Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/44469
標題: Iris recognition based on relative variation analysis with feature selection
作者: Tsai, C.C.
陶金旭
Taur, J.
Tao, C.W.
關鍵字: iris recognition;Gabor filter;feature selection;wavelet transform
Project: Optical Engineering
期刊/報告no:: Optical Engineering, Volume 47, Issue 9.
摘要: 
Iris recognition has received increasing attention in the field of biometrics due to its high performance in human identification. A challenge of iris recognition is to extract the small-size data with sufficient information from distinctive iris patterns. We propose a novel feature extraction algorithm for iris recognition, which utilizes a bank of Gabor filters and an effective encoding method. In image preprocessing, the lower portion of the iris is normalized and unwrapped into a rectangular block where the occluded area is masked out. Then multichannel Gabor filters are used to decompose the iris block. An iris code is generated by analyzing and encoding the horizontal variation of each filtered image. Finally, a feature selection scheme is adopted to remove redundant features to reduce the data size and improve the performance. Experimental results on public iris databases show that the proposed approach has a smaller code size and a lower equal error rate. (c) 2008 Society of Photo-Optical Instrumentation Engineers. [DOI: 10.1117/1.2977528]
URI: http://hdl.handle.net/11455/44469
ISSN: 0091-3286
DOI: 10.1117/1.2977528
Appears in Collections:電機工程學系所

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