A Feature Level Extraction based on Iris Recognition for Secure Biometric Authentication | Zendy

Gourav Sachdeva | Zendy; Bikrampal Kaur | Zendy

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A Feature Level Extraction based on Iris Recognition for Secure Biometric Authentication

Author(s) -

Gourav Sachdeva,

Bikrampal Kaur

Publication year - 2015

Publication title -

international journal of computer applications

Language(s) - English

Resource type - Journals

ISSN - 0975-8887

DOI - 10.5120/ijca2015905586

Subject(s) - computer science , biometrics , iris recognition , iris (biosensor) , authentication (law) , feature (linguistics) , artificial intelligence , feature extraction , pattern recognition (psychology) , computer vision , computer security , linguistics , philosophy

recognition is most precise and consistent biometric identification system accessible in the current situation. The demand for an accurate biometric system that provides dependable identification and verification of an individual has increased over the years. A biometric system that provides reliable and accurate identification of an individual is an iris recognition system. This reliability is provided by unique patterns of human iris which differs from person to person up to an extent of identical twins having different iris patterns. This paper has proposed the hybridization of Hough Circular Transform, Scale Invariant Feature Transform and Genetic Algorithm. The genetic algorithm is applied to optimize the features set as obtained by Scale invariant feature transform. KeywordsRecognition, Hough Transformation, SIFT, Genetic Algorithm.

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