WO2019196542A1

WO2019196542A1 - Image processing method and apparatus

Info

Publication number: WO2019196542A1
Application number: PCT/CN2019/073831
Authority: WO
Inventors: 杨磊磊; 方刚
Original assignee: 阿里巴巴集团控股有限公司
Priority date: 2018-04-10
Filing date: 2019-01-30
Publication date: 2019-10-17
Also published as: TWI694381B; CN108846399A; TW202001674A

Abstract

Disclosed by the present application are an image processing method and apparatus; first, according to the size of an image to be processed, a standard height and standard width are determined by means of an operation to divide into equal parts; according to the determined standard height and standard width, a matrix consisting of pile points in the image to be processed is determined; then, taking an average gray value of the area around each pile point as a determination condition, it is determined, for each pixel in the image, whether the gray value of the pixel is smaller than the average gray value corresponding to the nearest pile point, and the pixel points are binarized according to result of determination.

Description

Method and device for image processing

Technical field

The present application relates to the field of information technology, and in particular, to a method and an apparatus for image processing.

Background technique

Image binarization is one of the basic operations in image processing, and refers to an image processing method in which the gray value of a pixel on an image is set to 0 or 255.

In the prior art, the process of binarizing an image requires binarization processing for each pixel. Specifically, for each pixel in the image, first, a gray value of each pixel in a preset range with the pixel as a center point may be determined, and then, the determined average gray value of each pixel is calculated, As a threshold corresponding to the pixel, and then determining whether the gray value of the pixel is greater than the threshold, if yes, adjusting the gray value of the pixel to 255, that is, white, if not, adjusting the pixel The gray value is 0, that is, black. Thereby binarizing all pixels in the image to black or white.

Figure 1 is a schematic diagram of the existing binarization. Taking the pixel point A in the image as an example, from top to bottom respectively, the preset range corresponding to the pixel point A is determined first, and then the gray value of each pixel in the preset range is determined, and then the average gray level of each pixel is calculated. Value, finally, based on the numerical value of the gray value of the pixel point A and the average gray value, the gray value of the binarization of the pixel point A is determined.

It can be seen that the existing binarization processing method needs to calculate the average gray value corresponding to each pixel point, so that the calculation amount is large. Therefore, the present specification proposes a new image processing method to solve the defects existing in the prior art.

Summary of the invention

The embodiment of the present invention provides a method and an apparatus for image processing, which are used to solve the problem that the prior art requires a large amount of calculation when the image is binarized, resulting in low processing efficiency.

The embodiments of the present specification adopt the following technical solutions:

A method of image processing, comprising:

Determining the image to be processed;

Determining a standard height and a standard width by halving according to the size of the image to be processed;

Determining a standard height and a standard width as a pitch, and determining a matrix consisting of a plurality of pile points in the image to be processed;

For each pile point, determining an average gray value of a region of a specified area around the pile point as a gray value corresponding to the pile point;

Determining, according to each pixel point in the image to be processed, a pile point closest to the pixel point, determining whether the gray value of the pixel point is smaller than a gray value corresponding to the determined pile point;

If yes, adjusting the gray value of the pixel to a first value;

If not, adjust the gray value of the pixel to a second value.

A device for identifying the uniqueness of a device, comprising:

Determining a module to determine an image to be processed;

An aliquoting module determines the standard height and the standard width by halving according to the size of the image to be processed;

a pile positioning module to determine a standard height and a standard width as a spacing, and determine a matrix consisting of a plurality of pile points in the image to be processed;

a gray scale calculation module, for each pile point, determining an average gray value of a region of a specified area around the pile point as a gray value corresponding to the pile point;

The determining adjustment module determines, for each pixel point in the image to be processed, a pile point closest to the pixel point, and determines whether the gray value of the pixel point is smaller than a gray value corresponding to the determined pile point, and if so, Then, the gray value of the pixel is adjusted to be a first value, and if not, the gray value of the pixel is adjusted to a second value.

An apparatus for image processing, wherein the apparatus comprises: one or more processors and a memory, the memory storing a program, and being configured to perform the following steps by one or more processors:

Determining the image to be processed;

If yes, adjusting the gray value of the pixel to a first value;

If not, adjust the gray value of the pixel to a second value.

