| 鼻部毛囊的生物特征识别 |
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| 引用本文： | 宋尚玲,大沼一彦,梅良模,孙丰荣.鼻部毛囊的生物特征识别[J].模式识别与人工智能,2009,22(6). |
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| 作者姓名： | 宋尚玲 大沼一彦 梅良模 孙丰荣 |
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| 作者单位： | 1. 山东大学,信息科学与工程学院,济南,250100
2. 日本千叶大学工学部,千叶,263-8522 |
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| 摘 要： | 应用Hessian矩阵的(特征值,特征向量)参数组的关系提取鼻梁的中脊线,并区分出中脊线左右二边的毛囊识别区域.然后,在Hessian矩阵特征值符号的基础上,加入最大特征值对应的特征向量的方向和梯度方向的关系作为毛囊检测的条件.在103人的数据库中,得到的识别正确率为86.26%.实验结果表明,可以把鼻部毛囊的特征识别用作高效的人体身份认证技术之一.
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| 关 键 词： | 生物特征识别 鼻部毛囊识别 Hessian矩阵 梯度 |
Biometric Recognition Based on Nose Pore Features |
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| SONG Shang-Ling,KAZUHIKO Ohnuma,MEI Liang-Mo,SUN Feng-Rong.Biometric Recognition Based on Nose Pore Features[J].Pattern Recognition and Artificial Intelligence,2009,22(6). |
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| Authors: | SONG Shang-Ling KAZUHIKO Ohnuma MEI Liang-Mo SUN Feng-Rong |
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| Abstract: | Centerline of nose is extracted by Hessian matrix parameters to segment the matched region. Direction of gradient and eigenvector corresponding to the largest eigenvalue are combined to detect nose pore. The proposed method achieves an identification correct rate of 88.07% on a database of 103 persons. The experimental results show that nose pore feature can be used as one of the most efficient biometric features in recognition. |
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| Keywords: | Biometric Recognition Nose Pore Recognition Hessian Matrix Gradient |
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