Biometric Face Recognition Using Mexican Hat Wavelet Kernel Based SVM

被引：0
作者：
Panigrahi, Vikram [1 ]
Biswal, Pradyut Kumar [1 ]
Bastia, Rahul [1 ]
Sahoo, Sibasankar [1 ]
Mishra, Rajesh K. [1 ]
Senapaty, Soumya P. [1 ]
机构：
[1] IIIT Bhubaneswar, Dept Elect, Bhubaneswar, Odisha, India
来源：
2015 IEEE POWER, COMMUNICATION AND INFORMATION TECHNOLOGY CONFERENCE (PCITC-2015) | 2015年
关键词：
Face recognition; PCA; SVM; RBF; Mexican hat wavelet;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Face recognition for biometric purposes has an advantage of being a non-contact process. Various face recognition algorithms has been proposed in the literature. The face recognition system mainly consists of two steps i.e. feature extraction / reduction and classification. One of the most popular tool, Principal Component Analysis (PCA) is used for feature extraction. For classification purpose, various distance classifiers as well as Support Vector Machines (SVM) with various kernels are used. Radial basis function (RBF) kernel in SVM is one of the widely used kernels for this purpose. In this paper, Mexican hat wavelet kernel based SVM is proposed for classification and the comparison of this kernel with other classification methods are examined. The proposed kernel performs better in terms of no. of support vectors compared to RBF kernel and the recognition rate is also high with less number of features.
引用
收藏
页码：895 / 900
页数：6
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