J. Vass, J. Yao, A. Joshi, K. Palaniappan, and X. Zhuang

17th IEEE Symp. Reliable Distributed Systems, pgs. 461--466, 1998

segmentation, image analysis, color, shape, data mining, cbir

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Abstract

An efficient image database system is developed. The most important features of the proposed system include compressed domain indexing, searching by using scalable features, and progressive image transmission. User interaction is involved both at the search refinement stage and in the display of the query results. The most important query types include query by color layout and query by wavelet-coefficient clustering information. The indexing and searching algorithms are tightly coupled with the underlying image compression algorithm by which means the images are stored in the database, reducing both the complexity and the storage requirements of the database management system. In this research, we utilize our previously developed (B.-B. Chai et al., 1997, 1998) high-performance wavelet image coding algorithm, termed “significance-linked connected component analysis”, which not only renders a very high compression performance when compared to other top-ranked wavelet image coding algorithms and the JPEG standard, but also inherently supports scalable features and progressive transmission. Computer experiments demonstrate the efficiency of the developed system