Biometric Identification (Analysis Based on Fingerprints and Faces)

被引:2
|
作者
Mishra, Annapurna [1 ]
Modi, Niharika [1 ]
Panda, Monika [1 ]
机构
[1] Silicon Inst Technol, Dept Elect & Commun Engn, Bhubaneswar, India
关键词
Principal component analysis (PCA); Eigen faces; Local features; Global structures; Euclidean distance; Eigen vector;
D O I
10.1007/978-981-10-6872-0_3
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Biometric system used as a pattern recognition system helps in personal identification by considering specific physiological or behavioral characteristics of an individual. It is divided on the basis of the authentication medium used such as fingerprint, face, and iris. In our paper, we have considered fingerprint and face recognition process. Fingerprint is used as a medium of identification on account of its uniqueness, permanence, universal acceptability, and ease of acquisition. We have proposed a hybrid technique which combines minutia-based technique with the global features to obtain a better recognition rate especially for poor-quality fingerprints. Face being one of the unique, non-intrusive, and non-contact physical traits which can be captured without user cooperation finds its application in the recognition system. Every face is illustrated as a linear combination of singular vectors of set of faces. Hence, we have used principal component analysis (PCA) for the recognition. PCA using Eigen face approach has been used as it reduces the dimensionality of data set, thereby enhancing the computational efficiency.
引用
收藏
页码:27 / 38
页数:12
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