Performance Evaluation of Face Image Recognition Based Voila–Joins with SVM

Abstract

Nowadays face image recognition became an effective research area. It covers a wide range of activities from many aspects of life such as authentication and identification, airport security, inmate tracking, e-commerce and Facebooks automatic tag. The aim of face image recognition is to recognize the face of a person’s depend on the features extracted from their faces. In this paper, two proposed systems were developed, the conventional proposed system of image recognize include many steps to recognize faces. The first step is the preprocessing of images for all training and testing images. The second step is detecting accurate the accuracy of the face by using Viola and Jones algorithm. The third step is features extraction. The proposed system has been implemented by using the (MUCT) datasets. This dataset is considered taking the processing of faces for frontal position. The results show that the proposed system with SVM classifier recognition provides an accuracy total rate of 96.77% for the same test images.