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Image Identifier based on Local Feature's Histogram and Acceleration Technique using GPU  

Jeon, Hyeok-June (충남대학교 컴퓨터공학부)
Seo, Yong-Seok (한국전자통신연구원 콘텐츠연구본부)
Hwang, Chi-Jung (충남대학교 컴퓨터공학부)
Publication Information
Journal of KIISE:Computing Practices and Letters / v.16, no.9, 2010 , pp. 889-897 More about this Journal
Abstract
Recently, a cutting-edge large-scale image database system has demanded these attributes: search with alarming speed, performs with high accuracy, archives efficiently and much more. An image identifier (descriptor) is for measuring the similarity of two images which plays an important role in this system. The extraction method of an image identifier can be roughly classified into two methods: a local and global method. In this paper, the proposed image identifier, LFH(Local Feature's Histogram), is obtained by a histogram of robust and distinctive local descriptors (features) constrained by a district sub-division of a local region. Furthermore, LFH has not only the properties of a local and global descriptor, but also can perform calculations at a magnificent clip to determine distance with pinpoint accuracy. Additionally, we suggested a way to extract LFH via GPU (OpenGL and GLSL). In this experiment, we have compared the LFH with SIFT (local method) and EHD (global method) via storage capacity, extraction and retrieval time along with accuracy.
Keywords
LFH; feature histogram; image identifier; image descriptor; image retrieval;
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