Abstrato

A Novel Approach for Face Pattern Identification and Illumination

Viniya.P ,Peeroli.H

Extracting facial feature is a key step in facial expression recognition (FER). Inaccurate feature extraction very often results in erroneous categorizing of facial expressions. Especially in robotic application, environmental factors such as illumination variation may cause FER system to extract feature inaccurately. In this paper, we propose a robust facial feature point extraction method to recognize facial expression in various lighting conditions. Before extracting facial features, a face is localized and segmented from a digitized image frame. Face preprocessing stage consists of face normalization and feature region localization steps to extract facial features efficiently. As regions of interest corresponding to relevant features are determined, Gabor jets are applied based on Gabor wavelet transformation to extract the facial points. Gabor jets are more invariable and reliable than gray-level values, which suffer from ambiguity as well as illumination variation while representing local features. The proposed algorithm has two advantages only one face training image is needed to train the classifier by using the facial block features with lower data dimensions, the proposed system is more computational efficiency.The main aim of this proposed work is to improve the accuracy of the face recognition system using the multiple training images.