Performance of Biometric Palm Print Personal Identification Security System Using Ordinal Measures

Abstract

Personal identification is one of the most important requirements in all e-commerce and criminal detection applications. In this framework, a novel palm print representation method, namely orthogonal line ordinal features, is proposed. The palm print registration, feature extraction, palm print verification and palm print recognition modules are designed to manage the palm prints and the palm print database module is designed to store their palm prints and the person details in the database. The feature extraction module is proposed to extract the ordinal measurements for the palm prints. The verification module is designed to verify the palm print with the personal identification record. The recognition module is proposed to find out the relevant person associated with the palm print image. The proposed palm print recognition scheme uses the intensity and brightness to measure the ordinal measurement. The ordinal measures are estimated for the 4 x 4 regions of the palm print images.