CN113763354A - Image processing method and electronic equipment - Google Patents
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Abstract
The application relates to an image processing method and an electronic device, after a first image of a target object shot by first shooting parameters is obtained, once at least one pixel which does not meet preset pixel parameter conditions exists in at least partial image areas of the first image, updating shooting parameters are determined, an updating image of at least partial areas of the target object shot by the updating shooting parameters is obtained, and then the target image is further generated according to the first image and the updating image and a to-be-processed pixel set formed by the pixels which do not meet the preset pixel parameter conditions.
Description
Technical Field
The application belongs to the technical field of information acquisition and processing, and particularly relates to an image processing method and electronic equipment.
Background
The 3C product is a general name of computer products, communication products, and consumer electronics products, and in the manufacturing of the 3C product, it is usually necessary to perform screen defect detection on a Display of the product, such as LCD (Liquid Crystal Display) defect detection, so as to ensure the quality of the product. In the traditional 3C product manufacturing, when the screen defect detection is carried out on the display, the problems that the defect details cannot be shot or the shooting is not obvious and the like often occur, and further algorithm misjudgment or misjudgment is caused.
Disclosure of Invention
Therefore, the application discloses the following technical scheme:
an image processing method comprising:
acquiring a first image of a target object shot by first shooting parameters;
determining that at least one pixel which does not meet the condition of a preset pixel parameter exists in at least one partial image area of the first image to obtain a pixel set to be processed;
determining updated shooting parameters and acquiring an updated image of at least a partial region of the target object shot by the updated shooting parameters; the at least partial region at least comprises a set of points corresponding to the pixel set to be processed on the target object;
and generating a target image according to the first image, the updated image and the pixel set to be processed.
Optionally, the determining that at least one pixel which does not satisfy the preset pixel parameter condition exists in at least a partial image region of the first image to obtain a to-be-processed pixel set includes:
and determining at least one pixel of which the pixel gray value and/or the brightness value are not in a preset value interval in at least one partial image area of the first image to obtain the pixel set to be processed.
Optionally, determining an updated shooting parameter, and acquiring an updated image of at least a partial region of the target object shot with the updated shooting parameter, includes:
if the pixel set to be processed comprises first pixels of which the pixel parameter values are larger than the upper threshold value of the preset value interval, determining second shooting parameters, and acquiring a second image of the first point set shot by the second shooting parameters; the first point set at least comprises a set of points corresponding to the first pixels on the target object;
if the pixel set to be processed comprises second pixels of which the pixel parameter values are smaller than the lower threshold value of the preset value-taking interval, determining a third shooting parameter, and acquiring a third image of a second point set shot by the third shooting parameter; the second point set at least comprises a set of points corresponding to the second pixels on the target object;
the parameter types of the second shooting parameters and the third shooting parameters are the same as the parameter type of the first shooting parameters, the exposure degree of the shot object can be reduced by the second shooting parameters compared with the first shooting parameters, and the exposure degree of the shot object can be improved by the third shooting parameters compared with the first shooting parameters;
generating a target image according to the first image, the updated image and the to-be-processed pixel set, including:
and generating a target image according to the first image, the second image and/or the third image and the pixel set to be processed.
Optionally, the determining the second shooting parameter includes:
determining shooting parameters matched with pixel parameter values of the first pixels from a target shooting parameter set to obtain second shooting parameters;
the determining the third shooting parameter includes:
determining shooting parameters matched with pixel parameter values of the second pixels from the target shooting parameter set to obtain third shooting parameters;
wherein the target photographing parameter set further includes the first photographing parameter.
Optionally, the generating a target image according to the first image, the second image and/or the third image, and the to-be-processed pixel set includes:
and according to the position information of the first pixel and/or the second pixel included in the pixel set to be processed, carrying out fusion processing on the first image and the second image and/or the third image to obtain a target image.
Optionally, the target object is a display screen;
before the acquiring the first image of the target object photographed with the first photographing parameter, the method further includes:
acquiring the configuration information of the target object, and acquiring a shooting parameter set matched with the configuration information of the target object to obtain the target shooting parameter set; different objects with different configuration information respectively correspond to different shooting parameter sets;
and acquiring the first shooting parameters from the target shooting parameter set, and shooting the target object by using the first shooting parameters.
