Palmprint Feature Extraction for Human Verification
Publish Year: 1395
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
NPECE01_059
تاریخ نمایه سازی: 6 بهمن 1395
Abstract:
Various features such as principal lines, wrinkles and edges with high acceptability led to palmprint recognition has drawn attention from researchers. Research on feature extraction can be classified into three categories: 1)Line-based, 2)subspace-based, 3)texture-based. In this paper, we consider the palmprint as a texture and apply 2D-Gabor filters and discrete wavelet transform for feature extraction. Features are classified with new approach and using K-Nearest Neighbor, Support Vector Machine, Parzen Window and Fuzzy K-Nearest Neighbor classifiers. In CASIA testing database of 5,502 palmprint samples from 312 palms, we achieved Equal Error Rate of 6.45% 0.37 and Accuracy of 93.55% 0.37 with K-Nearest Neighbor classifier
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Authors
Farzam Kharajinezhadian
Faculty of Biomedical Engineering, Islamic Azad University, Science and Research branch
Saeid Rashidi
Faculty of Biomedical Engineering, Islamic Azad University, Science and Research branch