A Comparative Evaluation of Dotted Raster-Stereography and Feature-Based Techniques for Automated Face Recognition

Abstract

Automated face recognition systems are fast becoming a need for security-related applications. Development of a fool-proof and efficient face recognition system is a challenging domain for researchers. This paper presents comparative evaluation of two candidate techniques for automated face recognition application, viz. dotted Raster-stereography and feature-based system. The relevant performance parameters — accuracy, precision, sensitivity and specificity – measured for the two techniques using IPRL Database of images are reported. The results suggest that dotted Raster-stereography based face recognition system has better accuracy, precision, sensitivity and specificity, and hence is a preferred choice as compared with feature-based system for such sensitive applications where high face recognition accuracy is required. On the other hand, feature-based technique is faster in terms of the training and testing times required. Hence such applications where volume of face recognition work is large and high speed is required with some compromise in accuracy being acceptable then feature-based technique may also be the technique of choice.