Palm Print Classification By Global Features

Abstract

Biometric based personal identification is regarded as an effective method for automatically recognizing, with a high confidence, a person’s identity. Our project gives a new biometric approach to personal identification using palm print technology. In contrast to the existing methods, our palm print based personal identification system employs low-resolution palm print images to achieve effective personal identification. The system consists of three parts: palm print image acquisition, an efficient algorithm for fast palm print recognition and an efficient method for palm print matching. A robust image coordinate system is defined to facilitate image alignment for feature extraction. In addition, a 2D Gabor phase encoding scheme is proposed for palm print feature extraction and representation

Existing System

Proposed System

Architecture