In this project, face recognition algorithms for mobile phone are investigated. Eigenface recognition is applied due to its fast speed. Skin color segmentation by Cr classifier is used for face detection step. Experimental results show 80% accurate rate of face recognition. Keywords-face recognition; face detection; mobile phone; eigenface

Automated face recognition is a well studied problem in computer vision [4]. Its current applications include security (ATM’s, computer logins, secure building entrances), criminal photo (“mug-shot” databases, and human-computer interfaces. One of the more successful techniques of face recognition is principle component analysis, and specifically eigenfaces [1, 2, 3]. In this paper we describe ...

We propose a novel technique for direct visual matching of images for the purposes of face recognition and database search. Speci cally, we argue in favor of a probabilistic measure of similarity, in contrast to simpler methods which are based on standard L2 norms (e.g., template matching) or subspace-restricted norms (e.g., eigenspace matching). The proposed similarity measure is based on a Ba...

In realistic face recognition applications, such as surveillance photo identification, supervised learning algorithms usually fail when only one training sample per subject is available. The lack of training samples and the considerable image variations due to aging, illumination and pose variations, make recognition a challenging task. This letter proposes a development of the traditional eige...

This paper analyzes the merits of two biologically-inspired face recognition models, eigenfaces and graphmatching, in the context of related neurophysiological and psychophysical data. Given the ambiguity of current biological evidence, a more promising direction for future face recognition research is in the development of models that conform more closely to human perception of facial similari...

Face recognition systems have been grabbing high attention from commercial market point of view as well as pattern recognition field. It also stands high in researchers community. Face recognition have been fast growing, challenging and interesting area in real-time applications. A large number of face recognition algorithms have been developed from decades. The present paper refers to differen...

In this paper, an application of Eigenvectors, Eigenfaces, and Covariance vectors with the Principle of Component Analysis will be explained. Face Detection and Recognition is an advancing technology of the Electronic and Electrical Engineering Stream with an integration of Mathematics. The invention, working, advancements of Face Detection and Recognition will be discussed in further detail al...