CN112669290A - Image comparison method and device - Google Patents
Image comparison method and device Download PDFInfo
- Publication number
- CN112669290A CN112669290A CN202011617307.8A CN202011617307A CN112669290A CN 112669290 A CN112669290 A CN 112669290A CN 202011617307 A CN202011617307 A CN 202011617307A CN 112669290 A CN112669290 A CN 112669290A
- Authority
- CN
- China
- Prior art keywords
- image
- detected
- pixel points
- pixel
- error
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
Abstract
The invention discloses an image comparison method, medium, equipment and device, wherein the method comprises the following steps: acquiring an image to be detected and a standard image, wherein pixel points in the image to be detected and pixel points in the standard image are in one-to-one correspondence relationship; calculating a pixel difference value between a pixel point in the image to be detected and a pixel point in the corresponding standard image, judging whether the pixel difference value is larger than a preset difference value threshold value, and taking the pixel point in the image to be detected as an error pixel point when the judgment result is yes; and counting the number of the error pixel points, and judging whether the image to be detected meets the visual requirement or not according to the number of the error pixel points. The method can make the image comparison result more accord with the visual verification requirement from the visual verification angle.
Description
Technical Field
The present invention relates to the field of image processing technologies, and in particular, to an image comparison method, a computer-readable storage medium, a computer device, and an image comparison apparatus.
Background
In the related technology, when two images are compared, a characteristic quantity comparison mode is mostly adopted, and whether the two images are consistent or not is judged through the comparison of the characteristic quantities; however, the similarity between the two images is determined only by the feature quantity, and the result obtained by this method is often inaccurate in the process of visual verification (that is, the feature quantity determination result is consistent, but the difference between the two images can be clearly observed by naked eyes).
Disclosure of Invention
The present invention is directed to solving, at least to some extent, one of the technical problems in the art described above. Therefore, an object of the present invention is to provide an image comparison method, which can make an image comparison result better meet a visual verification requirement from the perspective of visual verification.
A second object of the invention is to propose a computer-readable storage medium.
A third object of the invention is to propose a computer device.
The fourth objective of the present invention is to provide an image matching apparatus.
In order to achieve the above object, an embodiment of a first aspect of the present invention provides an image comparison method, including the following steps: acquiring an image to be detected and a standard image, wherein pixel points in the image to be detected and pixel points in the standard image are in one-to-one correspondence relationship; calculating a pixel difference value between a pixel point in the image to be detected and a pixel point in the corresponding standard image, judging whether the pixel difference value is larger than a preset difference value threshold value, and taking the pixel point in the image to be detected as an error pixel point when the judgment result is yes; and counting the number of the error pixel points, and judging whether the image to be detected meets the visual requirement or not according to the number of the error pixel points.
According to the image comparison method provided by the embodiment of the invention, firstly, an image to be detected and a standard image are obtained, wherein pixel points in the image to be detected and pixel points in the standard image are in one-to-one correspondence relationship; then, calculating a pixel difference value between a pixel point in the image to be detected and a pixel point in the corresponding standard image, judging whether the pixel difference value is larger than a preset difference value threshold value, and taking the pixel point in the image to be detected as an error pixel point when the judgment result is yes; then, counting the number of the error pixel points, and judging whether the image to be detected meets the visual requirement or not according to the number of the error pixel points; therefore, the vision verification is realized, and the image comparison result is more in line with the vision verification requirement.
In addition, the image comparison method proposed by the above embodiment of the present invention may further have the following additional technical features:
optionally, judging whether the image to be detected meets the visual requirement according to the number of the error pixel points includes: calculating the ratio of the number of the error pixel points to the total number of the pixel points of the image to be detected, and judging whether the ratio is greater than a preset ratio threshold value or not; and if not, determining that the image to be detected meets the visual requirement.
Optionally, judging whether the image to be detected meets the visual requirement according to the number of the error pixel points includes: judging whether the number of the error pixel points is larger than a preset error number threshold value or not; if yes, calculating an average pixel difference value according to pixel difference values between all error pixel points and pixel points in the corresponding standard image; judging whether the average pixel difference value is larger than a preset error mean value threshold value or not; and if not, determining that the image to be detected meets the visual requirement.
