Image quality detection method, display equipment, device and computer readable storage medium

Abstract

The invention discloses an image quality detection method, display equipment, a device and a computer readable storage medium, and belongs to the technical field of display. The image quality detection method comprises the following steps: dividing a current display image into a plurality of areas based on a preset partition mode; performing subarea pixel detection and / or combined area detection on each area to obtain a detection result; and starting an image quality detection function under the condition that the detection result is that the image is abnormal. According to the method and the device, the single display picture is divided into the plurality of regions, and then the plurality of regions are subjected to partition pixel detection and / or combined region area detection, so that the picture abnormity problem of the display equipment can be more accurately detected, and then the picture quality detection function is started for the picture abnormity problem; the situation of false detection possibly caused by a single picture detection mode can be effectively avoided.

Description

Technical Field

[0001] The present application relates to the field of display technology, and in particular to an image quality detection method, a display device, an apparatus, and a computer-readable storage medium. Background Art

[0002] PDF (Pattern Detection Function) detects abnormal patterns of specific pixels and changes the driving mode of the LCD panel to correct the abnormal pixel pattern display problem.

[0003] Currently, TCONICs (timing controller ICs) in related technologies typically use a single-frame detection mode. For simple, regular images, the TCON IC sets the pixels to be detected. The TCON IC accumulates and superimposes the detected pixels. If the percentage exceeds a pre-set pixel arrangement area threshold, the image quality detection function is activated. However, in practice, this single-frame detection mode can lead to false detections for complex images. Summary of the Invention

[0004] The main purpose of this application is to provide a picture quality detection method, display device, apparatus and computer-readable storage medium, aiming to solve the technical problem that a single picture detection mode may misdetect complex pictures.

[0005] To achieve the above objectives, the present application provides a method for detecting image quality, which includes:

[0006] Divide the current display screen into multiple areas based on a preset partitioning method;

[0007] Performing a subarea pixel detection and / or a combined area detection on each of the regions to obtain a detection result;

[0008] When the detection result indicates that there is an abnormal image problem, the image quality detection function is activated.

[0009] In one embodiment, the step of performing pixel detection on each of the regions to obtain a detection result includes:

[0010] Obtaining the number of abnormal pixels contained in each of the regions;

[0011] The number of abnormal pixels is compared with a preset pixel threshold, and the obtained comparison result is used as the detection result.

[0012] In one embodiment, when the detection result indicates that an abnormal image problem exists, the step of activating the image quality detection function includes:

[0013] If the detection result shows that the number of abnormal pixels contained in at least one of the regions is greater than or equal to the preset pixel threshold, starting the image quality detection function; or

[0014] When the detection result shows that the number of abnormal pixels contained in each of the regions is greater than or equal to the preset pixel threshold, the image quality detection function is activated.

[0015] In one embodiment, the step of performing combined area detection on each of the regions to obtain a detection result includes:

[0016] Combining the regions to obtain a plurality of sub-pictures; wherein the area of ​​each sub-picture is smaller than or equal to the area of ​​the current display picture;

[0017] Abnormal area detection is performed on the multiple sub-pictures to obtain a detection result.

[0018] In one embodiment, the step of combining the regions to obtain a plurality of sub-pictures includes:

[0019] Each of the regions is combined with at least one adjacent region to obtain a plurality of sub-pictures.

[0020] In one embodiment, the step of performing abnormal area detection on the plurality of sub-pictures to obtain a detection result includes:

[0021] Obtaining the abnormal area of ​​each sub-picture;

[0022] The abnormal area is compared with a preset area threshold, and the obtained comparison result is used as the detection result.

[0023] In one embodiment, when the detection result indicates that an abnormal image problem exists, the step of activating the image quality detection function includes:

[0024] If the detection result shows that there is at least one sub-picture with an abnormal area greater than or equal to a preset area threshold, starting the image quality detection function; or

[0025] When the detection result shows that the abnormal area of ​​each sub-picture is greater than or equal to a preset area threshold, the image quality detection function is activated.

