CN112085030A - Similar image determining method and device - Google Patents
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- 238000000034 method Methods 0.000 title claims abstract description 40
- 238000012545 processing Methods 0.000 claims abstract description 14
- 238000010606 normalization Methods 0.000 claims description 4
- 238000010586 diagram Methods 0.000 description 7
- 238000004891 communication Methods 0.000 description 6
- 230000006870 function Effects 0.000 description 5
- 238000004590 computer program Methods 0.000 description 4
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
- G06V10/26—Segmentation of patterns in the image field; Cutting or merging of image elements to establish the pattern region, e.g. clustering-based techniques; Detection of occlusion
- G06V10/267—Segmentation of patterns in the image field; Cutting or merging of image elements to establish the pattern region, e.g. clustering-based techniques; Detection of occlusion by performing operations on regions, e.g. growing, shrinking or watersheds
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/22—Matching criteria, e.g. proximity measures
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/56—Extraction of image or video features relating to colour
Abstract
The application relates to the technical field of computers, and discloses a method for determining similar images, which comprises the following steps: acquiring an image to be detected; performing pixelization processing on the images to be detected to obtain pixel blocks corresponding to the images to be detected; acquiring image characteristic coordinates according to the pixel blocks; and determining a similar image from the image to be detected according to the image characteristic coordinates. Performing pixelization processing on the images to be detected to obtain pixel blocks corresponding to the images to be detected; and then, obtaining image characteristic coordinates according to the pixel blocks, and finally determining a similar image from the image to be detected according to the image characteristic coordinates, wherein the efficiency is higher compared with the mode of manually determining the similar image. The application also discloses a similar image determining device.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to a method and an apparatus for determining a similar image.
Background
At present, whether the images are similar or not is generally judged by considering of a user, the method is accurate, but the efficiency is very low, and under the condition that the number of the images is large, the similar images are difficult to determine by a manual identification method.
Disclosure of Invention
The following presents a simplified summary in order to provide a basic understanding of some aspects of the disclosed embodiments. This summary is not an extensive overview nor is intended to identify key/critical elements or to delineate the scope of such embodiments but rather as a prelude to the more detailed description that is presented later.
The embodiment of the disclosure provides a method and a device for determining similar images, so as to solve the technical problem of low efficiency of manually identifying similar images in the prior art.
In some embodiments, the method comprises:
acquiring an image to be detected;
performing pixelization processing on the images to be detected to obtain pixel blocks corresponding to the images to be detected;
acquiring image characteristic coordinates according to the pixel blocks;
and determining a similar image from the image to be detected according to the image characteristic coordinates.
In some embodiments, the apparatus comprises: a processor and a memory storing program instructions, the processor being configured to, when executing the program instructions, perform the similar image determining method described above.
The method and the device for determining the similar image provided by the embodiment of the disclosure can achieve the following technical effects: performing pixelization processing on the images to be detected to obtain pixel blocks corresponding to the images to be detected; and then, obtaining image characteristic coordinates according to the pixel blocks, and finally determining a similar image from the image to be detected according to the image characteristic coordinates, wherein the efficiency is higher compared with the mode of manually determining the similar image.
The foregoing general description and the following description are exemplary and explanatory only and are not restrictive of the application.
Drawings
One or more embodiments are illustrated by way of example in the accompanying drawings, which correspond to the accompanying drawings and not in limitation thereof, in which elements having the same reference numeral designations are shown as like elements and not in limitation thereof, and wherein:
fig. 1 is a schematic diagram of a similar image determination method provided in an embodiment of the present disclosure;
fig. 2 is a schematic diagram of a similar image determining apparatus according to an embodiment of the present disclosure.
Detailed Description
So that the manner in which the features and elements of the disclosed embodiments can be understood in detail, a more particular description of the disclosed embodiments, briefly summarized above, may be had by reference to the embodiments, some of which are illustrated in the appended drawings. In the following description of the technology, for purposes of explanation, numerous details are set forth in order to provide a thorough understanding of the disclosed embodiments. However, one or more embodiments may be practiced without these details. In other instances, well-known structures and devices may be shown in simplified form in order to simplify the drawing.
The terms "first," "second," and the like in the description and in the claims, and the above-described drawings of embodiments of the present disclosure, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It should be understood that the data so used may be interchanged under appropriate circumstances such that embodiments of the present disclosure described herein may be made. Furthermore, the terms "comprising" and "having," as well as any variations thereof, are intended to cover non-exclusive inclusions.
The term "plurality" means two or more unless otherwise specified.
In the embodiment of the present disclosure, the character "/" indicates that the preceding and following objects are in an or relationship. For example, A/B represents: a or B.
