1 October 2005 Multiresolution descriptor matching algorithm for fast exhaustive search in norm-sorted databases
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Abstract
To determine the best match to a query image in a database, conventional content-based image retrieval schemes require the exhaustive search, where the descriptor of the query, e.g., the histogram, must be compared with literally all images in the database. However, the straightforward exhaustive search algorithm is computationally expensive. Thus, fast exhaustive search algorithms are required. We present a fast exhaustive search algorithm based on a multiresolution descriptor structure and a norm-sorted database. First, we derive a condition to eliminate unnecessary matching operations from the search procedure by using a norm-sorted structure of the database. Then, we propose a fast search algorithm based on the elimination condition, which guarantees an exhaustive search for either the best match or multiple best matches to a query. With a luminance histogram as a descriptor, we show that the proposed algorithm provides a search accuracy of 100% with a high search speed.
©(2005) Society of Photo-Optical Instrumentation Engineers (SPIE)
Byung Cheol Song and Jong Beom Ra "Multiresolution descriptor matching algorithm for fast exhaustive search in norm-sorted databases," Journal of Electronic Imaging 14(4), 043019 (1 October 2005). https://doi.org/10.1117/1.2132318
Published: 1 October 2005
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Databases

Image retrieval

Distance measurement

Genetic algorithms

Radium

Algorithm development

Content based image retrieval

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