Palmprint authentication with Zernike moment invariants

Nowadays, palmprint verification is a novel and one of the most reliable biometrically based technology in applications of personal identification and authentication due to its high stability and uniqueness. The principal features of both Chinese character and palmprint are based on the line structure as feature descriptor. This idea prompts us to implement one of the most commonly used Chinese character recognition and reconstruction feature extraction technique, namely Zernike moment invariants (ZMI), in the application of human palmprint authentication. This technique is able to define the statistical and geometrical features containing the line structural information about palmprint. An experimental study about the verification rate of the palmprint authentication system using the Zernike moment invariants has been discussed here. Zernike moment invariant´s orthogonality and translation, rotation and scale invariant properties promote itself as a widely used feature extraction alternative in a broad spectrum of applications in image analysis.