The above at least one technical solution adopted by the embodiments of the present specification can achieve the following beneficial effects:

According to the method and device provided by the present specification, the standard height and the standard width are determined by an equal division operation according to the size of the image to be processed, and then the piled point is determined in the image to be processed according to the determined standard height and the standard width. The matrix is then determined by the average gray value of the area around each pile point, and each pixel point in the image to be processed is determined whether the gray value of the pixel point is smaller than the average gray value corresponding to the nearest pile point. And binarizing the pixel points according to the judgment result. Compared with the prior art method for calculating the average gray value corresponding to each pixel point, the method and apparatus provided by the present specification reduce the number of times the average gray value needs to be calculated, and improve the efficiency of binarization in image processing.

DRAWINGS

The drawings described herein are intended to provide a further understanding of the present application, and are intended to be a part of this application. In the drawing:

Figure 1 is a schematic diagram of the existing binarization;

2 is a process of image processing provided by an embodiment of the present specification;

Figure 3 is a number of steps of two-dimensional code preprocessing;

4 is a schematic diagram of determining a pile point in an image to be processed provided by the present specification;

FIG. 5 is a schematic diagram of determining a matrix composed of pile points on an image to be processed provided in the present specification; FIG.

6a and 6b are schematic diagrams provided by the present specification, taking the width of an image to be processed as an example;

7 is a schematic diagram of calculating an average gray value corresponding to each pile point based on the pile point matrix shown in FIG. 5;

FIG. 8 is a schematic diagram showing the presence of a plurality of pile points closest to the distance from the pixel; FIG.

Figure 9 is a schematic diagram of a situation in which misjudgment occurs in binarization;

FIG. 10 is a schematic structural diagram of an apparatus for image processing according to an embodiment of the present disclosure;

FIG. 11 is a schematic structural diagram of an apparatus for image processing according to an embodiment of the present disclosure.

detailed description

The technical solutions of the present application will be clearly and completely described in the following with reference to the specific embodiments of the specification and the accompanying drawings. It is apparent that the described embodiments are only a part of the embodiments of the present application, and not all of them. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the specification without departing from the inventive scope are the scope of the application.

The technical solutions provided by the embodiments of the present application are described in detail below with reference to the accompanying drawings.

2 is a process of image processing provided by an embodiment of the present invention, which may specifically include the following steps:

S100: Determine an image to be processed.

To solve the problem that the calculation amount of the binarization method in the existing image processing is too large, the image processing process provided by one or more embodiments of the present specification is specifically a process of image binarization.

With the development of technology, the performance of devices such as mobile terminals is becoming more and more powerful, so that mobile terminals (such as mobile phones) also have hardware conditions for performing image processing. Therefore, in this specification, it is not limited to which device is responsible for images. Processing. For example, the image processing process can be performed by a server, a mobile phone, a tablet, a personal computer, or the like.

For convenience of description, the image processing procedure performed by the terminal in the following description will be described as an example. Thus, the terminal can first determine the image to be processed. The present application is not limited to whether the image to be processed is generated by the terminal itself, acquired from other devices, or provided by other devices. For example, after the mobile phone takes an image, the image is determined as an image to be processed, or the captured image is provided to the server by the webcam, and the image is determined by the server as the image to be processed, or after the server sends the image acquisition request to the terminal. And determine the image returned by the terminal as the image to be processed.

In addition, since image binarization is one of the basic operations in image processing, and is usually used as a part of the processing steps in some image processing processes, the image binarization process provided in this specification can be used for image processing alone. Operation, or as part of an image processing process, can be used in conjunction with other image processing operations. For example, when the common two-dimensional code is preprocessed, the image processing process is as shown in FIG. 3, and binarization is seen as a loop in the image processing process.

S102: Determine a standard height and a standard width by halving according to the size of the image to be processed.

Since in the existing image binarization process, it is necessary to determine the average gray value corresponding to the area around each pixel point, and generally for the adjacent two pixel points, the determined average gray value is between The difference is small. Therefore, in the present specification, the image to be processed is divided into a plurality of regions, and for each region, the average gray value of the region is taken as the average gray value corresponding to each pixel in the region, so as to ensure the binary value. At the same time, the amount of calculation is reduced.

In one or more embodiments of the present specification, after the terminal determines the image to be processed, the size of the image to be processed may be determined first, and then the standard height and the standard width are further determined by the halving operation for the execution of the subsequent steps.

