Research of semantics saving in content based image retrieval based on complex networks
Hebiao Yang
Abstract
Hebiao Yang
Abstract
The research focus of CBIR is how to understand the content of image,digest the features of image and organize those features to retrieve.The result of retrieval is often discarded,which can not be used for the future retrieval of the similar images.This paper proposes a novel scheme for semantics saving of the results of the image retrieval,which uses the similar images of the retrieval results to form the complex network whose nodes are the regions of the images and uses the community finding algorithm to get the semantics communities to save the semantics concept of the retrieval results for matching the similar image of the same semantics in the future retrieval.It has shown from the experiments that the complex networks have the character of small world and can quicken the retrieval process for retrieving the similar semantics images.
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The research focus of CBIR is how to understand the content of image,digest the features of image and organize those features to retrieve.The result of retrieval is often discarded,which can not be used for the future retrieval of the similar images.This paper proposes a novel scheme for semantics saving of the results of the image retrieval,which uses the similar images of the retrieval results to form the complex network whose nodes are the regions of the images and uses the community finding algorithm to get the semantics communities to save the semantics concept of the retrieval results for matching the similar image of the same semantics in the future retrieval.It has shown from the experiments that the complex networks have the character of small world and can quicken the retrieval process for retrieving the similar semantics images.
Key concepts: Image retrieval, Computer science, Semantics (computer science), Information retrieval, Content-based image retrieval, Automatic image annotation, Matching (statistics), Visual Word