Optionally, before the determining whether at least one pixel whose display parameter does not satisfy the parameter condition exists in at least a partial image region of the first image, the method further includes:
and performing image segmentation processing on the first image to obtain an image area corresponding to the target object in the first image, so as to process the image area corresponding to the target object.
Optionally, the predetermined value interval is [30, 230 ].
Optionally, after generating and outputting the target image, the method further includes:
and carrying out defect identification processing on the target image so as to identify the defects of the target object.
There is also provided in an aspect of the present application an electronic device, comprising:
an image acquisition device;
a memory for storing at least one set of instructions;
a processor for implementing an image processing method as claimed in any one of the above by executing a set of instructions in said memory.
As can be seen from the above solutions, the image processing method and the electronic device provided in the present application, after acquiring the first image of the target object captured with the first capturing parameter, once determining that at least one pixel that does not satisfy the preset pixel parameter condition exists in at least a partial image area of the first image, determine the updated capturing parameter, and acquire the updated image of at least a partial area of the target object captured with the updated capturing parameter, then further generate the target image according to the first image and the updated image, and the to-be-processed pixel set formed by the pixels that do not satisfy the preset pixel parameter condition.
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In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, it is obvious that the drawings in the following description are only embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
FIG. 1 is a process flow diagram of an image processing method provided herein;
FIG. 2 is a screen image of a display captured based on a first capture parameter provided herein;
FIG. 3 is a pixel region with an overexposure in the image of FIG. 2 provided herein;
FIG. 4 is a pixel region with an under-exposure in the image of FIG. 2 provided herein;
FIG. 5 is another process flow diagram of the image processing method provided herein;
FIG. 6 is a flow chart of another process of the image processing method provided by the present application;
fig. 7 is a schematic structural diagram of an electronic device provided in the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, 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 application.
In order to overcome the defects that when a screen defect of a display is detected in the traditional 3C product manufacturing process, the defects that the details of the defect cannot be shot or the shooting is not obvious and the like often occur, and further the algorithm is judged wrongly or misjudged, the embodiment of the application discloses an image processing method and electronic equipment.
The image processing methods disclosed herein are operational with numerous general purpose or special purpose computing device environments or configurations. For example: personal computers, server computers, hand-held or portable devices, tablet-type devices, multi-processor apparatus, distributed computing environments that include any of the above devices or equipment, and the like.
The processing flow of the image processing method is shown in fig. 1, and specifically includes:
The target object may be, but is not limited to, a display screen of a display to be subjected to screen defect detection, such as an LCD screen of a terminal device such as a notebook or a mobile phone, or an LED (light-emitting diode) screen, etc.
The shooting parameters in the embodiment of the present application, such as the first shooting parameter, the second shooting parameter, the third shooting parameter, and the like, refer to parameters related to the exposure effect/the exposure performance in the camera parameters, including parameters such as exposure time and sensitivity, and in addition, may include parameters such as aperture size, shutter speed, Gamma (also called Gamma), and/or Gain (camera Gain).
The first shooting parameter is a conventional parameter value of the above parameter types (such as exposure time, etc.) when the screen of the display is shot in the screen defect detection, for example, a parameter value which is set by a system default configuration or a technician based on experience and can be generally suitable for most display screens to be detected of types to be detected in the screen defect detection scene so that the most display screens to be detected can have a relatively ideal exposure effect.
In the embodiment of the application, for a target object to be detected, initially, an image of the target object is captured according to a first capturing parameter, and a first image of the target object captured according to the first capturing parameter is obtained, for example, for a display screen to be subjected to screen defect detection, a screen image of the display screen captured according to a conventional exposure parameter is initially obtained.
Preferably, the image is captured with the display screen bright.
And 102, determining that at least one pixel which does not meet the preset pixel parameter condition exists in at least one partial image area of the first image, and obtaining a pixel set to be processed.
In the embodiment of the present application, the preset pixel parameter conditions are set as follows: the gray value and/or the brightness value of the pixel are/is in a preset value interval.
The predetermined value interval is specifically a conventional pixel gray level/brightness value interval set based on under exposure/over exposure matching with a reference standard.
Wherein, the reference benchmarks of underexposure (i.e. underexposure, which is embodied as too dark image) are: the image gray/brightness is lower than a set lower threshold; the overexposure (i.e., overexposure, which is embodied as an image that is too bright) reference benchmarks are: the gray level/brightness of the image is higher than the set upper threshold, and the lower threshold is lower than the upper threshold, then the predetermined value interval is [ lower threshold, upper threshold ].
