Face Recogition by Using Gabor Feature Extraction and Neural Networks
Iosr Journals, B.Gopika, K.Srilaxmi, D.Alekhya, B.Bhaskar Rao, B.Rama Mohan · Figshare · 2015
Face recognition is successful by using Gabor filter and neural networks. In this paper we present a biometric system of face detection and recognition in color images. In this 40 different Gabor filters are applied on an image will result 40 different images with different orientations. This paper addresses a novel algorithm in order to detect face features and extract their corresponding geometric points. In those 40 filtered images maximum intensity points are calculated and mark them as fiducially points. To reduce those Fiducially points distance between those points is considered. By using distance formula distances between those reduced points are calculated. Then distances between them are compared with the pre-defined database. If that distance exists that corresponding image will be recognized. The image will be convolved with Gabor filters by multiplying the image by Gabor filters in frequency domain. Face detection and recognition has many applications in a variety of fields such as security systems, video conferencing and identification. The neural Network employed for face recognition is based on the Multi Layer Perception (MLP) architecture.