Color image retrieval method based on particle clustering algorithm optimization

A color image and particle technology, applied in the field of image processing and computer vision, to achieve the effect of improving retrieval accuracy

Active Publication Date: 2018-04-24
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Problems solved by technology

[0006] Although CBIR technology has been studied for decades, there are still many key issues to be solved

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  • Color image retrieval method based on particle clustering algorithm optimization
  • Color image retrieval method based on particle clustering algorithm optimization
  • Color image retrieval method based on particle clustering algorithm optimization

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[0032] In order to make the purpose, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the implementation methods and accompanying drawings.

[0033] The color image retrieval method based on particle cluster algorithm optimization of the present invention normalizes various underlying features of a single image in the target database into an image information descriptor of a specific length, and stores the image features in the feature database to establish an index surface. During the image search process performed by the user, various single-lower-level feature extractions are performed on images used as search terms to form query vectors. Such as figure 1 As shown in , the similarity matching is performed by querying the feature vector and the feature vector in the feature database, and finally the retrieved image results are sorted and output in a unified way. Due to th...

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Abstract

The invention discloses a color image retrieval method based on particle clustering algorithm optimization and belongs to the technical field of image retrieval. The method comprises the steps that firstly, low-level features of all images in an image library are extracted respectively and stored in a picture feature library; secondly, different similarity measurement formulas are distributed fordifferent image feature descriptions; thirdly, the weights of similarity measures of a database are obtained through training by means of a PSO algorithm; fourthly, when image retrieval processing iscarried out, corresponding low-level feature extraction is carried out on inquired images, the inquired images are compared with feature descriptors extracted from the target database, on the basis ofthe trained weights of the similarity measures, the similarity measures of different features are subjected to unified sequencing, and first k most similar pictures are returned to serve as retrievalresults. Compared with the prior art, various feature extraction modes are combined and optimized, and by combining the feature descriptors, the retrieval precision of a CBIR retrieval system is improved.

Description

technical field [0001] The invention belongs to the technical fields of image processing and computer vision, and in particular relates to a color image retrieval method. Background technique [0002] The content-based image retrieval method (content-based image retrieval, CBIR) refers to the query condition itself is an image, or a description of the content of the image, and its indexing method is to extract the underlying features, and then compare these features by calculation. and the distance between the query conditions to determine the similarity of the two pictures. Since the 1970s, content-based image retrieval has been a hot research field. At present, mainstream search engines have launched their own image search functions. [0003] The existing CBIR technology is mainly based on knowledge in the fields of computer vision, pattern recognition, image processing, and image understanding, and then introduces new media data representation methods and data models to ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30G06K9/46G06K9/62
CPCG06F16/5838G06V10/507G06V10/56G06F18/22
Inventor 饶云波刘伟范柏江宋佳丽苟苗
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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