User identification using wavelet features of hand geometry graph
Shanmukhappa A. Angadi, Sanjeevakumar M. Hatture · 2015
Biometrics' based secure identification and personal verification solutions are essential for today's information systems. Hand geometry is one of biometric trait that has been widely employed in biometric identification systems. In this paper an innovative peg-free hand geometry based user identification system using the wavelet energy features of a graph representation of the hand is proposed. The user hand is represented as weighted undirected complete connected graph. The graph characteristics are represented as features vector comprising novel zone-wise wavelet energy features of the weighted adjacency matrix of the graph. User identification is performed using multiclass support vector machine (SVM). The proposed method is evaluated on a database of 144 users, with 10 right hand images of each user from GPDS150 hand database. The experimental results demonstrate a correct identification rate of 97.92% using the SVM classifier.