An Extendible Hash for Multi-Precision Similarity Querying of Image Databases
Shu Wen Lin, M. TAMER ÖZSU, Vincent Oria, Raymond T. Ng · 2001
Abstract We propose multi-precision similarity matchingwhere the image is divided into a number of subblocks, each with its associated color histogram.We present experimental results showing that the spatial distribution information recorded by multi-precision color histograms helps to make similarity matching more precise. We also showthat sub-image queries are much better supported with multi-precision color histograms. To mini-mize the overhead, we employ a filtering scheme based on the 3-dimensional average color vectors.We provide a formal result proving that filtering with multi-precision color histograms is complete.Finally, we develop a novel extendible hashing structure for indexing the average color vectors.We give experimental results showing that the proposed structure significantly outperforms theSR-tree.