In order to achieve the above object, a second aspect of the present invention provides a computer-readable storage medium, on which an image comparison program is stored, and the image comparison program, when executed by a processor, implements the image comparison method as described above.
According to the computer-readable storage medium of the embodiment of the invention, the image comparison program is stored, so that the processor realizes the image comparison method when executing the image comparison program; therefore, the vision verification is realized, and the image comparison result is more in line with the vision verification requirement.
In order to achieve the above object, a third embodiment of the present invention provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the image matching method as described above when executing the program.
According to the computer device of the embodiment of the invention, the image comparison program is stored through the memory, so that the processor can realize the image comparison method when executing the image comparison program; therefore, the vision verification is realized, and the image comparison result is more in line with the vision verification requirement.
In order to achieve the above object, a fourth aspect of the present invention provides an image matching apparatus, including: the device comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring an image to be detected and a standard image, and pixel points in the image to be detected and pixel points in the standard image are in one-to-one correspondence; the calculation module is used for calculating a pixel difference value between a pixel point in the image to be detected and a pixel point in the corresponding standard image, judging whether the pixel difference value is larger than a preset difference threshold value or not, and taking the pixel point in the image to be detected as an error pixel point if the judgment result is yes; the statistical module is used for counting the number of the error pixel points; and the judging module is used for judging whether the image to be detected meets the visual requirement or not according to the number of the error pixel points.
According to the image comparison device provided by the embodiment of the invention, the acquisition module is arranged for acquiring the image to be detected and the standard image, wherein the pixel points in the image to be detected and the pixel points in the standard image are in one-to-one correspondence; the calculation module is used for calculating a pixel difference value between a pixel point in the image to be detected and a pixel point in the corresponding standard image, judging whether the pixel difference value is larger than a preset difference value threshold value or not, and taking the pixel point in the image to be detected as an error pixel point when the judgment result is yes; the statistical module is used for counting the number of the error pixel points; the judging module is used for judging whether the image to be detected meets the visual requirement or not according to the number of the error pixel points; therefore, the vision verification is realized, and the image comparison result is more in line with the vision verification requirement.
In addition, the image matching apparatus proposed by the above embodiment of the present invention may further have the following additional technical features:
optionally, judging whether the image to be detected meets the visual requirement according to the number of the error pixel points includes: calculating the ratio of the number of the error pixel points to the total number of the pixel points of the image to be detected, and judging whether the ratio is greater than a preset ratio threshold value or not; and if not, determining that the image to be detected meets the visual requirement.
Optionally, judging whether the image to be detected meets the visual requirement according to the number of the error pixel points includes: judging whether the number of the error pixel points is larger than a preset error number threshold value or not; if yes, calculating an average pixel difference value according to pixel difference values between all error pixel points and pixel points in the corresponding standard image; judging whether the average pixel difference value is larger than a preset error mean value threshold value or not; and if not, determining that the image to be detected meets the visual requirement.
Drawings
FIG. 1 is a flowchart illustrating an image matching method according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating an image matching method according to another embodiment of the present invention;
fig. 3 is a block diagram of an image comparison apparatus according to an embodiment of the invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are illustrative and intended to be illustrative of the invention and are not to be construed as limiting the invention.
In the related technology, when images are compared, a characteristic quantity measurement mode is adopted, and the result is often not in accordance with the requirement of visual verification; according to the image comparison method provided by the embodiment of the invention, firstly, an image to be detected and a standard image are obtained, wherein pixel points in the image to be detected and pixel points in the standard image are in one-to-one correspondence relationship; then, calculating a pixel difference value between a pixel point in the image to be detected and a pixel point in the corresponding standard image, judging whether the pixel difference value is larger than a preset difference value threshold value, and taking the pixel point in the image to be detected as an error pixel point when the judgment result is yes; then, counting the number of the error pixel points, and judging whether the image to be detected meets the visual requirement or not according to the number of the error pixel points; therefore, the vision verification is realized, and the image comparison result is more in line with the vision verification requirement.
In order to better understand the above technical solutions, exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention can be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
In order to better understand the technical solution, the technical solution will be described in detail with reference to the drawings and the specific embodiments.