Illustratively, the predetermined value interval may be, but is not limited to, set to [0, 250], or [30, 230], etc.
The method specifically determines whether at least one pixel with a pixel parameter value not being in the predetermined value interval exists in at least a partial image area of the first image, wherein if a first pixel with a pixel parameter value being greater than an upper threshold value of the predetermined value interval exists and/or a second pixel with a pixel parameter value being less than a lower threshold value of the predetermined value interval exists, the first pixel and/or the second pixel are/is an overexposed or underexposed pixel in the first image.
On the contrary, if there is no pixel whose pixel parameter value is not in the predetermined value range, the defect detection may be performed on the target object, such as a screen of a display screen, directly with the first image as a reference.
103, determining an updated shooting parameter, and acquiring an updated image of at least a partial area of the target object shot by the updated shooting parameter; the at least partial region includes at least a set of points corresponding to the set of pixels to be processed on the target object.
In the conventional image gray/brightness calculation, an average value-based calculation method is generally adopted, that is, the average value of gray/brightness of each pixel in a certain area of an image is taken as the pixel gray/brightness value of the area, however, in the field of Automatic Optical Inspection (AOI) of a display screen, defects are generally fine, and averaging is very likely to average some bright points and dark points, which results in disadvantages to defect detection.
Aiming at the characteristics, the gray/brightness calculation and judgment of the pixel are carried out by taking the pixel as a unit, the pixel which is not in the set value interval is extracted, the shooting parameters are adjusted for the pixel which is not in the preset value interval such as [30, 230], and the shooting is carried out again based on the updated shooting parameters obtained after the adjustment, so that the gray/brightness is in the set value interval.
The method and the device for detecting the exposure of the display are characterized in that specific N groups of shooting parameters corresponding to different exposure performances of an object to be detected (such as a display of a corresponding model) are determined in advance, illustratively, three groups of exposure shooting parameters including low exposure shooting parameters, medium exposure shooting parameters and high exposure shooting parameters are determined for the display of the model to be detected, for a series of pixels with overexposure, the shooting parameters are adjusted to be uniformly recaptured by adopting the low exposure shooting parameters, and for a series of pixels with underexposure, the shooting parameters are adjusted to be uniformly recaptured by adopting the high exposure shooting parameters.
The middle exposure shooting parameters refer to the first shooting parameters, namely, the shooting parameters under the condition of normal exposure, the high exposure shooting parameters and the low exposure shooting parameters are consistent with the parameter types of the middle exposure shooting parameters relative to the shooting parameters under the condition of normal exposure, but the low exposure shooting parameters are compared with the middle exposure shooting parameters (namely, the first shooting parameters), so that the exposure degree of the shot object can be reduced, and the high exposure shooting parameters are compared with the middle exposure shooting parameters, so that the exposure degree of the shot object can be improved.
On the basis, if the pixel set to be processed comprises pixel parameter values such as a first pixel of which the pixel gray value/brightness value is larger than an upper threshold value of the preset value interval, determining a second shooting parameter, and acquiring a second image of the first point set shot by the second shooting parameter; the first set of points includes at least a set of points corresponding to respective first pixels on the target object.
Specifically, the above-described low-exposure shooting parameter may be determined as the second shooting parameter. The pixel gray value/brightness value is larger than the upper threshold value of the preset value interval, the representation pixel has an overexposure phenomenon, and in this case, the detail can be better shot by reducing the exposure degree of the corresponding point set of the part of pixels on the target object.
The acquiring of the second image of the first point set captured with the second capturing parameter may refer to acquiring an entire image of the target object captured with the second capturing parameter, or acquiring only an image of a point set corresponding to each first pixel captured with the second capturing parameter on the target object, for example, in a case where a series of first pixels with a gray value/brightness value larger than 230 is included in the pixel set to be processed, re-capturing the entire display screen with the second capturing parameter, or re-capturing only each corresponding point on the display screen of a series of pixels with a gray value/brightness value larger than 230.
If the pixel set to be processed comprises pixel parameter values such as a second pixel with a pixel gray value/brightness value smaller than the lower threshold value of the preset value interval, determining a third shooting parameter, and acquiring a third image of a second point set shot by the third shooting parameter; the second set of points includes at least a set of points corresponding to respective second pixels on the target object.
