Abstract: This study attempts to improve the performance of person verification by finger stripes geometry, which is an efficient, simple, fast, easy to handle and cost effective compared with other biometric human verification technique. Finger stripe geometry is a new biometric type in verification process. This finger stripe based verification consists of two main attributes, feature extraction by image processing and feature learning by ANN (Artificial Neural Network). The Distance Based Nearest Neighbor Algorithm, which shows greater accuracy than NN is also applied here. Using this approach, experimental result provides, Total Success Rate (TSR) is 98.79%, False Acceptance Rate (FAR) is 3.21% and False Rejection Rate (FRR) is 0%. Since the proposed method requires very small computational time, the practical implementation requirement for a large number of person verification is possible.