Fig. 1 is a schematic flowchart of an image comparison method according to an embodiment of the present invention, as shown in fig. 1, the image comparison method includes the following steps:
s101, acquiring an image to be detected and a standard image, wherein pixel points in the image to be detected and pixel points in the standard image are in one-to-one correspondence relationship.
That is, the image to be measured and the corresponding standard image are obtained, and the image to be measured and the corresponding standard image have the same specification; according to the coordinates of the pixel points in the image to be detected and the coordinates of the pixel points in the standard image; and each pixel point in any image to be detected has a corresponding pixel point in the standard image.
S102, calculating a pixel difference value between a pixel point in the image to be detected and a pixel point in the corresponding standard image, judging whether the pixel difference value is larger than a preset difference value threshold value, and taking the pixel point in the image to be detected as an error pixel point when the judgment result is yes.
That is, the pixel difference between the pixel of the pixel point in the image to be measured and the pixel of the pixel point in the corresponding standard image is calculated; and then, judging whether the pixel difference value is larger than a preset difference value threshold value or not so as to judge whether a pixel point in the image to be detected is an error pixel point or not.
S103, counting the number of the error pixel points, and judging whether the image to be detected meets the visual requirement or not according to the number of the error pixel points.
In some embodiments, determining whether the image to be measured meets the visual requirement according to the number of the error pixel points includes:
calculating the ratio of the number of error pixel points to the total number of pixel points of the image to be detected, and judging whether the ratio is greater than a preset ratio threshold value or not;
and if not, determining that the image to be detected meets the visual requirement.
That is, whether the image to be detected meets the visual requirement is judged according to the proportion of the error pixel points in the image to be detected; for example, if the number of error pixel points is 50 and the total number of pixel points of the image to be detected is 500, the ratio between the error pixel points and the pixel points is 1; 10; and if the preset ratio threshold value is 1:5, the image to be detected meets the visual requirement.
In some embodiments, determining whether the image to be measured meets the visual requirement according to the number of the error pixel points includes:
judging whether the number of the error pixel points is larger than a preset error number threshold value or not;
if yes, calculating an average pixel difference value according to pixel difference values between all error pixel points and pixel points in the corresponding standard image;
judging whether the average pixel difference value is larger than a preset error mean value threshold value or not;
and if not, determining that the image to be detected meets the visual requirement.
As an example, assuming that the number of error pixel points is 50, the preset error number threshold is 30; the number of the error pixel points is larger than a preset error number threshold value; further, obtaining a pixel difference value between the pixel value of each error pixel point in the 50 error pixel points and the pixel value of the pixel point in the corresponding standard image; then, an average pixel difference value of the 50 pixel difference values is calculated; then, judging whether the average pixel difference value is larger than a preset error mean value threshold value or not; if so, the image to be detected is considered to be not in accordance with the visual requirement; and if not, determining that the image to be detected meets the visual requirement.
In an embodiment of the present invention, as shown in fig. 2, the image matching method includes the following steps:
s201, acquiring an image to be detected and a standard image.
S202, calculating a pixel difference value between a pixel point in the image to be detected and a pixel point in the corresponding standard image.
S203, judging whether the pixel difference value is larger than a preset difference value threshold value; if so, step S204 is performed.
And S204, taking the pixel points in the image to be detected as error pixel points.
And S205, counting the number of error pixel points.
And S206, calculating the ratio of the number of the error pixel points to the total number of the pixel points of the image to be detected.
S207, judging whether the ratio is larger than a preset ratio threshold value or not; if yes, go to step S208; if not, step S209 is performed.
And S208, considering that the image to be detected does not meet the visual requirement.
S209, judging whether the number of the error pixel points is larger than a preset error number threshold value or not; if yes, go to step S210; if not, step S211 is performed.
And S210, calculating an average pixel difference value according to pixel difference values between all error pixel points and pixel points in the corresponding standard image.
And S211, determining that the image to be detected meets the visual requirement.
S212, judging whether the average pixel difference value is larger than a preset error mean value threshold value or not; if yes, go to step S208; if not, step S211 is performed.
