Retrieving image resource technique based on bayes semantic classification and visual feature extraction

Tao Gao, Guo Li*, Jie Hou

*此作品的通讯作者

    科研成果: 期刊稿件文章同行评审

    3 引用 (Scopus)

    摘要

    An image retrieval method was proposed based on feature extracted in DCT and semantic classification by bayes. Firstly, Semantic need for retrieving digital image was studied, and Simple Bayesian Classifier was used in semantic classification of image resource; secondly, improved image feature of edge space distribution probability based on DCT was extracted to obtain edge information of goal object and to set up 20 Eigen values. Thirdly, indexing feature vectors were obtained through semantic classification for semantic filtration, by which the retrieval efficiency was improved. With experiment, image resource database is established and the proposed algorithm shows better results by test on precision comparison compared with other methods.

    源语言英语
    页(从-至)929-934
    页数6
    期刊Journal of Internet Technology
    14
    6
    DOI
    出版状态已出版 - 2013

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