CN112749765A - Picture scene classification method, system, device and computer readable medium - Google Patents
Picture scene classification method, system, device and computer readable medium Download PDFInfo
- Publication number
- CN112749765A CN112749765A CN202110133970.9A CN202110133970A CN112749765A CN 112749765 A CN112749765 A CN 112749765A CN 202110133970 A CN202110133970 A CN 202110133970A CN 112749765 A CN112749765 A CN 112749765A
- Authority
- CN
- China
- Prior art keywords
- picture
- scene
- standard
- image
- similarity
- 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
- 238000000034 method Methods 0.000 title claims abstract description 29
- 238000004590 computer program Methods 0.000 claims description 8
- 238000000605 extraction Methods 0.000 claims description 5
- 238000004364 calculation method Methods 0.000 claims description 3
- 230000006870 function Effects 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000013145 classification model Methods 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000013135 deep learning Methods 0.000 description 1
- 238000013178 mathematical model Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
-
- 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
- G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Data Mining & Analysis (AREA)
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Evolutionary Biology (AREA)
- Evolutionary Computation (AREA)
- Bioinformatics & Computational Biology (AREA)
- General Engineering & Computer Science (AREA)
- Artificial Intelligence (AREA)
- Life Sciences & Earth Sciences (AREA)
- Multimedia (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
- Image Analysis (AREA)
Abstract
The invention discloses a method, a system, equipment and a computer readable medium for classifying picture scenes, wherein the method for classifying the picture scenes comprises the following steps: determining a standard picture under each scene; extracting picture characteristics of a standard picture in two dimensions, namely pixel mean value characteristics and picture contour characteristics; acquiring a new input picture; comparing the similarity of the newly input picture with the standard picture under different dimensions; and finishing the classification of the corresponding scenes of the new input picture according to the similarity of the new input picture and the standard picture under different dimensionalities. The image scene classification method and the image scene classification system can be used for rapidly classifying the image scenes based on a small number of labeled samples. The method has the advantages of short modeling time, high accuracy and easiness in iteration.
Description
Technical Field
The invention belongs to the technical field of mathematical model construction, and relates to a method, a system, equipment and a computer readable medium for classifying picture scenes.
Background
The method is used for classifying massive pictures containing different scenes, a common classification method (such as deep learning) needs a large number of labeled samples for training, and marking and signing models from the samples are trained, so that the time consumption is long.
In view of the above, there is an urgent need to design a new method for classifying a picture scene so as to overcome at least some of the above-mentioned disadvantages of the existing method for constructing a classification model.
Disclosure of Invention
The invention provides a method, a system, equipment and a computer readable medium for classifying picture scenes, which can be used for rapidly classifying the picture scenes based on a small number of samples with labels.
In order to solve the technical problem, according to one aspect of the present invention, the following technical solutions are adopted:
a picture scene classification method comprises the following steps:
determining a standard picture under each scene; extracting picture features of a standard picture under two dimensions, wherein the picture features comprise a pixel mean value feature and a picture outline feature; the picture contour characteristic is a Hash value of a picture;
acquiring a picture to be classified; extracting picture features of a picture to be classified under two dimensions, wherein the picture features comprise a pixel mean value feature and a picture outline feature; the picture contour characteristic is a Hash value of a picture;
comparing the similarity of the newly input picture with the standard picture under different dimensions; and finishing the classification of the corresponding scenes of the new input picture according to the similarity of the new input picture and the standard picture under different dimensionalities.
According to another aspect of the invention, the following technical scheme is adopted: a picture scene classification method comprises the following steps:
determining picture characteristics of a standard picture in each scene, wherein the picture characteristics comprise pixel mean value characteristics or/and picture contour characteristics;
acquiring picture characteristics of a picture to be classified, wherein the picture characteristics comprise pixel mean value characteristics or/and picture contour characteristics;
comparing the similarity of the picture to be classified and the standard picture under different dimensions; and finishing the classification of the corresponding scene of the new input picture according to the similarity of the picture to be compared and the standard picture under different dimensionalities.
As an embodiment of the present invention, the picture contour feature is a Hash value of the picture.
