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DEVELOPING A MULTI MODAL BIOMETRIC FRAMEWORK EMPLOYING THE PRINCIPLE COMPONENT ANALYSIS (PCA) IN CONJUNCTION WITH EDGE DETECTION TECHNIQUE TO ENHANCE THE EFFICACY OF SECURITY FEATURES

Lavaneesh Sharma

95-102

Vol. 4, Jul-Dec, 2016

Date of Submission: 2017-09-07 Date of Acceptance: 2016-10-11 Date of Publication: 2016-10-21

Abstract

Biometrics is the ever growing field of development that has rendered itself useful in various businesses and human identity recognition. The occasional lapse in the security over the recent years has even more necessitated the work in this field. The biometric device is defined as an object that can essentially distinguish one individual from other on the basis of his or her distinctive characteristic trait, that can be behavioural like walking, speaking or aesthetic or physical trait like eyes, fingerprints, tongue prints to name a few. The existent works depend on what are called uni-modal biometric frameworks which rely on just one trait. Here in this paper we are trying to evolve from the existing framework onto a multi-modal bio-metric framework and further delineate the advantages of implementing such a multi-dimensional and integrated platform. Additionally, the works of scholars are reviewed and presented with much more fine-tuning. Lastly, the paper concludes with the implementation of Principal Component Analysis and Edge Detection, as the methodologies for the detection of iris and ears.

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