[0026] In addition, to achieve the above-mentioned purpose, the present application also provides a display device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the image quality detection method as described above.

[0027] In addition, to achieve the above-mentioned purpose, the present application further provides a display device, comprising:

[0028] A partitioning module, configured to divide the current display screen into a plurality of areas based on a preset partitioning method;

[0029] A detection module, configured to perform pixel detection on each of the regions and / or area detection on each of the regions to obtain a detection result;

[0030] The processing module is used to start the image quality detection function when the detection result shows that there is an abnormal image problem.

[0031] In addition, to achieve the above-mentioned purpose, the present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the image quality detection method described above are implemented.

[0032] The present application proposes a method for detecting image quality, a display device, an apparatus, and a computer-readable storage medium. In the method, the current display screen is first divided into multiple areas based on a preset partitioning method; then, each of the areas is subjected to partition pixel detection and / or combined area detection to obtain a detection result; and then, if the detection result indicates that there is an abnormal image problem, the image quality detection function is activated. The embodiment of the present application divides a single display screen into multiple areas, and then performs partition pixel detection and / or combined area detection on the multiple areas, so as to more accurately detect abnormal image problems of the display device, and then activate the image quality detection function for the abnormal image problem, thereby improving the detection rate of the image quality detection function and effectively avoiding the situation where a single image detection mode may cause false detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only part of the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0034] Figure 1 A flowchart of an image quality detection method provided in an embodiment of the present application;

[0035] Figure 2 A schematic diagram of an application scenario of dividing a display screen involved in a method for detecting image quality provided in an embodiment of the present application;

[0036] Figure 3 for Figure 1 A detailed flow chart of step S20;

[0037] Figure 4 for Figure 1 Another detailed flow chart of step S20;

[0038] Figure 5 A schematic structural diagram of a display device provided in an embodiment of the present application;

[0039] Figure 6 A schematic structural diagram of a display device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0040] In the following description, specific details such as specific system structures and technologies are provided for illustration rather than limitation to facilitate a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the embodiments of the present application can also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the embodiments of the present application.

[0041] Television (TV), MNT (Monitor) and other display devices always have some special images that are not ideal or have some problems. For example, some images consume a lot of power. In this case, it is necessary to reduce the power consumption of this image. According to the power consumption formula P = CfV 2 As shown in Figure 2, C is the parasitic capacitance, a characteristic of the display panel that cannot be changed; f is the frequency of voltage charge and discharge; and V is the voltage range for charge and discharge. Therefore, by reducing the brightness of bright pixels and increasing the brightness of dark pixels, the voltage difference of the same data output can be reduced to reduce power consumption. However, this can result in suboptimal display effects on some images. In such cases, this can be resolved by changing the horizontal drive method of the pixels. The PDF (Pattern Detection Function) detects abnormal patterns in specific pixels and changes the LCD panel drive method or data voltage difference, thereby resolving specific image anomalies.

[0042] Currently, TCONICs (timing controller ICs) in related technologies generally use a single-frame detection mode. For simple, regular images, the pixels to be detected are set. The TCON IC accumulates and superimposes the detected pixels. If the proportion exceeds a pre-set pixel layout area threshold, the image quality detection function is activated. However, in actual applications, this single-frame detection mode has the potential for false detection for complex images. For many complex images, it is not possible to set a pixel layout area threshold in this way. This is because setting the threshold too high may result in no detection, while setting the threshold too low may easily lead to false detection. For example, a single image (Image 1) may contain pixel states such as dot on / off, V-stripe (vertical stripes), and H-stripe (horizontal stripes) (referred to as Region 1, Region 2, and Region 3). Combining Region 1 and Region 2 in a single image may result in image anomalies. However, combining Region 1 or Region 2 with other images in a single image (Image 2) may be fine. Therefore, Image Quality Detection does not need to be added to Image 2. In this case, simply detecting a single image (e.g., Image 2) may result in false detections.