According to another aspect of the invention, the following technical scheme is adopted: a picture scene classification system, the picture scene classification system comprising:
the scene standard picture determining module is used for determining a standard picture in each scene;
the standard picture feature extraction module is used for extracting picture features of a standard picture under two dimensions, wherein the picture features comprise pixel mean features and picture outline features; the picture contour characteristic is a Hash value of a picture;
the image to be classified acquisition module is used for acquiring an image to be classified;
the image feature extraction module is used for extracting image features of the image to be classified under two dimensions, wherein the image features comprise pixel mean value features and image contour features; the picture contour characteristic is a Hash value of a picture;
the similarity calculation module is used for comparing the similarity of the newly input picture with the similarity of the standard picture under different dimensions;
and the scene classification module is used for finishing the classification of the scene corresponding to the new input picture according to the similarity of the new input picture and the standard picture under different dimensionalities.
According to another aspect of the invention, the following technical scheme is adopted: a picture scene classification system, the picture scene classification system comprising:
the picture characteristic confirming module is used for confirming picture characteristics of a standard picture in each scene, and the picture characteristics comprise pixel mean value characteristics or/and picture outline characteristics;
the image characteristic acquisition module is used for acquiring image characteristics of the image to be classified, and the image characteristics comprise pixel mean value characteristics or/and image contour characteristics;
the scene classification module is used for comparing the similarity of the picture to be classified and the standard picture under different dimensions; and finishing the classification of the corresponding scene of the new input picture according to the similarity of the picture to be compared and the standard picture under different dimensionalities.
As an embodiment of the present invention, the picture contour feature is a Hash value of the picture.
The invention has the beneficial effects that: the image scene classification method, the image scene classification system, the image scene classification equipment and the computer readable medium can be used for rapidly classifying the image scene based on a small number of labeled samples.
Drawings
Fig. 1 is a flowchart of a method for classifying a picture scene according to an embodiment of the present invention.
Fig. 2 is a schematic diagram illustrating a composition of a picture scene classification system according to an embodiment of the present invention.
Detailed Description
Preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
For a further understanding of the invention, reference will now be made to the preferred embodiments of the invention by way of example, and it is to be understood that the description is intended to further illustrate features and advantages of the invention, and not to limit the scope of the claims.
The description in this section is for several exemplary embodiments only, and the present invention is not limited only to the scope of the embodiments described. It is within the scope of the present disclosure and protection that the same or similar prior art means and some features of the embodiments may be interchanged.
The steps in the embodiments in the specification are only expressed for convenience of description, and the implementation manner of the present application is not limited by the order of implementation of the steps. The term "connected" in the specification includes both direct connection and indirect connection.
The invention discloses a picture scene classification method, which comprises the following steps:
determining picture characteristics of a standard picture in each scene, wherein the picture characteristics comprise pixel mean value characteristics or/and picture contour characteristics;
acquiring picture characteristics of a picture to be classified, wherein the picture characteristics comprise pixel mean value characteristics or/and picture contour characteristics;
comparing the similarity of the picture to be classified and the standard picture under different dimensions; and finishing the classification of the corresponding scene of the new input picture according to the similarity of the picture to be compared and the standard picture under different dimensionalities.
FIG. 1 is a flowchart illustrating a method for classifying a scene of a picture according to an embodiment of the present invention; referring to fig. 1, in an embodiment of the invention, the method includes:
step S1, determining a standard picture under each scene;
step S2, extracting picture features in two dimensions of the standard picture, which are the pixel mean feature and the picture contour feature respectively. In an embodiment of the present invention, the picture contour feature is a Hash value of the picture.
Step S3, acquiring a new input picture;
step S4, extracting picture features in two dimensions of the new input picture, which are the pixel mean feature and the picture contour feature respectively. In an embodiment, the picture contour feature is a Hash value of a picture.
Step S5, comparing the similarity of the newly input picture and the standard picture under different dimensionalities;
and (S6) finishing the classification of the corresponding scenes of the new input picture according to the similarity of the new input picture and the standard picture under different dimensionalities.
The invention also discloses a picture scene classification system, which comprises: the device comprises a picture feature confirming module, a picture feature obtaining module and a scene classification module. The picture characteristic confirming module is used for confirming picture characteristics of a standard picture in each scene, and the picture characteristics comprise pixel mean value characteristics or/and picture outline characteristics. The image feature obtaining module is used for obtaining image features of the image to be classified, and the image features comprise pixel mean features or/and image contour features. The scene classification module is used for comparing the similarity of the picture to be classified and the standard picture under different dimensions; and finishing the classification of the corresponding scene of the new input picture according to the similarity of the picture to be compared and the standard picture under different dimensionalities.
