SONG Shang-Ling1, KAZUHIKO Ohnuma2, MEI Liang-Mo1, SUN Feng-Rong1
1.School of Information Science and Engineering, Shandong University, Jinan 250100 2.Department of Medical System Engineering, Faculty of Engineering, Chiba University, Chiba, Japan 263-8522
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.
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): 919-923.
SONG Shang-Ling, KAZUHIKO Ohnuma, MEI Liang-Mo, SUN Feng-Rong. Biometric Recognition Based on Nose Pore Features. , 2009, 22(6): 919-923.
[1] Yan Ping, Bowyer K W. Biometric Recognition Using Three-Dimensional Ear Shape. IEEE Trans on Pattern Analysis and Machine Intelligence, 2007, 29(8): 1297-1308 [2] Wang Changyu, Song Shangling, Sun Fengrong, et al. A Novel Biometrics Technology－Finger-Back Articular Skin Texture Recognition. Acta Automatica Sinica, 2006, 32(3): 360-367 (in Chinese) (王长宇,宋尚玲,孙丰荣,等.一种新的生物特征识别模式——手指背关节皮纹识别.自动化学报, 2006, 32(3): 360-367) [3] Wang Kejun, Duan Shengli, Feng Weixing. A Survey of Face Recognition Using Single Training Sample. Pattern Recognition and Artificial Intelligence, 2008, 21(5): 211-218 (in Chinese) (王科俊,段胜利,冯伟兴.单训练样本人脸识别技术综述.模式识别与人工智能, 2008, 21(5): 211-218) [4] Jain A K, Chen Yi, Demirkus M. Pores and Ridges: High-Resolution Fingerprint Matching Using Level 3 Features. IEEE Trans on Pattern Analysis and Machine Intelligence, 2007, 29(1): 15-27 [5] Jain A K, Chen Yi, Demirkus M. Pores and Ridges: Fingerprint Matching Using Level 3 Features // Proc of the 18th International Conference on Pattern Recognition. Hongkong, China, 2006, Ⅳ: 477-480 [6] West G B, Brown J H, Enquist B J. The Fourth Dimension of Life Fractal Geometry and Allometric Scaling of Organisms. Science, 1999, 284: 1677-1679 [7] Bishop C M. Exact Calculation of the Hessian Matrix for the Multilayer Perceptron. Neural Computation, 1992, 4(4): 494-501 [8] Baert S A M, Niessen W J, Meijering E H W, et al. Medical Image Computing and Computer-Assisted Intervention // Proc of the 3rd International Conference on Medical Image Computing and Computer Assisted Intervention. Pittsburgh, USA, 2000: 11-14 [9] Furst J D, Pizer S M. Marching Optimal-Parameter Ridges: An Algorithm to Extract Shape Loci in 3D Images // Proc of the Conference on Medical Image Computing and Computer-Assisted Intervention. New York, USA, 1998: 780-787 [10] Wang Zhiliang, Jin Jiehua, Liu Jiwei, et al. Realization of Motional Video Surveillance System Based on CDMA and MPEG-4. Computer Engineering, 2006, 32(20): 242-243 (in Chinese) (王志良,金洁华,刘冀伟,等.基于CDMA和MPEG-4的移动视频监控的实现.计算机工程, 2006, 32(20): 242-243) [11] Guan Qiu, Zhang Jianhua, Chen Shengyong, et al. Automatic Segmentation of Micro-Calcification Based on SIFT in Mammograms // Proc of the International Conference on BioMedical Engineering and Informatics. Sanya, China, 2008, Ⅱ: 13-17 [12] Li Guangmin, Tian Jie, Zhao Minchang, et al. Centerline Extraction Based on Hessian Matrix. Journal of Software, 2003, 14(12): 2074-2081 (in Chinese) (李光明,田 捷,赵明昌,等.基于Hessian 矩阵的中心路径提取算法.软件学报, 2003, 14(12): 2074-2081) [13] Lindeber T. Feature Detection with Automatic Scale Selection. International Journal of Computer Vision, 1998, 30(2): 79-116 [14] Kindlmann G, Tricoche X, Westin C F. Delineating White Matter Structure in Diffusion Tensor MRI with Anisotropy Creases. Medical Image Analysis, 2007, 11(5): 492-502 [15] Frangi A F, Niessen W J, Vincken K L, et al. Multiscale Vessel Enhancement Filtering // Barillot C, Haynor D R, Hellier P,et al, eds. Medical Image Computing and Computer-Assisted Intervention. Berlin, Germany: Springer Verlag, 1998: 130-137
2009, Vol. 22 