Specifically, to determine the standard height as an example, first, the terminal may determine the height of the image to be processed, and then perform an equal division calculation on the height of the image to be processed according to the preset value, determine the calculation result, and then, if the calculation result If it is an integer, the calculation result is taken as the standard height, and if the calculation result is not an integer, the calculation result is taken up to an integer, and the rounded result is taken as the standard height. Similarly, the terminal can determine the standard width through the same process.

The preset value can be set as needed, and the specification is not limited. For example, if you want to divide more areas, the value can be set larger. If the area of the area you want to divide is relatively larger, the value can be set smaller.

In the present specification, the calculation result after the operation of the width of the image to be processed is determined according to the formula windW=width/a, and the calculation result after the operation of the width of the image to be processed is determined according to the formula windH=height/a . Where width is the width of the image to be processed, height is the height of the image to be processed, and a is a preset value.

In addition, since the height and width of the image to be processed are integers, but they are not necessarily divisible by the preset value, the result of the aliquot calculation is either an integer or not an integer. The standard height and the standard width are determined for subsequent determination of the calculated average gray value range in the image to be processed, which needs to be an integer. Thus, when the result of the calculation is not an integer, the result of the calculation is taken up to an integer.

For example, taking the preset value equal to 8 as an example, assuming that the width of the image to be recognized is 80 pixels, and the height of the image to be recognized is 79 pixels, the terminal can determine the calculation after dividing the width according to the above formula. The result is 10, which can be determined as the standard width, and the settlement result of the equal division of the height is 9.875, so the upward rounding can be surely the standard height is 10.

S104: Determine the standard height and the standard width as the spacing, and determine a matrix consisting of several pile points in the image to be processed.

In the present specification, since the standard width and the standard height determined in the step S102 are determined by the division operation, it is determined in accordance with the standard width and the standard height, and a matrix composed of pile points is determined in the image to be processed. The matrix of the pile points can be evenly distributed in the image to be processed, so that when binarizing each pixel point, the binarization can be determined according to the average gray value corresponding to the pile point closest to the pixel point. As a result, the problem of excessive calculation is avoided.

Specifically, the terminal may first select any one of the pixels in the image to be processed as a starting point, and then based on the starting point, the standard width is the width spacing of each pile point, and the standard height is the height spacing of each pile point. , generating a matrix of pile points. The pile point matrix is uniformly covered in the image to be processed, as shown in FIG.

FIG. 4 is a schematic diagram of determining a pile point in an image to be processed provided by the present specification. Among them, it can be seen that the spacing of the pile points is a standard width and a standard height, and can be uniformly covered in the image to be processed.

In addition, in the present specification, the terminal may also use any one of the vertices of the image to be processed as the starting pile point, and then determine the pile point on the image to be processed at the standard height and the standard width. The matrix of the composition. For example, as shown in Figure 5.

It should be noted that, in step S102, for a calculation result that is not an integer, the terminal determines the standard height (or the standard width) by rounding up. Therefore, when the size of the image to be processed cannot be divisible, the determined The matrix may have the situation as shown in Figures 6a and 6b, i.e. there may be no pile points on the boundary of the image to be processed.

6a and 6b are schematic diagrams provided by the present specification, taking the width of an image to be processed as an example. The preset value used in calculating the standard width is 8, the width of the image to be processed in FIG. 6a is 79, and the width of the image to be processed in FIG. 6b is 81, and the determined standard widths are 10 and 11, respectively. Therefore, when the upper left vertex of the image to be processed is taken as the starting point, there is a case where the pile point fails to conform to the boundary.

S106: For each pile point, determine an average gray value of a region of a specified area around the pile point as a gray value corresponding to the pile point.

In the present specification, the terminal may calculate an average gray value corresponding to a region of a specified area around the pile point for each pile point in the pile point matrix determined in step S104, as the average gray value corresponding to the pile point. .

This step is similar to the method for determining the average gray value of the area around the pixel point in the prior art. Specifically, the terminal may be centered on the pile point for each pile point, and the standard height and the standard width are rectangular. The side length determines the area around the pile point, and then calculates the average value of the gray value of each pixel point included in the area around the pile point as the gray value corresponding to the pile point.

