Visual keyword image retrieval based on synergetic neural network for web-based image search

Tong Zhao, Lilian H. Tang, Horace H.S. Ip, Feihu Qi

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

    8 Citations (Scopus)

    Abstract

    Feature extraction and similarity measure are two basic key issues in image retrieval. Combining the advantages of SNN in image recognition and selective attention for image retrieval, a novel visual keywords-driven image retrieval approach based on these properties has been proposed. By using a predefined set of visual keywords as prototype patterns stored with the SNN and then measuring the degree of similarity of the stored images to the visual keywords, we show that such a visual keyword driven SNN can provide the framework for image indexing or retrieval which is scalable, robust and efficient for web-based search.
    Original languageEnglish
    Pages (from-to)127-142
    JournalReal-Time Systems
    Volume21
    Issue number1-2
    DOIs
    Publication statusPublished - Jul 2001

    Research Keywords

    • Affine-invariant feature
    • Synergetic neural network
    • Trademark image retrieval
    • Visual keywords, web-based multimedia search

    Fingerprint

    Dive into the research topics of 'Visual keyword image retrieval based on synergetic neural network for web-based image search'. Together they form a unique fingerprint.

    Cite this