Personal Authentication based on Angular Geometric Analysis using Finger Back Knuckle Surface

In this paper a new authentication system using Finger Back Knuckle Surface is examined. This paper is intended to propose an effectual method for personal authentication using Finger Back Knuckle Surface. This method take advantage of the less number of features extracted from the Finger Back Knuckle Surface and the Angular geometric analysis is done to mine the distinguishable feature information which is computationally less complex. This is achieved by the determination of convex curves from the finger back knuckle surface. From the recognized feature curves, the subset features like Knuckle Edge points, Knuckle Tip points and Knuckle Base Points are identified. From these features, geometrical structures like scalene triangles were constructed to obtain feature information in terms of angle. This method reduces critical problems that arise due to the extraction of more number of features. Also reduces the computational complexity of the feature extraction and recognition process.