Image retrieval based on regions of interest

    Authors

    K. Vu; K. A. Hua;W. Tavanapong

    Comments

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    Abbreviated Journal Title

    IEEE Trans. Knowl. Data Eng.

    Keywords

    image processing; image indexing and retrieval; regions of interest; arbitrary-shaped queries; Computer Science, Artificial Intelligence; Computer Science, Information; Systems; Engineering, Electrical & Electronic

    Abstract

    Query-by-example is the most popular query model in recent content-based image retrieval (CBIR) systems. A typical query image includes relevant objects (e.g., Eiffel Tower), but also irrelevant image areas (including background). The irrelevant areas limit the effectiveness of existing CBIR systems. To overcome this limitation, the system must be able to determine similarity based on relevant regions alone. We call this class of queries region-of-interest (ROI) queries and propose a technique for processing them in a sampling-based matching framework. A new similarity model is presented and an indexing technique for this new environment is proposed. Our experimental results confirm that traditional approaches, such as Local Color Histogram and Correlogram, suffer from the involvement of irrelevant regions. Our method can handle ROI queries and provide significantly better performance. We also assessed the performance of the proposed indexing technique. The results clearly show that our retrieval procedure is effective for large image data sets.

    Journal Title

    Ieee Transactions on Knowledge and Data Engineering

    Volume

    15

    Issue/Number

    4

    Publication Date

    1-1-2003

    Document Type

    Article

    Language

    English

    First Page

    1045

    Last Page

    1049

    WOS Identifier

    WOS:000183902100024

    ISSN

    1041-4347

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