Please use this identifier to cite or link to this item: https://doi.org/10.1016/S0169-023X(00)00002-1
Title: MOSAIC: A fast multi-feature image retrieval system
Authors: Goh, S.-T. 
Tan, K.-L. 
Issue Date: 2000
Citation: Goh, S.-T., Tan, K.-L. (2000). MOSAIC: A fast multi-feature image retrieval system. Data and Knowledge Engineering 33 (3) : 219-239. ScholarBank@NUS Repository. https://doi.org/10.1016/S0169-023X(00)00002-1
Abstract: Content-based image retrieval plays an important role in many multimedia applications. Images are typically retrieved based on a given sample image, a sketch or a simple description of the content. The rate of this retrieval is undeniably gaining importance as databases increase constantly in size. In this paper, we present MOSAIC, an image retrieval system that we have developed. In MOSAIC, an image is represented by a set of clusters, each of which captures information on multiple features - the `color' of the cluster, the `size' of the cluster and the `spatial' location of the cluster. We also propose an index structure, to facilitate speed retrieval of images. The structure is multitier with each tier dealing with one feature. In this way, images that are dissimilar in the higher tier can be pruned away immediately. We implemented and evaluated MOSAIC, and our results show that the system can retrieve relevant images effectively and efficiently.
Source Title: Data and Knowledge Engineering
URI: http://scholarbank.nus.edu.sg/handle/10635/39196
ISSN: 0169023X
DOI: 10.1016/S0169-023X(00)00002-1
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