| Summary: | 碩士 === 國立中正大學 === 資訊工程研究所 === 89 === Traditional region-based image retrieval systems often use only the dominant features within each region and ignore the useful relationship of neighboring regions. In this paper, we propose a new color region-based image retrieval system using the region relationship. An image is first processed with the wavelet transform to divide the image into several subbands and to extract the important texture information. A new color watershed transformation on not only the luminance wavelet coefficients but also the chromatic wavelet coefficients is performed to accurately segment the image into several important regions. Then, the region adjacency graph (RAG) is used to be the representation of the regions and their spatial relationships in the segmented image. In the RAG, a node denotes one region and an edge represents the spatial relationship of two neighboring regions. Hence, the features of regions such as the wavelet coefficients in an image can be recorded in their corresponding nodes within a RAG; while the features of adjacent regions are recorded in the edges. Now, the image retrieval problem is reduced to a subgraph isomorphism algorithm, which is performed to verify the similarity between two graphs. A simple and heuristic algorithm of subgraph isomorphism is applied to compare the query image’s RAG with those RAGs in the image database. In experiments, several query results from the test database that contains various kinds of images are used to evaluate the performance of proposed system.
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