Design of Real Time Automated Face Recognition System

Abstract

Automatic Face recognition of people has received much attention during the recent years due to its many applications in different fields such as law enforcement, security applications or video indexing. Up to date, there is no technique that provides a robust solution to all situations and different applications that face recognition may encounter. In general, we can make sure that performance of a face recognition system is determined by how to extract feature vector exactly and to classify them into a group accurately. It, therefore, is necessary for us to closely look at the feature extractor and classifier. The system utilizes a combination of techniques in two topics; face detection and recognition. The face detection is performed on live acquired images without any application field in mind. Processes utilized in the system are white balance correction, skin like region segmentation, facial feature extraction and face image extraction on a face candidate. In this project, Support Vector Machines (SVMs) is used for detecting the face. SVMs have been recently proposed as a new classifier for pattern recognition. Then from the human face structure, the four relevant regions such as right eye, left eye, nose, and mouth areas are cropped in a face image. Variations in lighting conditions, pose and expression make face recognition an even more challenging and difficult task.