PALMPRINT RECOGNITION SYSTEM USING 2-D GABOR AND SVM AS CLASSIFIER
Heena Sherawat, Sumit Dalal · IJITR International Journal of Innovative Technology and Research - IJITR International Journal of Innovative Technology and Research · 2016
From security point of view, Palmprint recognition has become a powerful means in person identification due to rich information in palmprint. Palmprint recognition typically consists of five stages: palmprint acquisition, preprocessing, feature extraction, database and matching. In this project for texture analysis and feature extraction, 2-D Gabor filter is used on segmented images of the sample. For pattern matching, Support Vector Machine (SVM) classifier is being used. The performance of the system is evaluated. Out of the total test images the system has shown 98.15% recognition rate. Thus, the system efficiency of 98.15 percent is obtained. This paper discusses proposed work for palmprint recognition of an individual using segmented parts of palmprint image. The experiment was carried out using MATLAB software image processing toolbox.