As shown in Fig. 7, Fig. 7 is a schematic diagram for calculating an average gray value corresponding to each pile point based on the pile point matrix shown in Fig. 5. The dotted line frame corresponds to the area around each pile point. When calculating the gray value corresponding to the pile point, the average value of the gray value of each pixel included in the dotted line frame of the pile point is calculated.

S108: determining, for each pixel in the image to be processed, a pile point closest to the pixel point, determining whether the gray value of the pixel point is smaller than a gray value corresponding to the determined pile point, and then performing the step S110, otherwise step S112 is performed.

In the present specification, after determining the average gray value corresponding to each pile point, the terminal can perform binarization processing on the image to be processed.

Specifically, the terminal may determine a pile point closest to the pixel point from each of the pile points for each pixel in the image to be processed, and then determine whether the gray value of the pixel point is smaller than the determined gray point corresponding to the pile point. The degree value, if yes, proceeds to step S110, otherwise to step S112.

In addition, since there are still a plurality of pile points closest to the distance from the pixel point, as shown in FIG. 8, therefore, in the present specification, for each pixel point, when determining the distance from the pixel point is the closest to the pile point At any time, select any one of the closest pile points and judge according to the gray value corresponding to the selected pile point.

In Fig. 8, if point A is the same distance from pile point 1 and pile point 2, then one of pile point 1 and pile point 2 can be selected, point B is from pile point 1, pile point 2 If the distance between the pile point 3 and the pile point 4 is the same, then any one of the pile points 1 to 4 can be selected.

S110: Adjust a gray value of the pixel to a first value;

S112: Adjust the gray value of the pixel to a second value.

In the present specification, when it is determined that the gray value of the pixel point is smaller than the determined gray value corresponding to the pile point, the gray value of the pixel point is adjusted to be the first value, and when the gray value of the pixel point is determined not to be smaller than the determination When the gray value corresponding to the pile point is obtained, the gray value of the pixel is adjusted to a second value. The first value and the second value may be set as needed. For example, when the color of the image is represented by 256 colors, the gray value is also 256 gray values, so the first value may be 0, and the second value may be Is 255.

Of course, the specific first value and the second value can be set as needed, for example, the first value is set to 10, the second value is set to 200, and the like.

Based on the image processing process shown in FIG. 2, the standard height and the standard width are determined by halving the image to be processed, and the standard width and the standard height are used as the pitch of the pile point, and the pile point is established on the image to be processed. Matrix, then calculate the gray value corresponding to each pile point (the average gray value of the area around the pile point), and then, when binarizing each pixel point, the gray corresponding to the pile point closest to the pixel point As the threshold value, the degree value is determined to adjust the gray value of the pixel point to the first value or the second value, and the binarization of the image to be processed is completed. In the method provided by the present specification, it is only necessary to calculate the average gray value of the area around the pile points without calculating the average gray value corresponding to each pixel point, thereby greatly reducing the calculation amount of the binarization and increasing the binary value. Efficiency.

It should be noted that the execution bodies of the steps of the method provided in the embodiments of the present specification may all be the same device, or the method may also be performed by different devices. For example, the execution body of step S100 and step S102 may be device 1, and the execution body of step S102 may be device 2; or the execution body of step S100 may be device 1, and the execution body of step S102 and step S104 may be device 2; and many more. The foregoing description of the specific embodiments of the specification has been described. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims can be performed in a different order than the embodiments and still achieve the desired results. In addition, the processes depicted in the figures are not necessarily in a particular order or in a sequential order to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

In addition, in the existing image binarization technique, when the two-dimensional code is included in the image to be processed, since the two-dimensional code is also an image composed of binarized dots, adjacent gray values may be identical. Pixels, where the calculated thresholds are different, occur. When the gray value of two pixels is close to the calculated threshold, the problem of poor binarization may occur.

Fig. 9 is a diagram showing a situation in which misjudgment occurs in binarization. Among them, it can be seen that the gray values of point A and point B are identical, but when the average gray value is calculated corresponding to the surrounding area of 3×3, the determined threshold values are different: 38 and 127, respectively, so the results after binarization are different. The two pixels of the same gray value are adjusted to white and adjusted to black, and the binarization effect is not good.

