Deformable Matching of Hand Shapes for User Verification

Wepresent a method for personal authentication based on deformable matching of hand shapes. Authentication systems are already employed in domains that require some sort of user verification. Unlike previous methods on hand shape-based verification, our method aligns the hand shapes before extracting a feature set. We also base the verification decision on the shape distance which as automatically computed during the alignment stage. The shape distance proves to be a more reliable classijication criterion than the handcrafted feature sets used by previous systems. Our verification system attained a high level of accuracy: 96.5% genuine accept rate us. 2% false accept rate. This performance is further improved by learning an enrollment template shape for each user.

• Type: Conference
• Year: 1999
• Where: ICIP
• Authors: Anil K. Jain, Nicolae Duta
• Keywords: Enrollment Template Shape, Genuine Accept Rate, Hand Shape-based Verification, ICIP 1999, Image Processing