Person Recognition at Various Distance using Different Biometric Techniques

The human face plays an important role in our social relations, surveying people’s identity. Using the human face as a basic to security, biometric face recognition technology has received significant attention in the past several years due to its potential for a wide variety of applications in both law obligation and non-law obligation. As contrasted with other biometrics systems using fingerprint/Palmprint and iris, face recognition has peculiar advantages because of its non-contact process. Face images can be trapped from a distance without touching the person being identified, and the identification does not desire interacting with the person. Correspondingly, face recognition discharges the crime deterrent purpose because face images that have been recorded and archived can later help identify a person [1]. The aim of this paper is to present self-reliant, comparative study of three most prominent appearance-based face recognition projection methods (PCA, ICA, and LDA) in completely equal working conditions regarding preprocessing and algorithm implementation. Our results show that no particular projection–metric combination is the best across all standard FERET tests and the choice of appropriate projection– Metric combination can only be made for a specific task. Our results are allegorized to other available studies and some discrepancies are pointed out. As an additional bestowal, our new idea of hypothesis testing across all ranks are introduced when comparing performance results.