[0043] Based on this, the embodiments of the present application provide a picture quality detection method, display device, apparatus and computer-readable storage medium. By dividing a single display screen into multiple areas, and then performing partitioned pixel detection and / or combined area detection on the multiple areas, it is possible to more accurately detect abnormal screen problems of the display device, and then activate the picture quality detection function for the abnormal screen problems, thereby improving the detection rate of the picture quality detection function, and at the same time effectively avoiding the situation where a single screen detection mode may cause false detection.

[0044] The image quality detection method, display device, apparatus, and computer-readable storage medium provided in the embodiments of the present application are specifically described through the following embodiments. First, the image quality detection method in the embodiments of the present application is described.

[0045] The present application embodiment provides a method for detecting image quality, referring to Figure 1 , Figure 1 A flow chart of a method for detecting image quality provided in an embodiment of the present application is provided. The method for detecting image quality can be applied to a display device, such as Figure 1 As shown, the image quality detection method provided by this embodiment includes steps S10 to S30.

[0046] Step S10, dividing the current display screen into multiple areas based on a preset partitioning method;

[0047] In this embodiment, the current display screen of the display device can be divided into several different areas based on a preset partitioning method, such as Figure 2 As shown, the preset partitioning method can be based on pixel status such as dot on / off, V-stripe (vertical stripes), H-stripe (horizontal stripes), dividing the current display screen into three areas S1, S2, and S3.

[0048] It is understandable that if Figure 2 The division method shown is only an optional example of a preset partitioning method. For a more complex display screen, the current display screen can be divided into more areas according to actual needs, and this embodiment does not limit this.

[0049] Step S20, performing a subarea pixel detection and / or a combined area detection on each area to obtain a detection result;

[0050] In this embodiment, after the screen partitioning is completed, the TCONIC (timing controller IC, main chip timing controller / main chip timing control circuit) in the display device can be used to simultaneously detect whether there is any screen abnormality in each area, thereby obtaining a detection result, and then deciding whether to start the image quality detection function based on the detection result. The specific method of detecting whether there is any screen abnormality can be partition pixel detection (abnormal pixel detection in each area separately), or combined area detection (each area is combined into multiple sub-screens for abnormal area detection), or a combination of the two detection methods, and this embodiment does not impose any restrictions on this.

[0051] In other words, this embodiment no longer determines whether to activate the image quality detection function based solely on the detection results of a single screen as in the related art. Instead, the single display screen is divided into multiple areas, and the detection results of multiple areas are comprehensively considered before determining whether to activate the image quality detection function. This allows for more accurate image quality detection, improves the detection rate of the image quality detection function, and avoids false detection.

[0052] In step S30 , if the detection result shows that there is an abnormal image problem, the image quality detection function is activated.

[0053] It is understandable that if the detection result obtained based on step S20 is that there is an abnormal image problem, the image quality detection function should be activated to correct the abnormal pixel pattern display problem; conversely, if the detection result obtained based on step S20 is that there is no abnormal image problem, there is no need to activate the image quality detection function.

[0054] Reference Figure 3 In some feasible embodiments, the step of performing pixel detection on each region in step S20 to obtain the detection result may specifically include:

[0055] Step S201, obtaining the number of abnormal pixels contained in each area;

[0056] In step S202 , the number of abnormal pixels is compared with a preset pixel threshold, and the obtained comparison result is used as the detection result.

[0057] In this embodiment, a method for implementing whether a detection area will cause special image abnormalities is provided, namely, obtaining the number of abnormal pixels contained in each area in real time, and determining the detection result based on the comparison result of the number of abnormal pixels and the preset pixel threshold, wherein the preset pixel threshold is a reference value for measuring whether the number of abnormal pixels is too much, thereby causing image abnormality problems. The specific value can be set according to actual conditions, and this embodiment does not limit this.

