A Fast Two-Phased Initial Search Technique For Arbitrary-Shaped Queries


Arbitrary-shaped queries; Filtering; Indexing/retrieval technique; Noise reduction


Most content-based image retrieval techniques are not able to eliminate noise (i.e., irrelevant regions) from similarity matching since they capture the features of the entire image area or pre-perceived objects at the database build time. Recent approaches address this outstanding issue by allowing users to arbitrarily exclude noise in formulating their queries. This capability has resulted in high retrieval effectiveness for a wide range of queries. However, implementing these techniques for large image collections presents a great challenge since we can not assume any shape for queries defined by users. In this paper, we propose an efficient indexing/retrieval technique for arbitrary-shaped queries which is able to eliminate a majority of unqualified images. Moreover, we improve the retrieval process with a filtering phase to prune out additional false matches before the detailed similarity measure is carried out. We have implemented the proposed technique in our image retrieval system for a large image collection. Our experimental results show that our technique is capable of handling image matching very well and 70 times on average faster than the straightforward sequential scanning.

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Proceedings of SPIE - The International Society for Optical Engineering



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Article; Proceedings Paper

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0035053784 (Scopus)

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