In summary, according to the image comparison method of the embodiment of the present invention, first, an image to be detected and a standard image are obtained, where a pixel point in the image to be detected and a pixel point in the standard image are in a one-to-one correspondence relationship; then, calculating a pixel difference value between a pixel point in the image to be detected and a pixel point in the corresponding standard image, judging whether the pixel difference value is larger than a preset difference value threshold value, and taking the pixel point in the image to be detected as an error pixel point when the judgment result is yes; then, counting the number of the error pixel points, and judging whether the image to be detected meets the visual requirement or not according to the number of the error pixel points; therefore, the vision verification is realized, and the image comparison result is more in line with the vision verification requirement.
In order to implement the above embodiments, an embodiment of the present invention provides a computer-readable storage medium, on which an image comparison program is stored, and the image comparison program, when executed by a processor, implements the image comparison method as described above.
According to the computer-readable storage medium of the embodiment of the invention, the image comparison program is stored, so that the processor realizes the image comparison method when executing the image comparison program; therefore, the vision verification is realized, and the image comparison result is more in line with the vision verification requirement.
In order to implement the foregoing embodiments, an embodiment of the present invention provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor executes the computer program to implement the image matching method as described above.
According to the computer device of the embodiment of the invention, the image comparison program is stored through the memory, so that the processor can realize the image comparison method when executing the image comparison program; therefore, the vision verification is realized, and the image comparison result is more in line with the vision verification requirement.
In order to implement the above embodiments, an embodiment of the present invention provides an image matching apparatus, as shown in fig. 3, the image matching apparatus includes: the device comprises an acquisition module 10, a calculation module 20, a statistic module 30 and a judgment module 40.
The acquiring module 10 is configured to acquire an image to be detected and a standard image, where pixel points in the image to be detected and pixel points in the standard image are in a one-to-one correspondence relationship;
the calculating module 20 is configured to calculate a pixel difference between a pixel point in the image to be detected and a pixel point in the standard image corresponding to the pixel point, determine whether the pixel difference is greater than a preset difference threshold, and if so, take the pixel point in the image to be detected as an error pixel point;
the statistical module 30 is used for counting the number of error pixel points;
the judging module 40 is configured to judge whether the image to be detected meets the visual requirement according to the number of the error pixel points.
In some embodiments, determining whether the image to be measured meets the visual requirement according to the number of the error pixel points includes:
calculating the ratio of the number of error pixel points to the total number of pixel points of the image to be detected, and judging whether the ratio is greater than a preset ratio threshold value or not;
and if not, determining that the image to be detected meets the visual requirement.
In some embodiments, determining whether the image to be measured meets the visual requirement according to the number of the error pixel points includes:
judging whether the number of the error pixel points is larger than a preset error number threshold value or not;
if yes, calculating an average pixel difference value according to pixel difference values between all error pixel points and pixel points in the corresponding standard image;
judging whether the average pixel difference value is larger than a preset error mean value threshold value or not;
and if not, determining that the image to be detected meets the visual requirement.
It should be noted that the above description about the image comparison method in fig. 1 is also applicable to the image comparison apparatus, and is not repeated herein.
In summary, according to the image comparison device of the embodiment of the present invention, an obtaining module is arranged to obtain an image to be detected and a standard image, where a pixel point in the image to be detected and a pixel point in the standard image are in a one-to-one correspondence relationship; the calculation module is used for calculating a pixel difference value between a pixel point in the image to be detected and a pixel point in the corresponding standard image, judging whether the pixel difference value is larger than a preset difference value threshold value or not, and taking the pixel point in the image to be detected as an error pixel point when the judgment result is yes; the statistical module is used for counting the number of the error pixel points; the judging module is used for judging whether the image to be detected meets the visual requirement or not according to the number of the error pixel points; therefore, the vision verification is realized, and the image comparison result is more in line with the vision verification requirement.
As will be appreciated by one skilled in the art, embodiments of the present invention may 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 an embodiment combining software and hardware aspects. Furthermore, the present invention may 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, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It should be noted that in the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
In the description of the present invention, it is to be understood that the terms "first", "second" and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implying any number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present invention, "a plurality" means two or more unless specifically defined otherwise.