Specifically, the high-exposure shooting parameter described above may be determined as the third shooting parameter. And under the condition that the pixel gray value/brightness value is smaller than the lower threshold of the preset value interval, the phenomenon of under exposure of the pixel is represented, and the details of the pixel can be better shot by improving the exposure degree of the corresponding point set of the part of the pixel on the target object.
Similarly, acquiring the third image of the second point set captured with the third shooting parameter may refer to acquiring an entire image of the target object captured with the third shooting parameter, or acquiring an image of a point set corresponding to each second pixel on the target object captured with the third shooting parameter. For example, in the case where the set of pixels to be processed includes a series of second pixels having a gradation value/luminance value smaller than 30, the entire display screen is re-photographed with the third photographing parameter, or only corresponding respective points on the display screen of the series of pixels having a gradation value/luminance value smaller than 30 are re-photographed.
It is easy to understand that the parameter types of the second shooting parameter and the third shooting parameter are the same as the parameter types of the first shooting parameter, for example, if the first shooting parameter only includes the exposure time, the second shooting parameter and the third shooting parameter only include the exposure time, and if the first shooting parameter includes the exposure time, the aperture size and the shutter speed, the second shooting parameter and the third shooting parameter also include the exposure time, the aperture size and the shutter speed. The second shooting parameter can reduce the exposure degree of the shot object (showing that the brightness of the shot object is reduced) compared with the first shooting parameter, and the third shooting parameter can improve the exposure degree of the shot object (showing that the brightness of the shot object is improved) compared with the first shooting parameter.
And 104, generating a target image according to the first image, the updated image and the pixel set to be processed.
On the basis of acquiring the second image and/or the third image by shooting based on the corresponding second shooting parameter and/or the third shooting parameter, the first image and the second image and/or the third image can be further subjected to fusion processing according to the position information of the first pixel and/or the second pixel included in the pixel set to be processed, so as to acquire the target image.
Specifically, if the to-be-processed pixel set includes first pixels, the portion of the second image corresponding to each first pixel is correspondingly replaced by each first pixel in the first image, or the portion of the second image corresponding to each second pixel in the first image is subjected to luminance value averaging or weighted averaging and equal processing, and if the to-be-processed pixel set includes second pixels, the portion of the third image corresponding to each second pixel is correspondingly replaced by each second pixel in the first image, or the portion of the third image corresponding to each second pixel in the first image is subjected to luminance value averaging or weighted averaging and equal processing with each second pixel in the first image, so that a target image is obtained, and therefore, over-exposed and/or under-exposed pixel points in the original first image are eliminated, and the problems that defective detail cannot be shot or shooting is not obvious are avoided.
In the process of fusing the first image, the second image and/or the third image, necessary scaling processing can be performed on the corresponding images to make the proportions of the images consistent.
With reference to fig. 2 to 4, fig. 2 is a screen image of a display to be subjected to defect detection, which is captured based on a first shooting parameter, fig. 3 is a pixel region where an overexposure phenomenon exists in the image in fig. 2, fig. 4 is a pixel region where an underexposure phenomenon exists in the image in fig. 2, both fig. 3 and fig. 4 have a series of points whose details are not clearly captured, and if a defect falls on the points in fig. 3 to fig. 4, the defect is difficult to identify, for the points, the defects can be detected based on the predetermined value interval in the present application, and a re-shooting is performed according to the corresponding updated shooting parameter, and then the shooting effect of the points is improved by image fusion processing, thereby reducing misjudgment or erroneous judgment of the algorithm.
As can be seen from the above solutions, the method of the embodiment of the present application, after acquiring the first image of the target object captured with the first capturing parameter, upon determining that at least one pixel that does not satisfy the preset pixel parameter condition exists in at least a partial image area of the first image, determines the updated capturing parameter, and acquires the updated image of at least a partial area of the target object captured with the updated capturing parameter, and then further generates the target image according to the first image and the updated image described above, and the to-be-processed pixel set formed by the pixels that do not satisfy the preset pixel parameter condition described above. According to the method and the device, the updated shooting parameters are determined, the updated image shot by the updated shooting parameters is obtained, and the pixels which do not meet the preset pixel parameter condition in the first image are subjected to optimization processing of shooting details by the updated image, so that the problems that the defect details cannot be shot or are not obvious in shooting in screen defect detection of the display and the like are solved, and further the misjudgment or misjudgment probability of the algorithm is reduced.
