Biometric identification system based on hand geometry

In this study, an effective biometric method based on hand geometry is presented for biometric identification or verification systems. Feature vectors have been constructed from measurable hand geometrics such as length, width and area of fingers. After low-pass filter input hand images for noise reduction, curvature of the shapes is computed. Then, the valleys of a hand are extracted for identification as feature vector. Twenty-four measurement from a hand shape geometry are used as effective features. Artificial neural network and k-nearest neighbor's algorithm are used as classifiers for Identification. The experimental result reaches to the performance of 95.3% for neural network and 91.2% for k-nearest neighbor's algorithm as correct recognition rates.