Classification of Palmprint Using Principal Line

Abstract

Abstract. In this paper, a new classification scheme for palmprint is proposed. Palmprint is one of the reliable physiological characteristics that can be used to authenticate an individual. Palmprint classification provides an important indexing mechanism in a very large palmprint database. Here, the palmprint database is initially categorized into two groups, right hand group and left hand group. Then, each group is further classified based on the distance traveled by principal line i.e. Heart Line During pre processing, a rectangular Region of Interest (ROI) in which only heart line is present, is extracted. Further, ROI is divided into 6 regions and depending upon the regions in which the heart line traverses the palmprint is classified accordingly. Consequently, our scheme allows 64 categories for each group forming a total number of 128 possible categories. The technique proposed in this paper includes only 15 such categories and it classifies not more than 20.96% of the images into a single category.