The proposed system for image retrieval using multidimensional features (IRMF) characterises and matches image content in a high dimensional feature space of colour, texture and shape dimensions. By including the entire pyramid of low-, medium-, and high-level primitives, the semantics of image content at different feature levels can be represented and extracted efficiently for image retrieval. This provides accurate query formulation and improves the accuracy in the search results. By co-jointly matching image features in a multidimensional space rather than in separate independent feature spaces, the precision in image retrieval is improved from more than 50% to up to 90% for the top 10 most similar images retrieved. The impact of the information of the image's background has been mentioned in a very few published papers. Our experiments show that the efficient extraction of background information can improve the precision of image retrieval. To speed up the retrieval process, we also propose interactive relevance feedback to let the user participate in the process. The system is implemented for Internet Web access.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Image retrieval with relevance feedback


    Contributors:
    Li Fang, (author) / Ang Yew Hock, (author)


    Publication date :

    2000-01-01


    Size :

    771772 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Image Retrieval with Relevance Feedback

    Fang, L. / Hock, A. | British Library Conference Proceedings | 2000


    Interactive Content-Based Image Retrieval Using Relevance Feedback

    MacArthur, S. D. / Brodley, C. E. / Kak, A. C. et al. | British Library Online Contents | 2002


    Bayesian Relevance Feedback for Content-based Image Retrieval

    Vasconcelos, N. / Lippman, A. / IEEE | British Library Conference Proceedings | 2000


    Multi-class relevance feedback content-based image retrieval

    Peng, J. | British Library Online Contents | 2003