The term "and/or" is an associative relationship that describes objects, meaning that three relationships may exist. For example, a and/or B, represents: a or B, or A and B.
With reference to fig. 1, an embodiment of the present disclosure provides a method for determining a similar image, including:
s101, acquiring N images to be detected, wherein N is a positive integer greater than 1;
s102, performing pixelization processing on the image to be detected to obtain pixel blocks corresponding to the image to be detected;
s103, acquiring image characteristic coordinates according to the pixel blocks;
and S104, determining a similar image from the image to be detected according to the image characteristic coordinates.
By adopting the method for classifying the system application program provided by the embodiment of the disclosure, the pixel blocks corresponding to the images to be detected are obtained by performing the pixelation processing on the images to be detected; and then, obtaining image characteristic coordinates according to the pixel blocks, and finally determining a similar image from the image to be detected according to the image characteristic coordinates, wherein the efficiency is higher compared with the mode of manually determining the similar image.
Optionally, the pixelation processing is performed on the image to be detected, and includes:
dividing an image to be detected according to m rows and n columns to obtain m multiplied by n pixel blocks, wherein m and n are positive integers;
and obtaining the decimal color code of each pixel point in each pixel block, and taking the most decimal color codes in each pixel block as the decimal color codes of the pixel block.
Optionally, acquiring the image feature coordinates according to the pixel blocks includes:
acquiring a color gear value corresponding to each pixel block according to the decimal color code of each pixel block;
acquiring a color position characteristic value according to the color gear value corresponding to each pixel block and the position of each pixel block;
obtaining a color characteristic value from the decimal color code corresponding to each pixel block;
and obtaining image characteristic coordinates according to the color position characteristic value and the color characteristic value.
Optionally, obtaining the color gear value corresponding to each pixel block according to the decimal color code of each pixel block includes:
and determining a corresponding color code range in a preset database according to the decimal color code of each pixel block, and matching a color gear value corresponding to the color code range in the preset database.
Optionally, obtaining the color position feature value according to the color gear value corresponding to each pixel block and the position of each pixel block includes:
computing
Obtaining the position WZ of the pixel block of the mth row and the nth columnm,n；
Calculating YWm,n＝YDZm,n×WZm,nObtaining the color position characteristic value YW of the pixel block of the mth row and the nth columnm,n，YDZm,nThe color gear value corresponding to the pixel block of the mth row and the nth column.
Optionally, obtaining the color feature value from the decimal color code corresponding to each pixel block includes:
computing
Obtaining a color characteristic value YST 'of the pixel block of the m line and the n column'm,n；
YSTm,nDecimal color code, YST, for pixel block in mth row and nth columnminFor the smallest decimal color code, YST, in each pixel blockmaxThe largest decimal color code in each pixel block.
Optionally, obtaining the image feature coordinates according to the color location feature value and the color feature value includes:
taking the color position characteristic value as an abscissa value and the color characteristic value as an ordinate value, thereby obtaining an image characteristic coordinate; or the like, or, alternatively,
taking the color characteristic value as an abscissa value and the color position characteristic value as an ordinate value, thereby obtaining an image characteristic coordinate; or the like, or, alternatively,
normalizing the color position characteristic value to be used as an abscissa value and the color characteristic value to be used as an ordinate value so as to obtain an image characteristic coordinate; or the like, or, alternatively,
and taking the color characteristic value as an abscissa value, and taking the color position characteristic value as an ordinate value after normalization processing, thereby obtaining an image characteristic coordinate.
Optionally, the normalizing the color location feature value includes:
computing
Obtaining blocks of pixels of the m-th row and the n-th columnValue YW 'after color position characteristic value normalization processing'm,n；
YWm,nIs the color position characteristic value, YW, of the pixel block of the m-th row and n-th columnminFor the smallest color location feature value, YW, in each pixel blockmaxThe largest color location feature value in each pixel block.
Optionally, determining a similar image from the image to be detected according to the image feature coordinates includes:
selecting two images from the images to be detected to obtain the similarity of the two images, and determining the two images with the similarity meeting the set conditions as similar images until the two images to be detected are completely compared in pairs; optionally, the image with the largest similarity is determined to be a similar image of the preferred image.
