Palmprint recognition using contourlet feature extraction and backpropagation neural network classifier

Abstract EN

Palm print biometrics technology is highest used for human identity verification in most of security application.

In this research the automated biometric system based palmprint biometric technique is used.

The procedure of implementation is divided into two Stages (Enrollment stage and Verification stage).

Each stage is divide into three parts, the first part is pre-processing techniques based on image requirement and cropping to achieve the better image for palmprint.

The second part is feature extraction based on countourlet to obtain a good coaffiention and KL transform to have eign values that reduce the input.

The third part is a classifier using backpropagation neural network to authentication.

The automated biometric system is feasible, easiest to use, and effective in personal authentication using palmprint features with high detection rate (97 % ).