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

Tao Gao, Guo Li*, Jie Hou

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    3 Citations (Scopus)

    Abstract

    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.

    Original languageEnglish
    Pages (from-to)929-934
    Number of pages6
    JournalJournal of Internet Technology
    Volume14
    Issue number6
    DOIs
    Publication statusPublished - 2013

    Keywords

    • Bayesian classifier
    • Feature extracted in DCT
    • Image retrieval
    • Image semantic classification

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