Title

Image retrieval based on regions of interest

Authors

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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