Location of Special Areas on Palmprint

Offline palmprint plays an important role in personal recognition, especially in the area of criminal investigation. Location of Special Areas is significant to offline palmprint classification and orientation field. This paper proposes an efficient algorithm to locate the Special Areas on offline palmprint, which can be divided into two stages. The first stage is to locate the coarse-level Special Areas based on the topology of four adjacent blocks. And then a dynamic clustering algorithm is adopted to segment the orientation fields of the coarse-level Special Areas according to well-suited optimality criteria. The singular points can be detected based on the information of segmented orientation field. Based on the singular points, the final Special Areas are located. In experimental section, the final location results are not only displayed from the aspect of human inspection, the quantitative results are also provided to compare our location results with official ones and our former algorithm.