Bimodal biometric used to authenticate a person is more accurate compared to single biometric trait. In this paper we propose Feature Level Fusion based Bimodal Biometric using Transformation Domine Techniques (FLFBBT). The algorithm uses two physiological traits viz., Fingerprint and Face to identify a person. The Region of Interest (ROI) of fingerprint is obtained using preprocessing. The fea...

Biometrics provides a new dimension of security to modern automated applications since each user will need to prove his identity when attempting an access. However, if a stored biometric template is compromised, then the conventional biometric recognition system becomes vulnerable to privacy invasion. This invasion is a permanent one because the biometric template is not replaceable. In this pa...

This paper presents a combined DWT and LSB based biometric watermarking algorithm that securely embeds a face template in a fingerprint image. The proposed algorithm is robust to geometric and frequency attacks and protects the integrity of both the face template and the fingerprint image. Experimental results performed on a database of 750 face and 750 fingerprint images show that the algorith...

Multimodal biometric can overcome the limitation possessed by single biometric trait and give better classification accuracy. The present work proposes an authentication system with the fingerprint, face and iris multimodal biometric system based on fusion at the feature level. The performances of fingerprint, face and iris recognition can be enhanced using a proposed feature selection method t...

The problem of biometric sensor interoperability has received limited attention in the literature. Most biometric systems operate under the assumption that the data (viz., images) to be compared are obtained using the same sensor and, hence, are restricted in their ability to match or compare biometric data originating from different sensors. Although progress has been made in the development o...

Recent times witnessed much advancement in the field of biometric and multimodal biometric fields. This is typically observed in the area, of security, privacy, and forensics. Even for the best of unimodal biometric systems, it is often not possible to achieve a higher recognition rate. Fusion of matching scores of multiple biometric traits is becoming more and more prevalent and is a very like...

This paper deals with the design of a biometric security system based upon the fingerprint and speech technology. In the first chapter there are the biometric security systems and a concept of an integration of the both technologies introduced. Then the fingerprint technology followed by the speech technology is shortly described. There are discussed some basic principles of each of the technol...

Biometric recognition is automated recognition of individual based on the physiological and behavioral characteristics. Unimodal biometrics are facing problems like noisy data, intra class variation, inter class variation, spoofing attack etc. These limitations can be solved by using multimodal biometrics. Comparing to unimodal, multimodal biometric systems are performing better. A multimodal b...

The deployment of fingerprint recognition systems has always raised concerns related to personal privacy. A fingerprint is permanently associated with an individual and, generally, it cannot be reset if compromised in one application. Given that fingerprints are not a secret, potential misuses besides personal recognition represent privacy threats and may lead to public distrust. Privacy mechan...