Efficient Face Recognition System Using Hybrid Methodology

Abstract

Recognizing frontal countenance of human beings by a computer system is an interesting and challenging problem. Facial recognition System has emerged as an adorable solution to address many instant needs for identification and the verification of identity claims. It brings together the portend of other biometric systems, which attempt to tie identity to individually distinctive features of the body. Facial feature extraction consists in restraining the most characteristic face countenance such as eyes, nose, and mouth regions within the face images that portray the human faces. In this paper, the two most well-known algorithms i.e. PCA and LBP are introduced and the combination of Local Binary Pattern (LBP) and Principal Component Analysis (PCA) is presented as our proposed approach in which the proposed approach has achieved 93.5% of gain in processing memory. LBP algorithm is used as feature extractor of the face image. LBP is used for their resistance against changing frontal facial expressions. PCA algorithm is used for dimension reduction of the countenance vector. The complete approach has been tested on databases of people under different facial expressions.