[0058] In this embodiment, whether a region contains abnormal pixels can be determined in the following manner:

[0059] Color Histogram Analysis: Calculates the color histogram of an area, counting the frequency of each color. Normally, the histogram distribution should be consistent with the subject and content of the image. For example, a landscape photo with a blue sky should have a high frequency of blue in the histogram. However, the presence of abnormal pixels may cause the histogram to have unusual peaks or inconsistent color distribution. For example, if a large number of green pixels suddenly appear in an area of ​​the sky that was originally dominated by blue, the proportion of green in the histogram will increase unreasonably.

[0060] Pixel value distribution statistics: Perform statistical analysis on the pixel values ​​(such as RGB values) in the area. Statistics such as the mean and standard deviation of pixel values ​​can be calculated. For a normal image, the distribution of pixel values ​​should be within a certain range and have a certain regularity. For example, in a grayscale image, the pixel values ​​should be evenly distributed between 0 and 255 (assuming it is an 8-bit image). If abnormal pixels appear, it may cause a large deviation in the mean or standard deviation of the pixel values. For example, if a very bright pixel suddenly appears in an image area that should be dark, this will increase the mean of the pixel values ​​in that area.

[0061] Edge detection algorithms (such as Sobel and Canny) are used to find edges in an image. Normally, edges should be continuous and conform to the shape of the object. However, the presence of abnormal pixels may cause edges to appear broken, discontinuous, or inconsistent with the actual shape of the object. For example, in a photograph of an architectural building, the edges should be smooth and continuous. If the edge detection algorithm detects abrupt breakpoints or unusual curvature, it may be due to interference from abnormal pixels.

[0062] Noise detection algorithm: A noise detection algorithm is used to identify possible noise pixels, also known as anomalous pixels. Common noise models include Gaussian noise and salt and pepper noise. For salt and pepper noise, the algorithm identifies isolated black or white pixels, which may be anomalous pixels. For example, in a scanned document image, if salt and pepper noise is present, small black or white dots will be scattered between the text and background. The noise detection algorithm can identify these dots.

[0063] Image filtering aids detection: First, use image filtering methods (such as median filtering and mean filtering) to process the image. The filtered image is then compared with the original image. If a pixel changes significantly before and after filtering, it may be an anomaly. For example, median filtering can remove salt and pepper noise. If there is a salt and pepper noise point in the original image, after median filtering, the pixel values ​​around the point will replace the value of the anomaly point, and the anomaly can be detected through comparison.

[0064] In some feasible embodiments, the above step S30 may include:

[0065] Step S301: if the detection result shows that the number of abnormal pixels in at least one region is greater than or equal to a preset pixel threshold, start the image quality detection function; or

[0066] In step S302 , when the detection result shows that the number of abnormal pixels in each region is greater than or equal to a preset pixel threshold, the image quality detection function is activated.

[0067] In this embodiment, two conditions for activating the image quality detection function are provided as examples. One is that as long as the number of abnormal pixels contained in a region is detected to be greater than or equal to a preset pixel threshold, the detection result is determined to be a picture abnormality problem and the image quality detection function is activated. This method will result in a high activation frequency of the image quality detection function. The other is that the number of abnormal pixels contained in all regions must be greater than or equal to the preset pixel threshold before the detection result is determined to be a picture abnormality problem and the image quality detection function is activated. This method will result in a low activation frequency of the image quality detection function. In actual applications, one of the conditions can be selected as the condition for activating the image quality detection function according to actual needs, and other conditions can also be set based on this. This embodiment does not limit this.

[0068] Reference Figure 4 In some feasible embodiments, the step of performing combined area detection on each of the regions and obtaining the detection result in the above step S20 may specifically include:

[0069] Step S21: combining the regions to obtain a plurality of sub-pictures; wherein the area of ​​each sub-picture is smaller than or equal to the area of ​​the current display picture;

[0070] Step S22: performing abnormal area detection on multiple sub-pictures to obtain detection results.

[0071] In this embodiment, the areas divided in the above embodiment can be combined and then the sub-pictures formed can be detected. The method of detecting each sub-picture can also be implemented based on the method of detecting areas provided in the above embodiment, which will not be described in detail here.

