Palmprint Recognition Using Fusion of 2D-Gabor and 2D Log-Gabor Features

Palmprint technology is a new branch of biometrics used to identify an individual. Palmprint has rich set of features like palm lines, wrinkles, minutiae points, texture, ridges etc. Several line and texture extraction techniques for palmprint have been extensively studied. This paper presents an intra-modal authentication system based on texture information extracted from the palmprint using the 2D- Gabor and 2D-Log Gabor filters. An individual feature vector is computed for a palmprint using the extracted texture information of each filter type. Performance of the system using two feature types is evaluated individually. Finally, we combine the two feature types using feature level fusion to develop an intra-modal palmprint recognition system. The experiments are evaluated on a standard benchmark database (PolyU Database), and the results shows that significant improvement in terms of recognition accuracy and error rates with the proposed intra-modal recognition system compared to individual representations.