FIG. 2 is a schematic diagram illustrating an exemplary embodiment of a system for classifying scenes of pictures; referring to fig. 2, in an embodiment of the invention, the system includes: the system comprises a scene standard picture determining module 1, an image feature extracting module 2, an input picture acquiring module 3, a similarity calculating module 4 and a scene classifying module 5.
The scene standard picture determining module 1 is used for determining a standard picture in each scene.
The image feature extraction module 2 is configured to extract image features in two dimensions of the image, which are pixel mean features and image contour features. In an embodiment, the picture contour feature is a Hash value of a picture.
The input picture acquiring module 3 is used for acquiring a newly input picture.
The similarity calculation module 4 is used for comparing the similarity of the newly input picture with the standard picture in different dimensions.
The scene classification module 5 is used for completing classification of a scene corresponding to the new input picture according to similarity of the new input picture and the standard picture under different dimensionalities.
The invention also discloses a device of the picture scene classification method, which comprises a memory for storing computer program instructions and a processor for executing the computer program instructions, wherein the computer program instructions, when executed by the processor, trigger the device to execute the method.
The invention further discloses a computer readable medium having stored thereon computer program instructions executable by a processor to implement the above-described method.
In summary, the image scene classification method, system, device and computer readable medium provided by the present invention can rapidly classify image scenes based on a small number of labeled samples.
It should be noted that the present application may be implemented in software and/or a combination of software and hardware; for example, it may be implemented using Application Specific Integrated Circuits (ASICs), general purpose computers, or any other similar hardware devices. In some embodiments, the software programs of the present application may be executed by a processor to implement the above steps or functions. As such, the software programs (including associated data structures) of the present application can be stored in a computer-readable recording medium; such as RAM memory, magnetic or optical drives or diskettes, and the like. In addition, some steps or functions of the present application may be implemented using hardware; for example, as circuitry that cooperates with the processor to perform various steps or functions.
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The description and applications of the invention herein are illustrative and are not intended to limit the scope of the invention to the embodiments described above. Effects or advantages referred to in the embodiments may not be reflected in the embodiments due to interference of various factors, and the description of the effects or advantages is not intended to limit the embodiments. Variations and modifications of the embodiments disclosed herein are possible, and alternative and equivalent various components of the embodiments will be apparent to those skilled in the art. It will be clear to those skilled in the art that the present invention may be embodied in other forms, structures, arrangements, proportions, and with other components, materials, and parts, without departing from the spirit or essential characteristics thereof. Other variations and modifications of the embodiments disclosed herein may be made without departing from the scope and spirit of the invention.
Claims (8)
1. A picture scene classification method is characterized by comprising the following steps:
determining a standard picture under each scene; extracting picture features of a standard picture under two dimensions, wherein the picture features comprise a pixel mean value feature and a picture outline feature; the picture contour characteristic is a Hash value of a picture;
acquiring a picture to be classified; extracting picture features of a picture to be classified under two dimensions, wherein the picture features comprise a pixel mean value feature and a picture outline feature; the picture contour characteristic is a Hash value of a picture;
comparing the similarity of the newly input picture with the standard picture under different dimensions; and finishing the classification of the corresponding scenes of the new input picture according to the similarity of the new input picture and the standard picture under different dimensionalities.
2. A picture scene classification method is characterized by comprising the following steps:
determining picture characteristics of a standard picture in each scene, wherein the picture characteristics comprise pixel mean value characteristics or/and picture contour characteristics;
acquiring picture characteristics of a picture to be classified, wherein the picture characteristics comprise pixel mean value characteristics or/and picture contour characteristics;
comparing the similarity of the picture to be classified and the standard picture under different dimensions; and finishing the classification of the corresponding scene of the new input picture according to the similarity of the picture to be compared and the standard picture under different dimensionalities.
3. The picture scene classification method according to claim 2, characterized in that:
the picture contour characteristic is a Hash value of the picture.
4. A picture scene classification system, comprising:
the scene standard picture determining module is used for determining a standard picture in each scene;
the standard picture feature extraction module is used for extracting picture features of a standard picture under two dimensions, wherein the picture features comprise pixel mean features and picture outline features; the picture contour characteristic is a Hash value of a picture;
the image to be classified acquisition module is used for acquiring an image to be classified;
the image feature extraction module is used for extracting image features of the image to be classified under two dimensions, wherein the image features comprise pixel mean value features and image contour features; the picture contour characteristic is a Hash value of a picture;
the similarity calculation module is used for comparing the similarity of the newly input picture with the similarity of the standard picture under different dimensions;
and the scene classification module is used for finishing the classification of the scene corresponding to the new input picture according to the similarity of the new input picture and the standard picture under different dimensionalities.
