Hand shape based biometric authentication system using radon transform and collaborative representation based classification
Ahana Gangopadhyay, Oindrila Chatterjee, Amitava Chatterjee · 2013
Biometric authentication systems are used to identify individuals based on their unique physiological and behavioral characteristics for access control and security enhancement. In this paper, we propose a novel method of authentication using hand images by collaborative representation based classification (CRC). The contour or hand shape of a query image is extracted by morphological operations and its radon transform is computed along an optimal direction to produce unique one-dimensional feature vector. The feature vector of the query image is then coded over similarly processed training samples from all subjects (or classes) and identified as a member of the class which produces the least reconstruction residual by regularized least square (RLS) instantiation of collaborative representation. Extensive experiments were conducted on a database of 300 images employing two different mathematical operators for dimensionality reduction of acquired feature vector.