017-08-18 | 上海兴芯微电子科技有限公司 | A kind of camera lens shadow correction method and device |
| CN107607549A (en) * | 2017-09-27 | 2018-01-19 | 深圳精创视觉科技有限公司 | Glass defect detection device |
| CN108413881A (en) * | 2017-12-12 | 2018-08-17 | 威海华菱光电股份有限公司 | Thickness detecting method and device and thickness imaging sensor |
-
2019
- 2019-09-06 CN CN201910841368.3A patent/CN110738606A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH0996610A (en) * | 1995-09-30 | 1997-04-08 | Tani Denki Kogyo Kk | Illuminating apparatus for visual inspection and its manufacture |
| US20070103893A1 (en) * | 2004-04-22 | 2007-05-10 | Olympus Corporation | Defect inspection device and substrate manufacturing system using the same |
| CN101561948A (en) * | 2008-04-17 | 2009-10-21 | 中国印钞造币总公司 | Automatic coin quality detection device |
| CN102680479A (en) * | 2012-04-27 | 2012-09-19 | 浙江工业大学 | System for detecting quality of carpet threads based on visual method |
| CN103884650A (en) * | 2014-03-28 | 2014-06-25 | 北京大恒图像视觉有限公司 | Multi-photosource linear array imaging system and method |
| CN107071234A (en) * | 2017-01-23 | 2017-08-18 | 上海兴芯微电子科技有限公司 | A kind of camera lens shadow correction method and device |
| CN107607549A (en) * | 2017-09-27 | 2018-01-19 | 深圳精创视觉科技有限公司 | Glass defect detection device |
| CN108413881A (en) * | 2017-12-12 | 2018-08-17 | 威海华菱光电股份有限公司 | Thickness detecting method and device and thickness imaging sensor |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111681201A (en) * | 2020-04-20 | 2020-09-18 | 深圳市鸿富瀚科技股份有限公司 | Image processing method, image processing device, computer equipment and storage medium |
| CN111681201B (en) * | 2020-04-20 | 2023-06-23 | 深圳市鸿富瀚科技股份有限公司 | Image processing method, device, computer equipment and storage medium |
| CN113179364A (en) * | 2021-04-26 | 2021-07-27 | 上海大学 | Image brightness calibration method for endoscope imaging |
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