Open AccessPalmprint features matching based on KAZE feature detection
Author(s) -
Noor Aldeen A. Khalid,
Muhammad Ahmad,
Thulfiqar H. Mandeel,
Mohd Nazrin Md Isa
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1878/1/012055
Subject(s) - artificial intelligence , computer science , pattern recognition (psychology) , biometrics , feature (linguistics) , process (computing) , computer vision , matching (statistics) , feature extraction , texture (cosmology) , image (mathematics) , mathematics , philosophy , linguistics , statistics , operating system
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.