Palmprint Authentication System Based on Local and Global Feature Fusion Using DOST

Abstract

Palmprint is the region between wrist and fingers. In this paper, a palmprint personal identification system is proposed based on the local and global information fusion. The local and global information is critical for the image observation based on the results of the relationship between physical stimuli and perceptions. The local features of the enhanced palmprint are extracted using discrete orthonormal Stockwell transform. The global feature is obtained by reducing the scale of discrete orthonormal Stockwell transform to infinity. The local and global matching distances of the two palmprint images are fused to get the final matching distance of the proposed scheme. The results show that the fusion of local and global features outperforms the existing works on the available three datasets.

State of the art and perspectives on traditional and emerging biometrics: A survey

“…In 2014, Kumar and Premalatha presented a palmprint personal biometric system based on the local and global information fusion. They used in their experiment three hand image databases, namely, the PolyU palmprint database of 7752 images, COEP palmprint database of 1344 images and IIT Delhi palmprint database of 1610.…”