In addition, in the embodiment, the low, medium and high sets of exposure shooting parameters corresponding to the object to be detected are determined in advance, and a series of overexposed pixels in the first image are adjusted to adopt the low exposure shooting parameters for uniform rephotography, and a series of underexposed pixels are adjusted to adopt the high exposure shooting parameters for uniform rephotography, so that the condition that each pixel point which is not in the set value interval is judged and then the exposure parameters are adjusted to execute the rephotography operation can be avoided, the data processing is accelerated, the processing time consumption is reduced, and meanwhile, the requirements of intelligent manufacturing are better met.
The applicant finds that under-exposure or over-exposure is a main reason causing screen defect details to be not shot or shot unobviously when the defect detection of the display screen is realized through image shooting, and based on the characteristics, in order to reduce the probability of algorithm misjudgment or misjudgment in the defect detection scene of objects such as the display screen, the embodiment of the application provides the optimal under-exposure and over-exposure threshold range matched with the defect detection scene in the industrial detection field. Through the practice of mass analysis and algorithms (defect detection algorithms) of millions of pictures on a production line, if the image gray/brightness exceeds a preferred threshold range, such as 30-230, some defects (such as bright spots and dark spots) of an LCD screen can not be shot obviously or can not be shot at all, and the contrast of the defects is poor.
Therefore, in the embodiment of the application, preferably, the under-exposure and over-exposure reference is set to be beyond the gray level/brightness of the image being 30-230, wherein the image is over-exposed and under-exposed, both of which affect the image details, resulting in poor contrast of the screen defect and difficulty in accurately detecting the defect.
The above-mentioned preset pixel parameter conditions are preferably set to: the grey value and/or the brightness value of the pixel is in the interval 30, 230.
On the basis, in some embodiments, the method shown in fig. 1 may perform, after acquiring the first image, a grayscale processing on the first image, convert the first image into a grayscale image, determine whether there are pixels whose grayscale values are not [30, 230] in at least a partial image region of the grayscale processed first image, and if there are first pixels whose grayscale values exceed 230 and/or there are second pixels whose grayscale values are lower than 30, take the first pixels and/or the second pixels as the to-be-processed pixel set. The first pixel is a general name of a series of overexposed pixel points in the first image, and the second pixel is a general name of a series of underexposed pixel points in the first image.
The at least partial image area of the first image may refer to the entire area of the first image, or refer to an image area corresponding to a target object (such as a screen of a display screen) in the first image.
In the latter case, preferably, after the first image of the target object captured by the first capturing parameter is obtained and before the first image is subjected to the gray scale processing, the first image may be subjected to image segmentation processing, an image area corresponding to the target object in the first image is extracted, and other parts are filtered out. In practical application, based on a machine vision algorithm, image segmentation may be performed on the first image, and a region of interest (ROI) therein is extracted, where the ROI is an image region corresponding to the target object, such as an image region corresponding to a screen of a display screen, and an image portion corresponding to a portion outside the screen, such as a frame or a background (a table top) of the display screen, is filtered. To filter out irrelevant parts and only the region of interest is processed.
In an embodiment, referring to the flowchart of the image processing method provided in fig. 5, the image processing method disclosed in the present application may further include, after step 104:
and 105, carrying out defect identification processing on the target image to identify the defects of the target object.
Specifically, the target image may be detected, but not limited to, by invoking AOI algorithm, so as to identify the defect of the target object, such as a display screen.
When the image originally shot by the target object has the underexposure/overexposure phenomenon, the shooting parameters are adjusted to shoot again, and the images shot for multiple times are subjected to fusion processing to eliminate the part with insufficient or over-bright brightness in the target object, so that the problem that the defect details in the image of the target object are not shot clearly or are not shot is solved, the accuracy of defect detection on the target object can be finally further improved, and the algorithm misjudgment or misjudgment probability is reduced.
In an embodiment, referring to the flowchart of the image processing method provided in fig. 6, the image processing method disclosed in the present application may further include, before step 101:
601, acquiring configuration information of a target object, and acquiring a shooting parameter set matched with the configuration information of the target object to obtain a target shooting parameter set; different objects having different configuration information correspond to different sets of photographing parameters, respectively.
