Development of efficient biometric recognition algorithms based on fingerprint and face /

Development of efficient biometric recognition algorithms based on fingerprint and face /

The reliable verification systems are required to verify and confirm the identity of an individual requesting their service. Secure access to the buildings, laptops, cellular phones, ATM etc. is an example of such applications. In the absence of robust verification systems, these systems are vulnerable to the wiles of an impostor. The traditional ways of authentications are passwords (knowledge ?? based security) and the ID Cards (token ?? based security). These methods can be easily breached due to the chance of stolen, lost or forget. The development and progress of biometrics technology, the fear of stolen, lost or forget can be eliminated. Biometrics refers to the automatic identification (or verification) of an individual (or a claimed identity) by using certain physiological or behavioral traits associated with the person. The biometrics identifies the person based on features vector derived from physiological or behavioural characteristics such as uniqueness, permanence, accessibility, collectability with minimum cost. The physiological biometrics are Fingerprint, Hand Scan, Iris Scan, Facial Scan and Retina Scan etc., and behavioural biometric are Voice, Keystroke, Gait, Signature etc., The physiological biometrics measures the specific part of the structure or shape of a portion of a subjects body. But the behavioural biometric are more concerned with mood and environment. Chapter one presents the introduction to biometrics and its various traits. Further description like structure of the biometric system, different approaches are discussed. Also the design issues in biometric system such as universality, collectability, distinctiveness, permanence, acceptability, uniqueness, performance, circumvention etc., are discussed. Chapter two gives a detailed survey of biometric techniques. It includes the literature survey of fingerprint and face biometric traits and various approaches. In Chapter three, the algorithm of Fingerprint Verification based on Dual Tree Complex Wavelet Transformation (DTCWT) is proposed. The original fingerprint is cropped and resized to apply the DTCWT. The features of Fingerprint are obtained by applying different levels of DTCWT. Performance analysis is discussed with the FRR, FAR and TSR. Chapter four discusses another highly recommended source of authentication such as face recognition. In this chapter, the algorithm of Performance Comparison of Face Recognition using Transform Domain Techniques (PCFTD) is proposed. The face databases L ?? Spacek, JAFFE and NIR are considered. The features of face are generated using wavelet families such as Haar, Symelt and DB1 by considering approximation band only. The face features are also generated using magnitudes of FFTs. The test image features are compared with database features using Euclidian Distance (ED). The performance parameters such as FAR, FRR, TSR and EER computed using wavelet families and FFT. The methodology described in this paper is accurate, simple, fast and better than the existing algorithms. Chapter five presents conclusion and future work.

George Jossy P

Computer Science