Histogram of Oriented Lines for Palmprint Recognition

被引:151
作者
Jia, Wei [1 ]
Hu, Rong-Xiang [1 ]
Lei, Ying-Ke [2 ]
Zhao, Yang [3 ]
Gui, Jie [4 ]
机构
[1] Chinese Acad Sci, Inst Nucl Energy Safety Technol, Hefei 230031, Peoples R China
[2] Inst Elect Engn, Hefei 230037, Anhui, Peoples R China
[3] Univ Sci & Technol China, Dept Automat, Hefei 230027, Peoples R China
[4] Chinese Acad Sci, Inst Intelligent Machines, Hefei 230031, Peoples R China
来源
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS | 2014年 / 44卷 / 03期
基金
美国国家科学基金会;
关键词
Biometric; histogram of oriented gradients (HOG); palm line; palmprint recognition; subspace learning; DISCRIMINANT-ANALYSIS; FACE REPRESENTATION; EXTRACTION; ALGORITHM; FEATURES; PCA; LDA;
D O I
10.1109/TSMC.2013.2258010
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Subspace learning methods are very sensitive to the illumination, translation, and rotation variances in image recognition. Thus, they have not obtained promising performance for palmprint recognition so far. In this paper, we propose a new descriptor of palmprint named histogram of oriented lines (HOL), which is a variant of histogram of oriented gradients (HOG). HOL is not very sensitive to changes of illumination, and has the robustness against small transformations because slight translations and rotations make small histogram value changes. Based on HOL, even some simple subspace learning methods can achieve high recognition rates.
引用
收藏
页码:385 / 395
页数:11
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