[0072] In some feasible embodiments, the above step S21 may include:

[0073] Step S211 : combining each region with at least one adjacent region to obtain a plurality of sub-pictures.

[0074] In this embodiment, the areas with a common boundary can be regarded as adjacent areas, and a sub-image can be obtained by combining at least two adjacent areas. Figure 2 Taking the three areas shown as an example, S1 and S2 can be combined to obtain a sub-screen, S2 and S3 can be combined to obtain a sub-screen, and S1 and S3 can be combined to obtain a sub-screen. In the case where the current display screen is divided into four areas, the three areas can also be combined to obtain a sub-screen, and so on. The more areas the current display screen is divided into by preset partitioning methods, the more feasible combinations of sub-screens there are, and this embodiment does not limit this.

[0075] In some feasible embodiments, the above step S22 may include:

[0076] Step S221, obtaining the abnormal area of ​​each sub-picture;

[0077] Step S222: compare the abnormal area with a preset area threshold, and use the comparison result as the detection result.

[0078] In this embodiment, the abnormal area of ​​the sub-screen can be inferred based on the number of abnormal pixels contained in the detection area provided in the above embodiment. After the number of abnormal pixels is known, the area occupied by each abnormal pixel in a sub-screen is accumulated, which is the abnormal area of ​​the sub-screen, and the detection result is determined based on the comparison result of the abnormal area and the preset area threshold. Among them, the preset area threshold is a reference value for measuring whether the abnormal area of ​​the sub-screen is too large, thereby causing the screen abnormality problem. Its specific value can be set according to actual conditions, and this embodiment does not limit this.

[0079] In some feasible embodiments, the above step S30 may further include:

[0080] Step S31: if the detection result shows that there is at least one sub-picture with an abnormal area greater than or equal to a preset area threshold, start the image quality detection function; or

[0081] In step S32 , when the detection result shows that the abnormal area of ​​each sub-picture is greater than or equal to the preset area threshold, the image quality detection function is activated.

[0082] In this embodiment, two conditions for activating the image quality detection function are provided as examples. One is that as long as the abnormal area of ​​a sub-screen is detected to be greater than or equal to a preset area threshold, the detection result is determined to be a picture abnormality problem and the image quality detection function is activated. This method results in a high activation frequency of the image quality detection function. The other is that the abnormal area of ​​all sub-screens must be greater than or equal to the preset area threshold before the detection result is determined to be a picture abnormality problem and the image quality detection function is activated. This method results in a low activation frequency of the image quality detection function. In actual applications, one of these conditions can be selected as the condition for activating the image quality detection function according to actual needs, and other conditions can also be set based on this. This embodiment does not limit this.

[0083] In addition, the present application also provides a display device, referring to Figure 5 , Figure 5 A schematic diagram of the structure of a display device provided in an embodiment of the present application is shown in FIG. Figure 5 As shown, in this embodiment, the display device includes: a partitioning module 100 , a detection module 200 and a processing module 300 .

[0084] The partition module 100 is used to divide the current display screen into multiple areas based on a preset partitioning method;

[0085] The detection module 200 is used to perform pixel detection of each region and / or area detection of the combined region to obtain a detection result;

[0086] The processing module 300 is configured to activate the image quality detection function when the detection result indicates that an image abnormality exists.

[0087] In some feasible embodiments, the detection module 200 is further configured to obtain the number of abnormal pixels contained in each region; compare the number of abnormal pixels with a preset pixel threshold, and use the obtained comparison result as the detection result.

[0088] In some feasible embodiments, the processing module 300 is also used to start the image quality detection function when the detection result is that the number of abnormal pixels contained in at least one area is greater than or equal to a preset pixel threshold; or, when the detection result is that the number of abnormal pixels contained in each area is greater than or equal to the preset pixel threshold, start the image quality detection function.

