A SIMILARITY MEASURE FOR COLOR IMAGE RETRIEVAL AND INDEXING BASED ON THE MULTIVARIATE TWO SAMPLE PROBLEM (FriPmOR4)

Author(s) : Christos Theoharatos (University of Patras, Greece) Nikolaos Laskaris (University of Patras, Greece) George Economou (University of Patras, Greece) Spiros Fotopoulos (University of Patras, Greece)

Abstract : In this work, a similarity measure in the feature space is proposed for color retrieval and indexing based on the ‘‘Multivariate Two-Sample Problem’’. Color information is extracted via random selection of image pixels from high-density regions. The proposed scheme has a global nature due to its randomness and is easy to implement. It makes uses of the minimal spanning tree (MST) structure and properties, providing the retrieval results with a statistical measure of their significance level. The main advantages of our proposal are its computational efficiency and the fact that it is generally applicable to natural image collections.

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