In the present invention, unless otherwise expressly stated or limited, the terms "mounted," "connected," "secured," and the like are to be construed broadly and can, for example, be fixedly connected, detachably connected, or integrally formed; can be mechanically or electrically connected; either directly or indirectly through intervening media, either internally or in any other relationship. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
In the present invention, unless otherwise expressly stated or limited, the first feature "on" or "under" the second feature may be directly contacting the first and second features or indirectly contacting the first and second features through an intermediate. Also, a first feature "on," "over," and "above" a second feature may be directly or diagonally above the second feature, or may simply indicate that the first feature is at a higher level than the second feature. A first feature being "under," "below," and "beneath" a second feature may be directly under or obliquely under the first feature, or may simply mean that the first feature is at a lesser elevation than the second feature.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above should not be understood to necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.
Claims (8)
1. An image comparison method is characterized by comprising the following steps:
acquiring an image to be detected and a standard image, wherein pixel points in the image to be detected and pixel points in the standard image are in one-to-one correspondence relationship;
calculating a pixel difference value between a pixel point in the image to be detected and a pixel point in the corresponding standard image, judging whether the pixel difference value is larger than a preset difference value threshold value, and taking the pixel point in the image to be detected as an error pixel point when the judgment result is yes;
and counting the number of the error pixel points, and judging whether the image to be detected meets the visual requirement or not according to the number of the error pixel points.
2. The image comparison method of claim 1, wherein determining whether the image to be tested meets the visual requirement according to the number of the error pixel points comprises:
calculating the ratio of the number of the error pixel points to the total number of the pixel points of the image to be detected, and judging whether the ratio is greater than a preset ratio threshold value or not;
and if not, determining that the image to be detected meets the visual requirement.
3. The image comparison method of claim 1, wherein determining whether the image to be tested meets the visual requirement according to the number of the error pixel points comprises:
judging whether the number of the error pixel points is larger than a preset error number threshold value or not;
if yes, calculating an average pixel difference value according to pixel difference values between all error pixel points and pixel points in the corresponding standard image;
judging whether the average pixel difference value is larger than a preset error mean value threshold value or not;
and if not, determining that the image to be detected meets the visual requirement.
4. A computer-readable storage medium, on which an image matching program is stored, which when executed by a processor implements the image matching method according to any one of claims 1 to 3.
5. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor, when executing the program, implements the image matching method according to any one of claims 1-3.
6. An image matching device, comprising:
the device comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring an image to be detected and a standard image, and pixel points in the image to be detected and pixel points in the standard image are in one-to-one correspondence;
the calculation module is used for calculating a pixel difference value between a pixel point in the image to be detected and a pixel point in the corresponding standard image, judging whether the pixel difference value is larger than a preset difference threshold value or not, and taking the pixel point in the image to be detected as an error pixel point if the judgment result is yes;
the statistical module is used for counting the number of the error pixel points;
and the judging module is used for judging whether the image to be detected meets the visual requirement or not according to the number of the error pixel points.
7. The image comparison device of claim 6, wherein determining whether the image to be tested meets the visual requirement according to the number of the error pixel points comprises:
calculating the ratio of the number of the error pixel points to the total number of the pixel points of the image to be detected, and judging whether the ratio is greater than a preset ratio threshold value or not;