[0089] In some feasible embodiments, the detection module 200 is further used to combine the regions to obtain multiple sub-screens; wherein the area of ​​each sub-screen is less than or equal to the area of ​​the current display screen; and perform abnormal area detection on the multiple sub-screens to obtain detection results.

[0090] In some feasible embodiments, the detection module 200 is further configured to combine each region with at least one adjacent region to obtain a plurality of sub-pictures.

[0091] In some feasible embodiments, the detection module 200 is further configured to obtain an abnormal area of ​​each sub-picture; compare the abnormal area with a preset area threshold, and use the obtained comparison result as a detection result.

[0092] In some feasible embodiments, the processing module 300 is further used to activate the image quality detection function when the detection result is that the abnormal area of ​​at least one sub-screen is greater than or equal to a preset area threshold; or, when the detection result is that the abnormal area of ​​each sub-screen is greater than or equal to the preset area threshold, activate the image quality detection function.

[0093] The display device provided in this embodiment and the image quality detection method provided in the above embodiment belong to the same technical concept. Technical details not fully described in this embodiment can be referred to any of the above embodiments, and this embodiment has the same beneficial effects as executing the image quality detection method.

[0094] In addition, an embodiment of the present application also provides a display device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the image quality detection method in any of the above embodiments.

[0095] Reference below Figure 6 , which shows a schematic diagram of the structure of a display device suitable for implementing the embodiments of the present application. The display device in the embodiments of the present application may include, but is not limited to, any product or component with a display function, such as a television, monitor, mobile phone, tablet computer, laptop computer, digital photo frame, navigation system, etc. Figure 6 The display device shown is merely an example and should not limit the functions and scope of use of the embodiments of the present application.

[0096] like Figure 6As shown, the display device may include a processing device 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory 1002 or a program loaded from a storage device 1003 into a random access memory 1004. The random access memory 1004 also stores various programs and data required for the operation of the display device. The processing device 1001, the read-only memory 1002, and the random access memory 1004 are connected to each other via a bus 1005. An input / output interface 1006 is also connected to the bus. Typically, the following systems can be connected to the input / output interface 1006: an input device 1007 including, for example, a touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; an output device 1008 including, for example, a speaker, vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the display device to communicate with other devices wirelessly or by wire to exchange data. Although the figures show a display device with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems may be implemented or have instead.

[0097] In particular, according to the embodiments disclosed in the present application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, the embodiments disclosed in the present application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program comprising program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via a communication device, or installed from a storage device 1003, or installed from a read-only memory 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are performed.

[0098] The beneficial effects of the display device provided in this application are the same as the beneficial effects of the image quality detection method provided in the above embodiment, and other technical features in the display device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0099] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0100] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

[0101] In addition, an embodiment of the present application also provides a computer-readable storage medium, which can be a non-volatile computer-readable storage medium. A computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the image quality detection method provided in any of the above embodiments is implemented.

[0102] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems or devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0103] The computer-readable storage medium may be included in the electronic device, or may exist independently without being incorporated into the electronic device.

[0104] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by an electronic device, the electronic device implements the image quality detection method.

[0105] Computer program code for performing the operations of the present application may be written in one or more programming languages, or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0106] The flow charts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, program segment or a part of code, and the module, program segment or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented by a dedicated hardware-based system that performs the specified function or operation, or can be implemented by a combination of dedicated hardware and computer instructions.

[0107] The modules described in the embodiments of the present application may be implemented in software or hardware, wherein the name of a module does not necessarily limit the unit itself.

[0108] The readable storage medium provided in this embodiment is a computer-readable storage medium, which stores computer-readable program instructions (i.e., a computer program) for executing the above-mentioned image quality detection method. The beneficial effects of the computer-readable storage medium provided in this application are the same as the beneficial effects of the image quality detection method provided in the above-mentioned embodiment, and will not be repeated here.

[0109] In addition, an embodiment of the present application further provides a computer program product, including a computer program, which implements the image quality detection method provided in any of the above embodiments when executed by a processor.

