Method, device and system for image classification

A classification method and image technology, applied in the field of image processing, can solve the problems of lack of effectiveness and comprehensiveness of image classification methods

Active Publication Date: 2013-09-25
SHANGHAI KEENSHINE ELECTRONIC TECH CO LTD
View PDF2 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the embodiments of the present invention is to provide an image classification method, aiming to solve the problem of lack of effectiveness and comprehensiveness of the existing image classification methods

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Method, device and system for image classification
  • Method, device and system for image classification
  • Method, device and system for image classification

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0098] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0099] In the embodiment of the present invention, according to the pre-established optimization function model of dictionary learning and the normalization matrix, the dictionary primitives of dictionary learning and the sparse coefficients of the unlabeled images are generated; according to the sparse coefficients of the unlabeled images Classify the unlabeled image, so that there is no need to extract a large number of features of the image, and there is no need to retrieve and classify the image through the feature, thus avoiding the complexity of the image, each specific feature only represents...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention relates to the field of image processing, and provides a method for image classification. The method for image classification comprises the steps of (1) obtaining images without being labeled, carrying out preprocessing on the obtained images without being labeled to generate a standardized matrix of the images without being labeled, (2) generating a dictionary primitive of dictionary learning and sparsity coefficients of the images without being labeled according to a prebuilt optimization function model of the dictionary learning and the standardized matrix, and (3) carrying out classification on the images without being labeled according to the sparsity coefficients of the images without being labeled. According to the method for image classification, the situations that each specific feature only represents a part of information, and each specific feature is only effective on part of image targets due to complexity of the images are avoided, meanwhile, the situations that a training model only contains information of labeled images, labeled information is extremely limited, and a large amount of information without being labeled is wasted are avoided, thus, the problem that an existing method for image classification is poor in validity and comprehensiveness is solved, and efficiency of image classification is improved.

Description

technical field [0001] The invention belongs to the field of image processing, and in particular relates to an image classification method, device and system. Background technique [0002] With the explosive increase of multimedia data, it is more and more difficult to manually classify images, and the automatic classification based on image content is getting more and more attention. Automatic image classification technology can predict the category of the image by processing and analyzing the content of the image itself, avoiding a lot of manual processing. How to use computers to automatically divide images into different semantic categories according to the way people understand has become a key issue in image processing. [0003] However, the existing image classification methods lack effectiveness and comprehensiveness. Specifically, the existing image classification methods mainly realize the automatic classification of images through the content characteristics of i...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06K9/62
Inventor 秦兴德王军吴金勇
Owner SHANGHAI KEENSHINE ELECTRONIC TECH CO LTD
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap