计算机工程与应用2011，Vol.47Issue(19)：182-185,4.DOI:10.3778/j.issn.1002-8331.2011.19.051
应用二维EMD和独立成分分析的掌纹识别
Approach for palm print recognition based on two-dimensional Empirical Mode Decomposition and ICA
摘要
Abstract
A novel method based on Two-dimensional Empirical Mode Decomposition(2-D EMD) and Independent Comment Analysis (ICA) is proposed to solve palm print recognition.The adaptive time-frequency localization of 2-D EMD and higher-order statistical independency of ICA II are utilized to extract the palm print features.Firstly, the preprocessed palm print image is decomposed into some Intrinsic Mode Functions(IMFs) by 2-D EMD,and then the palm print feature subspaces of IMF subimages matrix are obtained by a fast fixed-point algorithm for ICA II (Fast ICA II), before which Principal Component Analysis(PCA) is used to decrease the dimensions of input images matrix.Finally,the recognition performance of the integrated method (2-D EMD+ICA II) is tested on the Hong Kong Polytechnic University palm print database.Experimental results show that,compared with ICA II,the proposed method not only can more effectively and accurately extract the palm print features,but also achieves superior Signal-noise-ratio(SNR) of the reconstructed image and higher recognition rate.关键词
二维经验模式分解(2-D EMD)/独立成分分析(ICA)/主成分分析(PCA)/掌纹识别Key words
two-dimensional empirical mode decomposition/ independent comment analysis/ principal component analysis/palm print recognition分类
信息技术与安全科学引用本文复制引用
戴桂平,尚丽..应用二维EMD和独立成分分析的掌纹识别[J].计算机工程与应用,2011,47(19):182-185,4.基金项目
江苏省自然科学基金(No.BK2009131) （No.BK2009131）
河北省科学技术研究与发展计划项目(No.10212152). （No.10212152）
