LOCAL LINE BINARY PATTERN FOR FEATURE EXTRACTION ON PALM VEIN RECOGNITION
Abstract: In recent years,
palm vein recognition has been studied to overcome problems in conventional
systems in biometrics technology (finger print, face, and iris). Those problems
in biometrics includes convenience and performance. However, due to the clarity
of the palm vein image, the veins could not be segmented properly. To overcome
this problem, we propose a palm vein recognition system using Local Line Binary
Pattern (LLBP) method that can extract robust features from the palm vein
images that has unclear veins. LLBP is an advanced method of Local Binary
Pattern (LBP), a texture descriptor based on the gray level comparison of a
neighborhood of pixels. There are four major steps in this paper, Region of
Interest (ROI) detection, image preprocessing, features extraction using LLBP
method, and matching using Fuzzy k-NN classifier. The proposed method was
applied on the CASIA Multi-Spectral Image Database. Experimental results showed
that the proposed method using LLBP has a good performance with recognition
accuracy of 97.3%. In the future, experiments will be conducted to observe which
parameter that could affect processing time and recognition accuracy of LLBP is
needed
Author: Jayanti Yusmah Sari,
Chastine Fatichah, Nanik Suciati
Journal Code: jptkomputergg150015
