We present BioVXML as an extension of the Voice Extensible Markup Language (VoiceXML). BioVXML is designed for creating modules of biometric verification while maintaining all the features and capabilities of the original VoiceXML. The user verification can now be performed by processing different biometric traits, such as speech or face, and these features gives us an assurance of the user ide...

In this paper we present an effective scheme that preserves the biometric templates more secured. We present a new algorithm called Enhanced Blind Encryption Algorithm for securing biometric templates between client and server and using that for authentication. There are four phases involved in this process namely, enrollment, identification, matching and fusion. During enrollment, biometric tr...

Soft Biometric traits are physical or behavioral human characteristics like skin color, eye color, gait, used by humans to distinguish their peers. However soft biometric characteristics lack in distinctiveness and permanence to identify an individual uniquely and reliably. In this paper a new Gaze Analysis based Soft-biometric (GAS) is investigated. The way an observer looks at a particular su...

This paper proposes an open platform, Biometric Forensic V ideo analyzer (BioFoV), for forensic video analysis and biometric data extraction. The platform’s architecture and implemented modules are described, sample results are shown, and a list of possible enhancements is included. BioFoV is implemented with open software, can be run in multiple software platforms, and is designed to be easily...

Feature vector generation is an important step in biometric authentication. Biometric traits such as fingerprint, palmprint, iris, & finger-knuckle prints are rich in texture. This texture is unique and the feature vector extraction algorithm should correctly represent the texture pattern. In this paper a texture feature extraction methodology is proposed for iris and pamlprints. This method is...

Biometrics based personal identification is regarded as an effective method for automatically recognizing, with a high confidence a person’s identity. A multimodal biometric systems consolidate the evidence presented by multiple biometric sources and typically better recognition performance compare to system based on a single biometric modality. This paper proposes an authentication method for ...

Biometric systems identify a person through physical traits or verify his/her identity through automatic processes. Various systems were used over years including systems like fingerprint, iris, facial images, hand geometry and speaker recognition. For biometric systems successful implementation, it has to address issues like efficiency, accuracy, applicability, robustness and universality. Sin...

This paper presents a multimodal biometric fusion algorithm that supports biometric image quality and case-based context switching approach for selecting appropriate constituent unimodal traits and fusion algorithms. Depending on the quality of input samples, the proposed algorithm intelligently selects appropriate fusion algorithm for optimal performance. Experiments and correlation analysis o...

Biometric systems have a variety of problems such as noisy data, non-universality, spoof attacks and unacceptable error rate. These limitations can be solved by deploying multimodal biometric systems. Multimodal biometric systems utilize two or more individual traits, like face, iris, retina and fingerprint. Multimodal biometric systems improve the recognition accuracy more than uni-modal metho...