5. A picture scene classification system, comprising:
the picture characteristic confirming module is used for confirming picture characteristics of a standard picture in each scene, and the picture characteristics comprise pixel mean value characteristics or/and picture outline characteristics;
the image characteristic acquisition module is used for acquiring image characteristics of the image to be classified, and the image characteristics comprise pixel mean value characteristics or/and image contour characteristics;
the scene classification module is used for comparing the similarity of the picture to be classified and the standard picture under different dimensions; and finishing the classification of the corresponding scene of the new input picture according to the similarity of the picture to be compared and the standard picture under different dimensionalities.
6. The picture scene classification system according to claim 4, characterized in that:
the picture contour characteristic is a Hash value of the picture.
7. A device for a picture scene classification method, characterized in that the device comprises a memory for storing computer program instructions and a processor for executing the computer program instructions, wherein the computer program instructions, when executed by the processor, trigger the device to perform the method of any of claims 1 to 3.
8. A computer-readable medium having computer program instructions stored thereon, the computer-readable instructions being executable by a processor to implement the method of any one of claims 1 to 3.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110133970.9A CN112749765A (en) | 2021-02-01 | 2021-02-01 | Picture scene classification method, system, device and computer readable medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110133970.9A CN112749765A (en) | 2021-02-01 | 2021-02-01 | Picture scene classification method, system, device and computer readable medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112749765A true CN112749765A (en) | 2021-05-04 |
Family
ID=75653450
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110133970.9A Pending CN112749765A (en) | 2021-02-01 | 2021-02-01 | Picture scene classification method, system, device and computer readable medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112749765A (en) |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111222548A (en) * | 2019-12-30 | 2020-06-02 | Oppo广东移动通信有限公司 | Similar image detection method, device, equipment and storage medium |
-
2021
- 2021-02-01 CN CN202110133970.9A patent/CN112749765A/en active Pending
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111222548A (en) * | 2019-12-30 | 2020-06-02 | Oppo广东移动通信有限公司 | Similar image detection method, device, equipment and storage medium |
Non-Patent Citations (1)
| Title |
|---|
| 简献忠;唐章源;: "一种融合感知哈希的快速压缩跟踪算法", 《小型微型计算机系统》, no. 11, 15 November 2018 (2018-11-15), pages 153 - 157 * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US10803554B2 (en) | Image processing method and device | |
| US9218537B2 (en) | Image processing device and image processing method | |
| US9928439B2 (en) | Facilitating text identification and editing in images | |
| US20150379371A1 (en) | Object Detection Utilizing Geometric Information Fused With Image Data | |
| CN109918513B (en) | Image processing method, device, server and storage medium | |
| CN109919002B (en) | Yellow stop line identification method and device, computer equipment and storage medium | |
| CN111191649A (en) | Method and equipment for identifying bent multi-line text image | |
| CN111753764A (en) | Gesture recognition method of edge terminal based on attitude estimation | |
| CN110210480B (en) | Character recognition method and device, electronic equipment and computer readable storage medium | |
| CN113221918B (en) | Target detection method, training method and device of target detection model | |
| CN112380978A (en) | Multi-face detection method, system and storage medium based on key point positioning | |
| US20150023599A1 (en) | Optical Match Character Classification | |
| CN114359932B (en) | Text detection method, text recognition method and device | |
| CN111611438B (en) | Picture labeling method, device, processing equipment and system | |
| CN111950517A (en) | Target detection method, model training method, electronic device and storage medium | |
| KR20110087620A (en) | Layout based page recognition method for printed medium | |
| US10509986B2 (en) | Image similarity determination apparatus and image similarity determination method | |
| CN114821513B (en) | Image processing method and device based on multilayer network and electronic equipment | |
| CN109816709B (en) | Monocular camera-based depth estimation method, device and equipment | |
| CN114267076B (en) | Image identification method, device, equipment and storage medium | |
| CN112749765A (en) | Picture scene classification method, system, device and computer readable medium | |
| CN111914850A (en) | Picture feature extraction method, device, server and medium | |
| KR102256409B1 (en) | Method of generating a learning data set and computer apparatus for generating a learning data set | |
| US20230368324A1 (en) | Method and apparatus of embedding image in video, and method and apparatus of acquiring plane prediction model | |
| CN111476090A (en) | Watermark identification method and device |
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 |