A study on searching image by cluster indexing and sequential I/O


The KIPS Transactions:PartD, Vol. 9, No. 5, pp. 779-788, Oct. 2002
10.3745/KIPSTD.2002.9.5.779,   PDF Download:

Abstract

There are many technically difficult issues in searching multimedia data such as image, video and audio because they are massive and more complex than simple text-based data. As a method of searching multimedia data, a similarity retrieval has been studied to retrieve automatically basic features of multimedia data and to make a search among data with retrieved features because exact match is not adaptable to a matrix of features of multimedia. In this paper, data clustering and its indexing are proposed as a speedy similarity-retrieval method of multimedia data. This approach clusters similar images on adjacent disk cylinders and then builds indexes to access the clusters. To minimize the search cost, the hashing is adapted to index cluster. In addition, to reduce I/O time, the proposed searching takes just one I/O to look up the location of the cluster containing similar object and one sequential file I/O to read in this cluster. The proposed schema solves the problem of multi- dimension by using clustering and its indexing and has higher search efficiency than the content-based image retrieval that uses only clustering or indexing structure.


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Cite this article
[IEEE Style]
J. O. Kim and D. J. Hwang, "A study on searching image by cluster indexing and sequential I/O," The KIPS Transactions:PartD, vol. 9, no. 5, pp. 779-788, 2002. DOI: 10.3745/KIPSTD.2002.9.5.779.

[ACM Style]
Jin Ok Kim and Dae Joon Hwang. 2002. A study on searching image by cluster indexing and sequential I/O. The KIPS Transactions:PartD, 9, 5, (2002), 779-788. DOI: 10.3745/KIPSTD.2002.9.5.779.