Setting two images selected each time as a first image to be detected and a second image to be detected respectively; calculating the similarity between each corresponding pixel block in the first image to be detected and the second image to be detected, and summing the similarities between all the corresponding pixel blocks to obtain the similarity between the first image to be detected and the second image to be detected; computing
Obtaining the similarity between the pixel blocks of the p-th line and the q-th line in the first image to be detected and the pixel blocks of the i-th line and the j-th line in the second image to be detected; YST'p,qIs a color characteristic value, YW ', of a pixel block of a line q-th column of a p-th line in a first image to be detected'p,qThe characteristic value of the color position of the pixel block of the p row and the q column in the first image to be detected is obtained; YST'i,jIs the color characteristic value YW 'of the pixel block of the ith line and the jth column in the second image to be detected'i,jAnd the color position characteristic values of pixel blocks in the ith row and the jth column in the second image to be detected are p, q, i and j which are positive integers, p belongs to m, i belongs to m, q belongs to n, j belongs to n, i is equal to p, and j is equal to q.
As shown in fig. 2, an embodiment of the present disclosure provides a similar image determining apparatus, which includes a processor (processor)100 and a memory (memory) 101. Optionally, the apparatus may also include a Communication Interface (Communication Interface)102 and a bus 103. The processor 100, the communication interface 102, and the memory 101 may communicate with each other via a bus 103. The communication interface 102 may be used for information transfer. The processor 100 may call logic instructions in the memory 101 to perform the similar image determination method of the above-described embodiment.
In addition, the logic instructions in the memory 101 may be implemented in the form of software functional units and stored in a computer readable storage medium when the logic instructions are sold or used as independent products.
The memory 101, which is a computer-readable storage medium, may be used for storing software programs, computer-executable programs, such as program instructions/modules corresponding to the methods in the embodiments of the present disclosure. The processor 100 executes functional applications and data processing, i.e., implements the similar image determination method in the above-described embodiments, by executing program instructions/modules stored in the memory 101.
The memory 101 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the terminal device, and the like. In addition, the memory 101 may include a high-speed random access memory, and may also include a nonvolatile memory.
The embodiment of the disclosure provides a computer or a server, which comprises the similar image determination device.
The disclosed embodiments provide a computer-readable storage medium storing computer-executable instructions configured to perform the above-described similar image determination method.
An embodiment of the present disclosure provides a computer program product comprising a computer program stored on a computer-readable storage medium, the computer program comprising program instructions that, when executed by a computer, cause the computer to perform the above-described similar image determination method.
The computer-readable storage medium described above may be a transitory computer-readable storage medium or a non-transitory computer-readable storage medium.
The technical solution of the embodiments of the present disclosure may be embodied in the form of a software product, where the computer software product is stored in a storage medium and includes one or more instructions to enable a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method of the embodiments of the present disclosure. And the aforementioned storage medium may be a non-transitory storage medium comprising: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes, and may also be a transient storage medium.
The above description and drawings sufficiently illustrate embodiments of the disclosure to enable those skilled in the art to practice them. Other embodiments may incorporate structural, logical, electrical, process, and other changes. The examples merely typify possible variations. Individual components and functions are optional unless explicitly required, and the sequence of operations may vary. Portions and features of some embodiments may be included in or substituted for those of others. Furthermore, the words used in the specification are words of description only and are not intended to limit the claims. As used in the description of the embodiments and the claims, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. Similarly, the term "and/or" as used in this application is meant to encompass any and all possible combinations of one or more of the associated listed. Furthermore, the terms "comprises" and/or "comprising," when used in this application, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. Without further limitation, an element defined by the phrase "comprising an …" does not exclude the presence of other like elements in a process, method or apparatus that comprises the element. In this document, each embodiment may be described with emphasis on differences from other embodiments, and the same and similar parts between the respective embodiments may be referred to each other. For methods, products, etc. of the embodiment disclosures, reference may be made to the description of the method section for relevance if it corresponds to the method section of the embodiment disclosure.
Those of skill in the art would appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software may depend upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the disclosed embodiments. It can be clearly understood by the skilled person that, for convenience and brevity of description, the specific working processes of the system, the apparatus and the unit described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the embodiments disclosed herein, the disclosed methods, products (including but not limited to devices, apparatuses, etc.) may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units may be merely a logical division, and in actual implementation, there may be another division, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form. The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to implement the present embodiment. In addition, functional units in the embodiments of the present disclosure may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. In the description corresponding to the flowcharts and block diagrams in the figures, operations or steps corresponding to different blocks may also occur in different orders than disclosed in the description, and sometimes there is no specific order between the different operations or steps. For example, two sequential operations or steps may in fact be executed substantially concurrently, or they may sometimes be executed in the reverse order, depending upon the functionality involved. Each block of the block diagrams and/or flowchart illustrations, and combinations of blocks in the block diagrams and/or flowchart illustrations, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
Claims (10)
1. A method for determining a similar image, comprising:
acquiring an image to be detected;
performing pixelization processing on the images to be detected to obtain pixel blocks corresponding to the images to be detected;
acquiring image characteristic coordinates according to the pixel blocks;
and determining a similar image from the image to be detected according to the image characteristic coordinates.