However, if the method provided in this manual is used, when the closest pile point between point A and point B is the same pile point, the binarization result is the same, either all is adjusted to white, or all is adjusted to black, which can be improved. The binarization effect on the two-dimensional code.

Based on the method of image processing shown in FIG. 2, the embodiment of the present specification further provides an apparatus for image processing, as shown in FIG.

FIG. 10 is a schematic structural diagram of an apparatus for image processing according to an embodiment of the present disclosure, where the apparatus includes:

Determining module 200, determining an image to be processed;

The halving module 202 determines the standard height and the standard width by halving according to the size of the image to be processed;

The pile point positioning module 204 determines a standard height and a standard width as a pitch, and determines a matrix composed of a plurality of pile points in the image to be processed;

The grayscale calculation module 206 determines, for each pile point, an average gray value of a region of a specified area around the pile point as a gray value corresponding to the pile point;

The determining adjustment module 208 is configured to determine, for each pixel point in the image to be processed, a pile point closest to the pixel point, and determine whether the gray value of the pixel point is smaller than a gray value corresponding to the determined pile point, and if Then, the gray value of the pixel is adjusted to be a first value, and if not, the gray value of the pixel is adjusted to a second value.

The halving module 202 determines the height and width of the image to be processed, and separately calculates the height and width of the image to be processed according to a preset value, and determines the standard height and the standard width according to the calculation result. .

The aliquoting module 202, when the calculation result of the aliquot calculation of the height of the image to be processed is not an integer, takes the calculation result up to an integer as the standard height, when the width of the image to be processed is performed, etc. When the calculation result of the sub-calculation is not an integer, the calculation result is taken up to the integer as the standard width.

The pile point positioning module 204 takes any vertex of the image to be processed as a starting pile point, determines a standard height and a standard width as a pitch, and determines that the pile to be processed is composed of a plurality of pile points. Matrix.

The gray scale calculation module 206 uses the standard height and the standard width as the side length, the pile point is a center point, determines an area around the pile point, and calculates each pixel point included in the area around the pile point. The average value of the gray value is used as the gray value corresponding to the pile point.

The gray value is a 256-level gray value, the first value is 0, and the second value is 255.

The determining adjustment module 208 selects any one of the pile points closest to the pixel point when there are a plurality of pile points closest to the pixel point.

Based on the method of image processing described in FIG. 2, the present specification correspondingly provides an apparatus for image processing, as shown in FIG. 11, wherein the apparatus includes: one or more processors and a memory, and the memory stores a program. And configured to perform the following steps by one or more processors:

Determining the image to be processed;

If yes, adjusting the gray value of the pixel to a first value;

If not, adjust the gray value of the pixel to a second value.

In the 1990s, improvements to a technology could clearly distinguish between hardware improvements (eg, improvements to circuit structures such as diodes, transistors, switches, etc.) or software improvements (for process flow improvements). However, as technology advances, many of today's method flow improvements can be seen as direct improvements in hardware circuit architecture. Designers almost always get the corresponding hardware circuit structure by programming the improved method flow into the hardware circuit. Therefore, it cannot be said that the improvement of a method flow cannot be implemented by hardware entity modules. For example, a Programmable Logic Device (PLD) (such as a Field Programmable Gate Array (FPGA)) is an integrated circuit whose logic function is determined by the user programming the device. Designers program themselves to "integrate" a digital system on a single PLD without having to ask the chip manufacturer to design and fabricate a dedicated integrated circuit chip. Moreover, today, instead of manually making integrated circuit chips, this programming is mostly implemented using "logic compiler" software, which is similar to the software compiler used in programming development, but before compiling The original code has to be written in a specific programming language. This is called the Hardware Description Language (HDL). HDL is not the only one, but there are many kinds, such as ABEL (Advanced Boolean Expression Language). AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, RHDL (Ruby Hardware Description Language), etc., are currently the most commonly used VHDL (Very-High-Speed Integrated Circuit Hardware Description Language) and Verilog. It should also be apparent to those skilled in the art that the hardware flow for implementing the logic method flow can be easily obtained by simply programming the method flow into the integrated circuit with a few hardware description languages.