In order to further meet the requirement of intelligent manufacturing, the embodiment of the application determines in advance, through analysis of big data, such as big data analysis of cloud-end batch positive and negative samples, the specific N groups of shooting parameters, such as the above three groups of low, medium and high exposure shooting parameters, corresponding to different exposure performances, of each configured object to be detected (such as displays of different models).
The positive sample can be a display screen image with normal exposure of defect details and a better defect detail shooting effect, and the negative sample can be a display screen image with abnormal exposure of defect details, un-shot defect details or unobvious shooting. The method comprises the steps of setting three groups of exposure shooting parameters including low, middle and high for each configured object to be detected by analyzing shooting parameters corresponding to positive and negative samples of the object to be detected in batches in different configurations of a cloud, wherein the three groups of exposure shooting parameters including low, middle and high for the object to be detected in different configurations have different values, so that the shooting equipment is supported to call matched shooting parameter sets to quickly adjust exposure and shoot again aiming at the object to be detected in a certain configuration in a targeted manner.
On this basis, for the target object to be detected, configuration information of the target object to be detected, including but not limited to Serial Number (SN), model Number, size and other information of a display screen such as an LCD, may be acquired first. In one embodiment, an electronic code such as a two-dimensional code or a barcode carrying configuration information of the target object may be bound to the target object in advance, for example, a paper electronic code is attached to a display screen, or the electronic code is displayed on a lighted display screen, and before photographing the target object, the electronic code is scanned to obtain configuration information such as a model number and a serial number of the target object.
And then, according to the configuration information of the target object to be detected, such as scanning, analyzing and shooting the two-dimensional code/electronic code, calling the exposure parameter set matched with the configuration information from the cloud end to obtain the target shooting parameter set of the current target object to be detected. The target shooting parameter set includes three groups of shooting parameters, namely, a middle shooting parameter, a low shooting parameter and a high shooting parameter, which respectively represent the first shooting parameter, the second shooting parameter and the third shooting parameter described above in the present application.
Optionally, the preset high, medium, and low three groups of shooting parameters corresponding to each configuration may also be preset at the shooting device end, and the matching shooting parameter set (including the high, medium, and low three groups of shooting parameters) may be directly called at the shooting device end according to the configuration information of the current object to be detected, which is not limited in this embodiment.
On the basis, calling the middle exposure shooting parameter in the target shooting parameter set, taking the middle exposure shooting parameter as the first shooting parameter to shoot the target object, and continuing to execute each subsequent step of the method shown in fig. 1 or fig. 5 until the target image is obtained or the defect detection of the target object is finished.
According to the embodiment, through the big data analysis of the cloud-end batch positive and negative samples, three groups of low, medium and high exposure shooting parameters are set for each configured object to be detected in a targeted manner in advance, so that the equipment can quickly call or adjust the shooting parameters related to exposure for each configured object to be detected to perform image shooting, the image processing speed is accelerated, and the defect identification speed of the object to be detected such as a display is correspondingly accelerated.
The embodiment of the present application further discloses an electronic device, a composition structure of which is shown in fig. 7, including:
an image acquisition device 701.
The image capturing device may include, for example, a camera module of the electronic device. It is used to take images of the device under test and is not limited to the first, second, third images described above.
A memory 702 for storing at least one set of instructions.
The set of instructions may be embodied in the form of a computer program.
A processor 703 for implementing the image processing method as disclosed in any of the above method embodiments by executing the instruction set in the memory.
The processor 703 may be a Central Processing Unit (CPU), an application-specific integrated circuit (ASIC), a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device.
Besides, the electronic device may further include a communication interface, a communication bus, and the like. The memory, the processor and the communication interface communicate with each other via a communication bus.
The communication interface is used for communication between the electronic device and other devices. The communication bus may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like, and may be divided into an address bus, a data bus, a control bus, and the like.
It should be noted that, in the present specification, the embodiments are all described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments may be referred to each other.
For convenience of description, the above system or apparatus is described as being divided into various modules or units by function, respectively. Of course, the functionality of the units may be implemented in one or more software and/or hardware when implementing the present application.
From the above description of the embodiments, it is clear to those skilled in the art that the present application can be implemented by software plus necessary general hardware platform. Based on such understanding, the technical solutions of the present application may be essentially or partially implemented in the form of a software product, which may be stored in a storage medium, such as a ROM/RAM, a magnetic disk, an optical disk, etc., and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method according to the embodiments or some parts of the embodiments of the present application.