2. The method according to claim 1, wherein pixelating the image to be detected comprises:
dividing the image to be detected according to m rows and n columns to obtain m multiplied by n pixel blocks, wherein m and n are positive integers;
and obtaining the decimal color code of each pixel point in each pixel block, and taking the most decimal color codes in each pixel block as the decimal color codes of the pixel block.
3. The method of claim 2, wherein obtaining image feature coordinates from the block of pixels comprises:
acquiring a color gear value corresponding to each pixel block according to the decimal color code of each pixel block;
acquiring a color position characteristic value according to the color gear value corresponding to each pixel block and the position of each pixel block;
obtaining a color characteristic value from the decimal color code corresponding to each pixel block;
and obtaining the image characteristic coordinate according to the color position characteristic value and the color characteristic value.
4. The method of claim 3, wherein obtaining a color gear value for each of the pixel blocks based on the decimal color code for each of the pixel blocks comprises:
and determining a corresponding color code range in a preset database according to the decimal color code of each pixel block, and matching a color gear value corresponding to the color code range in the preset database.
5. The method of claim 4, wherein obtaining a color position feature value based on the color gear value corresponding to each of the pixel blocks and the position of each of the pixel blocks comprises:
computing
Obtaining the position WZ of the pixel block of the mth row and the nth columnm,n；
Calculating YWm,n＝YDZm,n×WZm,nObtaining the color position characteristic value YW of the pixel block of the mth row and the nth columnm,nSaid YDZm,nThe color gear value corresponding to the pixel block of the mth row and the nth column.
6. The method of claim 5, wherein obtaining the color feature value from the decimal color code corresponding to each of the pixel blocks comprises:
computing
Obtaining a color characteristic value YST 'of the pixel block of the m line and the n column'm,n；
The YSTm,nDecimal color code, YST, for pixel block in mth row and nth columnminFor the smallest decimal color code, YST, in each pixel blockmaxThe largest decimal color code in each pixel block.
7. The method of claim 6, wherein obtaining the image feature coordinates from the color location feature values and color feature values comprises:
taking the color position characteristic value as an abscissa value and the color characteristic value as an ordinate value, thereby obtaining the image characteristic coordinate; or the like, or, alternatively,
taking the color characteristic value as an abscissa value and the color position characteristic value as an ordinate value, thereby obtaining the image characteristic coordinate; or the like, or, alternatively,
normalizing the color position characteristic value to be used as an abscissa value and the color characteristic value to be used as an ordinate value so as to obtain the image characteristic coordinate; or the like, or, alternatively,
and taking the color characteristic value as an abscissa value, and taking the color position characteristic value as an ordinate value after normalization processing, thereby obtaining the image characteristic coordinate.
8. The method of claim 7, wherein normalizing the color location feature values comprises:
computing
Obtaining a value YW 'after normalization processing of the color position characteristic value of the pixel block of the mth line and the nth line'm,n；
Said YWm,nIs the color position characteristic value, YW, of the pixel block of the m-th row and n-th columnminFor the smallest color location feature value, YW, in each pixel blockmaxThe largest color location feature value in each pixel block.
9. The method according to claim 8, wherein determining similar images from the images to be detected according to the image feature coordinates comprises:
selecting two images from the images to be detected to obtain the similarity of the two images until the two images to be detected are compared in pairs, and determining the two images with the similarity meeting set conditions as similar images;
setting two images selected each time as a first image to be detected and a second image to be detected respectively; calculating the similarity between each corresponding pixel block in the first image to be detected and the second image to be detected, and summing the similarities between all the corresponding pixel blocks to obtain the similarity between the first image to be detected and the second image to be detected;
computing
Obtaining the similarity between the pixel blocks of the p-th line and the q-th line in the first image to be detected and the pixel blocks of the ith line and the jth line in the second image to be detected; YST'p,qIs the image of the p row and the q column in the first image to be detectedColor feature value of plain Block, YW'p,qThe characteristic value of the color position of the pixel block of the qth line and the qth column in the first image to be detected is obtained; YST'i,jIs the color characteristic value YW 'of the pixel block of the ith line and the jth column in the second image to be detected'i,jAnd setting the color position characteristic values of pixel blocks in the ith row and the jth column in the second image to be detected as p, q, i and j which are positive integers, wherein p belongs to m, i belongs to m, q belongs to n, j belongs to n, i is equal to p, and j is equal to q.
10. A similar image determining apparatus comprising a processor and a memory storing program instructions, wherein the processor is configured to perform the similar image determining method according to any one of claims 1 to 9 when executing the program instructions.
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