Palmprint features matching based on KAZE feature detection
Noor Aldeen A. Khalid, Muhammad Imran Ahmad, Thulfiqar H. Mandeel, Mohd Nazrin Md Isa · Journal of Physics Conference Series · 2021
Abstract Palmprint is very popular biometric recognition system that is able to guarantee high accuracy. It has attracted increasing amount of attention because palmprints are abundant of many characteristics, such as the principle lines, ridges, minute points and textures for the use of images with low resolution. In this paper we propose palmprint feature detection based on KAZE technique. Palmprint texture has many important points for discrimination process. Selecting the best number of point using KAZE is very important for classification process in order to avoid overlapping features in different class. The experimental work has been done using polyU palmprint database in order to evaluate the best number of features.