The controller can be implemented in any suitable manner, for example, the controller can take the form of, for example, a microprocessor or processor and a computer readable medium storing computer readable program code (eg, software or firmware) executable by the (micro)processor. In the form of logic gates, switches, application specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers, examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, The Microchip PIC18F26K20 and the Silicone Labs C8051F320, the memory controller can also be implemented as part of the memory's control logic. Those skilled in the art will also appreciate that in addition to implementing the controller in purely computer readable program code, the controller can be logically programmed by means of logic gates, switches, ASICs, programmable logic controllers, and embedding. The form of a microcontroller or the like to achieve the same function. Such a controller can therefore be considered a hardware component, and the means for implementing various functions included therein can also be considered as a structure within the hardware component. Or even a device for implementing various functions can be considered as a software module that can be both a method of implementation and a structure within a hardware component.

The system, device, module or unit illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product having a certain function. A typical implementation device is a computer. Specifically, the computer can be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or A combination of any of these devices.

For the convenience of description, the above devices are described separately by function into various units. Of course, the functions of each unit may be implemented in the same software or software and/or hardware when implementing the present application.

Those skilled in the art will appreciate that embodiments of the present invention can be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or a combination of software and hardware. Moreover, the invention can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) including computer usable program code.

The present invention has been described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (system), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or FIG. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing device to produce a machine for the execution of instructions for execution by a processor of a computer or other programmable data processing device. Means for implementing the functions specified in one or more of the flow or in a block or blocks of the flow chart.

The computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture comprising the instruction device. The apparatus implements the functions specified in one or more blocks of a flow or a flow and/or block diagram of the flowchart.

These computer program instructions can also be loaded onto a computer or other programmable data processing device such that a series of operational steps are performed on a computer or other programmable device to produce computer-implemented processing for execution on a computer or other programmable device. The instructions provide steps for implementing the functions specified in one or more of the flow or in a block or blocks of a flow diagram.

In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include non-persistent memory, random access memory (RAM), and/or non-volatile memory in a computer readable medium, such as read only memory (ROM) or flash memory. Memory is an example of a computer readable medium.

Computer readable media includes both permanent and non-persistent, removable and non-removable media. Information storage can be implemented by any method or technology. The information can be computer readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read only memory. (ROM), electrically erasable programmable read only memory (EEPROM), flash memory or other memory technology, compact disk read only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, Magnetic tape cartridges, magnetic tape storage or other magnetic storage devices or any other non-transportable media can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary storage of computer readable media, such as modulated data signals and carrier waves.

It is also to be understood that the terms "comprises" or "comprising" or "comprising" or any other variations are intended to encompass a non-exclusive inclusion, such that a process, method, article, Other elements not explicitly listed, or elements that are inherent to such a process, method, commodity, or equipment. An element defined by the phrase "comprising a ..." does not exclude the presence of additional equivalent elements in the process, method, item, or device including the element.

Those skilled in the art will appreciate that embodiments of the present application can be provided as a method, system, or computer program product. Thus, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment in combination of software and hardware. Moreover, the application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) including computer usable program code.

The application can be described in the general context of computer-executable instructions executed by a computer, such as a program module. Generally, program modules include routines, programs, objects, components, data structures, and the like that perform particular tasks or implement particular abstract data types. The present application can also be practiced in distributed computing environments where tasks are performed by remote processing devices that are connected through a communication network. In a distributed computing environment, program modules can be located in both local and remote computer storage media including storage devices.

The various embodiments in the specification are described in a progressive manner, and the same or similar parts between the various embodiments may be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the description of the method embodiment.

The above description is only an embodiment of the present application and is not intended to limit the application. Various changes and modifications can be made to the present application by those skilled in the art. Any modifications, equivalents, improvements, etc. made within the spirit and scope of the present application are intended to be included within the scope of the appended claims.

Claims

A method of image processing, comprising:

Determining the image to be processed;

Determining a standard height and a standard width by halving according to the size of the image to be processed;

Determining a standard height and a standard width as a pitch, and determining a matrix consisting of a plurality of pile points in the image to be processed;

For each pile point, determining an average gray value of a region of a specified area around the pile point as a gray value corresponding to the pile point;

Determining, according to each pixel point in the image to be processed, a pile point closest to the pixel point, determining whether the gray value of the pixel point is smaller than a gray value corresponding to the determined pile point;

If yes, adjusting the gray value of the pixel to a first value;