and if not, determining that the image to be detected meets the visual requirement.
8. The image comparison device of claim 6, wherein determining whether the image to be tested meets the visual requirement according to the number of the error pixel points comprises:
judging whether the number of the error pixel points is larger than a preset error number threshold value or not;
if yes, calculating an average pixel difference value according to pixel difference values between all error pixel points and pixel points in the corresponding standard image;
judging whether the average pixel difference value is larger than a preset error mean value threshold value or not;
and if not, determining that the image to be detected meets the visual requirement.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011617307.8A CN112669290A (en) | 2020-12-30 | 2020-12-30 | Image comparison method and device |
| PCT/CN2021/094857 WO2022142080A1 (en) | 2020-12-30 | 2021-05-20 | Image comparison method and apparatus |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011617307.8A CN112669290A (en) | 2020-12-30 | 2020-12-30 | Image comparison method and device |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112669290A true CN112669290A (en) | 2021-04-16 |
Family
ID=75411372
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011617307.8A Pending CN112669290A (en) | 2020-12-30 | 2020-12-30 | Image comparison method and device |
Country Status (2)
| Country | Link |
|---|---|
| CN (1) | CN112669290A (en) |
| WO (1) | WO2022142080A1 (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2022142080A1 (en) * | 2020-12-30 | 2022-07-07 | 稿定（厦门）科技有限公司 | Image comparison method and apparatus |
| CN115330657A (en) * | 2022-10-14 | 2022-11-11 | 威海凯思信息科技有限公司 | Ocean exploration image processing method and device and server |
| CN116229123A (en) * | 2023-02-21 | 2023-06-06 | 深圳市爱培科技术股份有限公司 | Binocular stereo matching method and device based on multi-channel grouping cross-correlation cost volume |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116911698B (en) * | 2023-09-14 | 2023-12-12 | 通渭县食品药品检验检测中心 | Food and drug detection system |
| CN117128888B (en) * | 2023-10-26 | 2024-01-09 | 天津华夏联盛汽车部件有限公司 | Error identification method for irregular bumper surface shape |
Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20120133781A1 (en) * | 2010-11-26 | 2012-05-31 | Hon Hai Precision Industry Co., Ltd. | System and method for identifying discrepancy of image of object |
| CN103544716A (en) * | 2013-10-30 | 2014-01-29 | 北京京北方信息技术有限公司 | Method and device for classifying colors of pixels of image |
| CN104008377A (en) * | 2014-06-07 | 2014-08-27 | 北京联合大学 | Ground traffic sign real-time detection and recognition method based on space-time correlation |
| CN106898082A (en) * | 2017-03-15 | 2017-06-27 | 深圳怡化电脑股份有限公司 | A kind of image is stained the method and device of judgement |
| CN108319908A (en) * | 2018-01-26 | 2018-07-24 | 华中科技大学 | A kind of untethered environment method for detecting human face based on Pixel-level Differential Characteristics |
| CN109242035A (en) * | 2018-09-25 | 2019-01-18 | 北京华开领航科技有限责任公司 | Vehicle bottom fault detection means and method |
| CN109345600A (en) * | 2018-09-04 | 2019-02-15 | 青岛海信电器股份有限公司 | A kind of local noise-reduction method, device and terminal based on tone |
| CN109711238A (en) * | 2018-07-24 | 2019-05-03 | 永康市巴九灵科技有限公司 | Protection against rodents formula intelligence cabinet |
| CN109740499A (en) * | 2018-12-28 | 2019-05-10 | 北京旷视科技有限公司 | Methods of video segmentation, video actions recognition methods, device, equipment and medium |
| CN109741377A (en) * | 2018-11-30 | 2019-05-10 | 四川译讯信息科技有限公司 | A kind of image difference detection method |
| CN110909791A (en) * | 2019-11-20 | 2020-03-24 | 车智互联（北京）科技有限公司 | Similar image identification method and computing device |
| CN111028213A (en) * | 2019-12-04 | 2020-04-17 | 北大方正集团有限公司 | Image defect detection method and device, electronic equipment and storage medium |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5446804A (en) * | 1994-04-14 | 1995-08-29 | Hewlett-Packard Company | Magnifying digital image using edge mapping |
| CN104239909B (en) * | 2014-08-11 | 2018-03-16 | 北京捷通华声语音技术有限公司 | A kind of recognition methods of image and device |
| CN106502891B (en) * | 2016-10-19 | 2019-05-17 | 广州视源电子科技股份有限公司 | The automatic testing method and device of user interface |
| CN112669290A (en) * | 2020-12-30 | 2021-04-16 | 稿定（厦门）科技有限公司 | Image comparison method and device |
-
2020
- 2020-12-30 CN CN202011617307.8A patent/CN112669290A/en active Pending
-
2021
- 2021-05-20 WO PCT/CN2021/094857 patent/WO2022142080A1/en active Application Filing
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20120133781A1 (en) * | 2010-11-26 | 2012-05-31 | Hon Hai Precision Industry Co., Ltd. | System and method for identifying discrepancy of image of object |
