Content-based image retrieval from a large image database

Authors:
Zhen Jia;Laurent Amselag;Patric Gros
Affiliations:
School of EEE, Nanyang Technological University, Singapore 639798;TexMex Group, IRISA-CNRS, Rennes 350042, France;TexMex Group, IRISA-CNRS, Rennes 350042, France
Venue:
Pattern Recognition
Year:
2008

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Abstract

In this paper, a content-based image retrieval system is built based on the image local descriptors and database indexing and searching techniques. The proposed system is designed for a powerful computer system-the ReMIX platform. The ReMIX system manages hundreds of GB memories and a number of power CPUs. Using this ReMIX system, the image retrieval over a large database becomes an easy and efficient task. In this paper, firstly, the image local descriptors, the ReMIX system's architectures and multi-dimensional database indexing and searching techniques are described. Secondly, the specific database searching strategies based on the ReMIX system are explained. Thirdly, due to the hardware requirement of the ReMIX platform, integer instead of float or double is the best data format for hardware implementation. Therefore, the novel float-to-integer conversion is presented with the step by step procedures. Finally, in the experimental results, the comparisons among using float values and integer values and also using different integer conversion parameters are presented. Several images generated with large image variations are queried into a large database to demonstrate the image retrieval power of the ReMIX system. From the results, it is clear that the ReMIX system is a powerful tool for the content-based image retrieval.