Content-based object organization for efficient image retrieval in image databases

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Much research has focused on content-based image retrieval (CBIR) methods that can be automated in image classification and query processing. In this paper, we propose a blob-centric image retrieval scheme based on the blobworld representation. The blob-centric scheme consists of several newly proposed components, including an image classification method, an image browsing method based on semantic hierarchy of representative blobs, and a blob search method based on multidimensional indexing. We present the database structures and their maintenance algorithms for these components and conduct a performance comparison of three image retrieval methods, the naive method, the representative-blobs method, and the indexed-blobs method. Our quantitative analysis shows significant reduction in query response time by using the representative-blobs method and the indexed-blobs method.

论文关键词:Blob-centric image representation,Content-based image retrieval,Image database management,MB+-trees,Multi-dimensional indexing,Object-oriented image organization

论文评审过程:Received 10 June 2005, Revised 26 February 2006, Accepted 24 April 2006, Available online 15 June 2006.

论文官网地址:https://doi.org/10.1016/j.dss.2006.04.013