Technique of Face Recognition Based on PCA with Eigen-Face Approach

被引：3

作者：

Tatepamulwar, C. B. ^{[1
]}

Pawar, V. P. ^{[2
]}

Khamitkar, S. D. ^{[1
]}

Fadewar, H. S. ^{[1
]}

机构：

[1] SRTM Univ, Sch Computat Sci, Nanded, India

[2] WALMI, Aurangabad, Maharashtra, India

来源：

COMPUTING, COMMUNICATION AND SIGNAL PROCESSING, ICCASP 2018 | 2019年 / 810卷

关键词：

PCA; Eigen-face; Euclidian distance;

D O I：

10.1007/978-981-13-1513-8_92

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

PCA is utilized in the area of recognition of face, fingerprint, handprint, industrial robotics, and mobile robotics. In the face recognition, research shows that the success rate is not satisfactory for a variant of poses which have rotation gap of more than 30 degrees. If there are lots of variations in lightning, expressions, and pose variation, then PCA results are not up to the mark in the existing algorithm. This problem is arising in mind. The objective of the present paper is to study and propose modified PCA and Eigen-face-based algorithm to improve result with the accuracy of face recognition. In this paper, we focus on the pose variations which have 30 degrees range of pose in image.

引用

页码：907 / 918

页数：12

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