[0110] The computer program product provided in this embodiment and the image quality detection method proposed in the above embodiment belong to the same technical concept. Compared with the relevant technology, the beneficial effects of the computer program product provided in this application are the same as the beneficial effects of the image quality detection method provided in the above embodiment, which will not be repeated here.

[0111] It should be noted that although a logical order is shown in the flowcharts, in some cases, the steps shown or described may be performed in a different order than that shown in the flowcharts. The terms "first," "second," and the like in the specification, claims, and drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0112] It should also be understood that references to "one embodiment" or "some embodiments" in the description of the embodiments of the present application mean that one or more embodiments of the embodiments of the present application include specific features, structures, or characteristics described in conjunction with the embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in other embodiments," etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but rather mean "one or more but not all embodiments," unless otherwise specifically emphasized. The terms "including," "comprising," "having," and their variations all mean "including but not limited to," unless otherwise specifically emphasized.

[0113] The above is a specific description of some implementation methods of the embodiments of the present application, but the embodiments of the present application are not limited to the above implementation methods. Technical personnel familiar with this field can also make various equivalent modifications or substitutions without violating the spirit of the embodiments of the present application. These equivalent modifications or substitutions are all included in the scope defined by the claims of the embodiments of the present application.

Claims

1. A method for detecting image quality, characterized in that: The image quality detection method includes: Divide the current display screen into multiple areas based on a preset partitioning method; Performing a subarea pixel detection and / or a combined area detection on each of the regions to obtain a detection result; When the detection result indicates that there is an abnormal image problem, the image quality detection function is activated.

2. The image quality detection method according to claim 1, wherein: The step of performing partition pixel detection on each of the regions to obtain a detection result includes: Obtaining the number of abnormal pixels contained in each of the regions; The number of abnormal pixels is compared with a preset pixel threshold, and the obtained comparison result is used as the detection result.

3. The image quality detection method according to claim 2, wherein: The step of activating the image quality detection function when the detection result indicates that an abnormal image problem exists includes: If the detection result shows that the number of abnormal pixels contained in at least one of the regions is greater than or equal to the preset pixel threshold, starting the image quality detection function; or When the detection result shows that the number of abnormal pixels contained in each of the regions is greater than or equal to the preset pixel threshold, the image quality detection function is activated.

4. The image quality detection method according to claim 1, wherein: The step of performing combined area detection on each of the regions to obtain a detection result includes: Combining the regions to obtain a plurality of sub-pictures; wherein the area of ​​each sub-picture is smaller than or equal to the area of ​​the current display picture; Abnormal area detection is performed on the multiple sub-pictures to obtain a detection result.

5. The image quality detection method according to claim 4, wherein: The step of combining the regions to obtain a plurality of sub-pictures includes: Each of the regions is combined with at least one adjacent region to obtain a plurality of sub-pictures.

6. The image quality detection method according to claim 4, wherein: The step of performing abnormal area detection on the plurality of sub-pictures to obtain a detection result includes: Obtaining the abnormal area of ​​each sub-picture; The abnormal area is compared with a preset area threshold, and the obtained comparison result is used as the detection result.

7. The image quality detection method according to claim 6, wherein: The step of activating the image quality detection function when the detection result indicates that an abnormal image problem exists includes: If the detection result shows that there is at least one sub-picture with an abnormal area greater than or equal to a preset area threshold, starting the image quality detection function; or When the detection result shows that the abnormal area of ​​each sub-picture is greater than or equal to a preset area threshold, the image quality detection function is activated.

8. A display device, characterized in that: The display device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the image quality detection method according to any one of claims 1 to 7.

9. A display device, characterized in that: The display device includes: A partitioning module, configured to divide the current display screen into a plurality of areas based on a preset partitioning method; A detection module, configured to perform pixel detection on each of the regions and / or area detection on each of the regions to obtain a detection result; The processing module is used to start the image quality detection function when the detection result shows that there is an abnormal image problem.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the image quality detection method according to any one of claims 1 to 7 are implemented.

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