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�������պ����ѧѧ�� 2008, Vol. 34 Issue (03) :290-294    DOI:
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Palmprint recognition based on ICA and BP neural network
Chen Zhi, Huang Linlin*
School of Automation Science and Electrical Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100083, China

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ժҪ �����һ�ֻ��ڶ����ɷַ���(ICA,Independent Comment Analysis)�Ͷ��ǰ��(BP,Back Propagation)���������ϵķ��������ƽ���ʶ��.���Ȳ���һ���µķ������ǵ�,�õ�����ͼ��IJ���������,������Щ��У�����Ʒ��򲢵õ����Ƶĸ���Ȥ����.�Ը�������ö������ICA�㷨(FastICA),�õ����������ӿռ�,Ȼ�󹹽�BP������,������ѵ�������õ���������������ѵ��,�õ����ʵ�Ȩֵ.���������ѧ�������ݿ���в���,�����ɷַ���(PCA,Principal Components Analysis)��ȡ�����ķ������бȽ�,ȡ���˽ϸߵ�ʶ����.
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Abstract�� A novel method based on independent comment analysis (ICA) and back propagation neural network (BPNN) was proposed to solve palmprint recognition. First, a new method was used to detect corner points as the invariant feature points in palm images. Then the palm images were aligned by the points, and the region of interest (ROI) of the images was gotten. In the next place, palmprint features were extracted from the ROI by a fast fixed-point algorithm for ICA (FastICA). By means of this method, the original palmprint ROI images were transformed into a small set of feature space. Finally, the BPNN was trained by the feature spaces of the samples in the training set to get the appropriate weights. After the training, perform palm classification was applied. The method was tested on the Hong Kong Polytechnic University palmprint database. Experimental results show that method based on ICA achieves higher recognition rate than that based on principal components analysis (PCA).
Keywords�� independent comment analysis   principal components analysis   back propagation neural network   region of interest   palmprint recognition     
Received 2007-06-29;
About author: �� ��(1982-),��,����֣����,˶ʿ��,llhuang@buaa.edu.cn.
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����,������.����ICA��BP���������ϵ�����ʶ��[J]  �������պ����ѧѧ��, 2008,V34(03): 290-294
Chen Zhi, Huang Linlin.Palmprint recognition based on ICA and BP neural network[J]  JOURNAL OF BEIJING UNIVERSITY OF AERONAUTICS AND A, 2008,V34(03): 290-294
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http://bhxb.buaa.edu.cn//CN/     ��     http://bhxb.buaa.edu.cn//CN/Y2008/V34/I03/290
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