If not, adjust the gray value of the pixel to a second value.
The method according to claim 1, wherein the standard height and the standard width are determined by an aliquot operation according to the size of the image to be processed, and specifically includes:

Determining a height and a width of the image to be processed;

According to the preset value, the height and the width of the image to be processed are respectively equally calculated, and the standard height and the standard width are respectively determined according to the calculation result.
The method according to claim 2, wherein the standard height and the standard width are respectively determined according to the calculation result, and specifically includes:

When the calculation result of the aliquot calculation of the height of the image to be processed is not an integer, the calculation result is taken up to an integer as the standard height;

When the calculation result of the aliquot calculation of the width of the image to be processed is not an integer, the calculation result is taken up to an integer as the standard width.
The method of claim 1, wherein the determined standard height and the standard width are spaces, and determining a matrix consisting of a plurality of pile points in the image to be processed includes:

Taking any vertex of the image to be processed as a starting pile point, determining a standard height and a standard width as a pitch, and determining a matrix composed of a plurality of pile points in the image to be processed.
The method of claim 1, determining an average gray value of the area of the designated area around the pile point, as the gray value corresponding to the pile point, specifically comprising:

The standard height and the standard width are side lengths, and the pile point is a center point, and an area around the pile point is determined;

The average value of the gradation values of the respective pixel points included in the area around the pile point is calculated as the gradation value corresponding to the pile point.
The method of claim 1 wherein said gray value is a 256 level gray value, said first value being zero and said second value being 255.
The method of claim 1, determining a pile point closest to the pixel point, specifically comprising:

When there are multiple pile points closest to the pixel point, select any one of the pile points closest to the pixel point.
An image processing apparatus comprising:

Determining a module to determine an image to be processed;

An aliquoting module determines the standard height and the standard width by halving according to the size of the image to be processed;

a pile positioning module to determine a standard height and a standard width as a spacing, and determine a matrix consisting of a plurality of pile points in the image to be processed;

a gray scale calculation module, for each pile point, determining an average gray value of a region of a specified area around the pile point as a gray value corresponding to the pile point;

The determining adjustment module determines, for each pixel point in the image to be processed, a pile point closest to the pixel point, and determines whether the gray value of the pixel point is smaller than a gray value corresponding to the determined pile point, and if so, Then, the gray value of the pixel is adjusted to be a first value, and if not, the gray value of the pixel is adjusted to a second value.
The apparatus according to claim 8, wherein the halving module determines a height and a width of the image to be processed, and separately calculates an altitude of the image to be processed according to a preset value, according to the calculation The results determine the standard height and the standard width, respectively.
The apparatus according to claim 9, wherein the halving module, when the calculation result of the aliquot calculation of the height of the image to be processed is not an integer, takes the calculation result up to an integer as the standard height, when When the calculation result of the width of the image to be processed is not an integer, the calculation result is taken up as an integer.
The apparatus according to claim 8, wherein the pile positioning module uses any vertex of the image to be processed as a starting pile point to determine a standard height and a standard width as a pitch, in the to-be-processed A matrix consisting of several pile points is determined in the image.
The apparatus according to claim 8, wherein the gradation calculation module defines the area around the pile point by using the standard height and the standard width as a side length, and calculating the area around the pile point. The average value of the gray value of each pixel included in the area is used as the gray value corresponding to the pile point.
The apparatus of claim 8, said gray value being a 256-level gray value, said first value being 0, and said second value being 255.
The apparatus according to claim 8, wherein the judgment adjustment module selects any one of the pile points closest to the pixel point when there are a plurality of pile points closest to the pixel point.
An apparatus for image processing, wherein the apparatus comprises: one or more processors and a memory, the memory storing a program, and being configured to perform the following steps by one or more processors:

Determining the image to be processed;

Determining a standard height and a standard width by halving according to the size of the image to be processed;

Determining a standard height and a standard width as a pitch, and determining a matrix consisting of a plurality of pile points in the image to be processed;

For each pile point, determining an average gray value of a region of a specified area around the pile point as a gray value corresponding to the pile point;

Determining, according to each pixel point in the image to be processed, a pile point closest to the pixel point, determining whether the gray value of the pixel point is smaller than a gray value corresponding to the determined pile point;

If yes, adjusting the gray value of the pixel to a first value;

If not, adjust the gray value of the pixel to a second value.