Palmprint identification system using shape matching and K-Nearest neighbor algorithm

This paper presents a palmprint identification system based on principle lines. The system is divided into two main subsystems. The first part concerns with palmprint feature extraction using a cascade of consecutive filters to obtain the principle lines. To achieve our proposed system, recognition is provided as the second part to classify principle line image. Firstly, shape histogram is constructed from the extracted image by projections along vertical and horizontal axes. Then, the histogram of query image and the image in database are compared by using cosine similarity measure. Finally, K-Nearest Neighbor is employed to identify a person. The experimental results demonstrate the efficient system yielding high recognition accuracy.