Finally, it is further noted that, herein, relational terms such as first, second, third, fourth, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The foregoing is only a preferred embodiment of the present application and it should be noted that those skilled in the art can make several improvements and modifications without departing from the principle of the present application, and these improvements and modifications should also be considered as the protection scope of the present application.
Claims (10)
1. An image processing method comprising:
acquiring a first image of a target object shot by first shooting parameters;
determining that at least one pixel which does not meet the condition of a preset pixel parameter exists in at least one partial image area of the first image to obtain a pixel set to be processed;
determining updated shooting parameters and acquiring an updated image of at least a partial region of the target object shot by the updated shooting parameters; the at least partial region at least comprises a set of points corresponding to the pixel set to be processed on the target object;
and generating a target image according to the first image, the updated image and the pixel set to be processed.
2. The method according to claim 1, wherein the determining that at least one pixel which does not meet a preset pixel parameter condition exists in at least one partial image area of the first image to obtain a to-be-processed pixel set comprises:
and determining at least one pixel of which the pixel gray value and/or the brightness value are not in a preset value interval in at least one partial image area of the first image to obtain the pixel set to be processed.
3. The method according to claim 2, determining updated shooting parameters and acquiring an updated image of at least a partial region of the target object shot with the updated shooting parameters, comprising:
if the pixel set to be processed comprises first pixels of which the pixel parameter values are larger than the upper threshold value of the preset value interval, determining second shooting parameters, and acquiring a second image of the first point set shot by the second shooting parameters; the first point set at least comprises a set of points corresponding to the first pixels on the target object;
if the pixel set to be processed comprises second pixels of which the pixel parameter values are smaller than the lower threshold value of the preset value-taking interval, determining a third shooting parameter, and acquiring a third image of a second point set shot by the third shooting parameter; the second point set at least comprises a set of points corresponding to the second pixels on the target object;
the parameter types of the second shooting parameters and the third shooting parameters are the same as the parameter type of the first shooting parameters, the exposure degree of the shot object can be reduced by the second shooting parameters compared with the first shooting parameters, and the exposure degree of the shot object can be improved by the third shooting parameters compared with the first shooting parameters;
generating a target image according to the first image, the updated image and the to-be-processed pixel set, including:
and generating a target image according to the first image, the second image and/or the third image and the pixel set to be processed.
4. The method of claim 3, the determining second shooting parameters, comprising:
determining shooting parameters matched with pixel parameter values of the first pixels from a target shooting parameter set to obtain second shooting parameters;
the determining the third shooting parameter includes:
determining shooting parameters matched with pixel parameter values of the second pixels from the target shooting parameter set to obtain third shooting parameters;
wherein the target photographing parameter set further includes the first photographing parameter.
5. The method of claim 3, the generating a target image from the first image, and the second image and/or the third image, and the set of pixels to be processed, comprising:
and according to the position information of the first pixel and/or the second pixel included in the pixel set to be processed, carrying out fusion processing on the first image and the second image and/or the third image to obtain a target image.
6. The method of claim 4, wherein the target object is a display screen;
before the acquiring the first image of the target object captured with the first capturing parameter, the method further includes:
acquiring the configuration information of the target object, and acquiring a shooting parameter set matched with the configuration information of the target object to obtain the target shooting parameter set; different objects with different configuration information respectively correspond to different shooting parameter sets;
and acquiring the first shooting parameters from the target shooting parameter set, and shooting the target object by using the first shooting parameters.
7. The method of claim 1, further comprising, prior to the determining whether at least one pixel having a display parameter that does not satisfy a parameter condition is present in at least a portion of an image region of the first image:
and performing image segmentation processing on the first image to obtain an image area corresponding to the target object in the first image, so as to process the image area corresponding to the target object.
8. The method of claim 2, wherein the predetermined interval is[30，230]。
9. The method of claim 1, further comprising, after generating and outputting the target image:
and carrying out defect identification processing on the target image so as to identify the defects of the target object.
10. An electronic device, comprising:
an image acquisition device;
a memory for storing at least one set of instructions;
a processor for implementing the image processing method of any one of claims 1 to 9 by executing the set of instructions in the memory.
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