A Novel Histogram-biasing Factor for Fast Sorted Histogram-based Measurement in Large Image Database Retrieval System

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Original languageEnglish
Pages (from-to)601-604
Journal / PublicationICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Publication statusPublished - 2003


Title2003 IEEE International Conference on Accoustics, Speech, and Signal Processing
PlaceHong Kong
CityHong Kong
Period6 - 10 April 2003


The exhaustive histogram matching is usually the most computational intensive part for any query in most large image database retrieval systems. In this paper, we introduce a histogram-biasing factor (HBF) to measure the biased-behavior of ordered-bins in a sorted histogram. The proposed HBF can be used to increase the early rejection rate of unreliable or impossible candidate reference images based on one of the sorted histograms. Moreover, it can be treated as a color-histogram descriptor. Only images with very closed HBFs are taken into account, searching speed can thus be increased without loss of accuracy. Experimental results show that the proposed factor results in up to 13 times speedup meanwhile providing the exhaustive retrieval performance.

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