| CN103544716A (en) * | 2013-10-30 | 2014-01-29 | 北京京北方信息技术有限公司 | Method and device for classifying colors of pixels of image |
| CN104008377A (en) * | 2014-06-07 | 2014-08-27 | 北京联合大学 | Ground traffic sign real-time detection and recognition method based on space-time correlation |
| CN106898082A (en) * | 2017-03-15 | 2017-06-27 | 深圳怡化电脑股份有限公司 | A kind of image is stained the method and device of judgement |
| CN108319908A (en) * | 2018-01-26 | 2018-07-24 | 华中科技大学 | A kind of untethered environment method for detecting human face based on Pixel-level Differential Characteristics |
| CN109711238A (en) * | 2018-07-24 | 2019-05-03 | 永康市巴九灵科技有限公司 | Protection against rodents formula intelligence cabinet |
| CN109345600A (en) * | 2018-09-04 | 2019-02-15 | 青岛海信电器股份有限公司 | A kind of local noise-reduction method, device and terminal based on tone |
| CN109242035A (en) * | 2018-09-25 | 2019-01-18 | 北京华开领航科技有限责任公司 | Vehicle bottom fault detection means and method |
| CN109741377A (en) * | 2018-11-30 | 2019-05-10 | 四川译讯信息科技有限公司 | A kind of image difference detection method |
| CN109740499A (en) * | 2018-12-28 | 2019-05-10 | 北京旷视科技有限公司 | Methods of video segmentation, video actions recognition methods, device, equipment and medium |
| CN110909791A (en) * | 2019-11-20 | 2020-03-24 | 车智互联（北京）科技有限公司 | Similar image identification method and computing device |
| CN111028213A (en) * | 2019-12-04 | 2020-04-17 | 北大方正集团有限公司 | Image defect detection method and device, electronic equipment and storage medium |
Non-Patent Citations (1)
| Title |
|---|
| 代小红 等: "基于机器视觉的印刷品缺陷检测与识别", 《半导体光电》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2022142080A1 (en) * | 2020-12-30 | 2022-07-07 | 稿定（厦门）科技有限公司 | Image comparison method and apparatus |
| CN115330657A (en) * | 2022-10-14 | 2022-11-11 | 威海凯思信息科技有限公司 | Ocean exploration image processing method and device and server |
| CN116229123A (en) * | 2023-02-21 | 2023-06-06 | 深圳市爱培科技术股份有限公司 | Binocular stereo matching method and device based on multi-channel grouping cross-correlation cost volume |
Also Published As
| Publication number | Publication date |
|---|---|
| WO2022142080A1 (en) | 2022-07-07 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112669290A (en) | Image comparison method and device | |
| CN109948684B (en) | Quality inspection method, device and equipment for laser radar point cloud data labeling quality | |
| US20210192761A1 (en) | Image depth estimation method and device, readable storage medium, and electronic apparatus | |
| US10275682B2 (en) | Information processing apparatus, information processing method, and storage medium | |
| CN110111382B (en) | Irregular area calculation method and device, computer equipment and storage medium | |
| CN116824516B (en) | Road construction safety monitoring and management system | |
| CN112802080A (en) | Monocular absolute depth estimation method and device based on deep learning | |
| JP2007316950A (en) | Method, apparatus and program for processing image | |
| CN112700446A (en) | Algorithm model training method and device for industrial quality inspection | |
| CN115683012A (en) | Slope monitoring point displacement prediction method and device, electronic equipment and medium | |
| CN111461342A (en) | System integration method, medium, device and system based on machine learning | |
| US20210131840A1 (en) | Method for setting quality thresholds of products for testing purposes and device employing method | |
| CN112767211A (en) | Rescue resource recommendation method and device, electronic equipment and storage medium | |
| JP2019066267A (en) | Crack detector, crack detection method, and computer program | |
| CN112954310A (en) | Image quality detection method, device, computer equipment and readable storage medium | |
| JP2022013433A5 (en) | ||
| CN113538900B (en) | Method for detecting reverse driving of vehicle in parking lot | |
| CN114494253B (en) | Method and device for industrial quality inspection | |
| CN113256498B (en) | Interpolation method, device and equipment based on three-dimensional color space and storage medium | |
| CN113763383B (en) | Method and device for measuring elongation of steel bar | |
| CN111445391B (en) | Image contour point adjusting method, medium, device and apparatus | |
| CN109215068A (en) | Image magnification ratio measurement method and device | |
| CN116342534A (en) | Detection method, device and equipment for electric heating screw of air conditioner and storage medium | |
| CN112232283A (en) | Bubble detection method and system based on optical flow and C3D network | |
| CN113870359A (en) | Laser radar external parameter calibration method and device based on random gradient descent |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20210416 |
|
| RJ01 | Rejection of invention patent application after publication |