生物识别及其关键技术研究
|
摘要
生物识别是指利用人的生理学和行为学特征自动识别其身份的技术。本文主要对生物识别尤其是其关键技术—人脸识别进行了研究。具体内容为：对于人脸识别近年来的研究工作进行了较为系统的介绍；提出了一种肤色滤波模型人脸检测算法，试验结果表明该算法在速度和准确性上具有一定的实用性；提出了一种基于小波分析的人脸识别算法，该算法利用了小波分解的多分辨特性，对人脸特征点进行了准确的定位，提取的人脸特征分辨性优于传统方法提取的人脸特征。
Biometrics is the technology that can identify and verify human individuals with their physiological or behavioural features. In this paper, biometrics has been studied and more attention been paid on face recognition (FR). Based on FR research, a systemic summary which included the FR research in recent years has been presented; and a complexion filter model face detection algorithm that has been proved to be of high performance and great accuracy by a lot of images test is also proposed; in addition to, a face recognition algorithm based on wavelet analysis is proposed, as the mutilresolutional feature of wavelet decompose, the facial feature points has been precisely located, and the facial features which is more differentiable also been extracted.
Biometrics is the technology that can identify and verify human individuals with their physiological or behavioural features. In this paper, biometrics has been studied and more attention been paid on face recognition (FR). Based on FR research, a systemic summary which included the FR research in recent years has been presented; and a complexion filter model face detection algorithm that has been proved to be of high performance and great accuracy by a lot of images test is also proposed; in addition to, a face recognition algorithm based on wavelet analysis is proposed, as the mutilresolutional feature of wavelet decompose, the facial feature points has been precisely located, and the facial features which is more differentiable also been extracted.
引文
[1] Chellappa R, Wilson C L, Sirohey S. Human and machine recognition effaces: A Survey. Proc. IEEE, 1995, 83(5) : 705-740
[2] Samal A, Iyengar A. Automatic recognition and analysis for human faces and facial expressions: A survey. Pattern Recognition, 1992, 25(1) : 65-77
[3] Allen A L, Personal descriptions. London: Butterworth, 1950
[4] Parke F I. Computer generated animation of faces. Proc. ACM ann. Conf, 1972, 1: 451:457
[5] Goldstion R J, Harmon L D, Lesk A B. Man-machine interaction in human face identification. Bell Systech Journal, 1972, 51: 399-427
[6] Harmon L D. The recognition of faces. Science of America. 1973,229: 71-82
[7] Kaya Y, Kobayashi K. A basic study on human recognition. In Frontier of Pattern Recognition, New York: Academic, 1971, 51: 265-289
[8] Anderson J A, Silverstein J W, et al. Distinctive features, categorical perception, and probability learning: some application of a neural model. Psych. Rev., 1977, 84: 413-451
[9] Valentin D, et al. Connectionist model of face processing: A survey. Pattern Recognition, 1994． 27:1209-1230
[10] Daugman J. High-confidence visual recognition of person by a test of statistical independence. IEEE Trans on PAMI, 1993 15(11) : 1148-1161
[11] M Neginr T A Chmielewski Jr, et al. An iris biometric system for public and personal use. IEEE Computer, 2000, 33(2) : 70-75
[12] Lawrence O'Gorman. An overview of fingerprint verification technologies. Information Security Technical Report. 1998, 3(1) : 21-32
[13] Huang C L, Chen C W. Human facial feature extraction for face interpretation and recognition. Pattern Recognition, 1992, 25( 12) : 1435-1444
[14] Turk M. Pentland A. Eigen-faces for recognition, J of Cognitive Neuroscience, 1991, 3 (1) : 71-86
[15] Chen C W, Huang L H. Human Face Recognition from a Single Front View. Int. J of Pattern Recognition.1992, 6(4) 571-593
[16] T. Kanade. Picture Processing System by Computer Complex and Recognition of Human Faces, PH.D, Kyoto University, November, 1973
[17] Zhang Hui, Zhou Hong-Xiang, He Zhen-Ya. Face image feature extraction and recognition based on principal component analysis neural networks. Pattern Recognition and Artificial Intelligence, 1996, 9(1) : 52-57
[18] Samaria F, Young S. HMM-based architecture for face identification. Image and Vision Computing, 1994,12(8) : 537-543
[19] Ming-Hsuan Yang, Narendra Ahuja. Detecting human faces in color images. Proc. IEEE, 1998, 1(8) : 127-130
[20] Rowley H A, Baluja S, Kanada T. Neural-network based face detection. IEEE Computer Society
Conf. on Computer Vision and Pattern Recognition. 1996,209-216
[21] Juell P, Marsh R. A hierarchical neural network for human face detection. Pattern Recognition, 1996, 29(25) : 781-787
[22] Burel G, Carnel D. Detection and location effaces on digital images. Pattern Recognition, 1994, 15:963-967
[23] Vincent J M. Face finding in images. (In:) Application of Neural Network. Murray N F (ed.). 1995,35-70
[24] Lin S H, Kung S Y, Lin L J. Face recognition/detection by probabilistic decision-based neural netvvok. IEEE Trans on Neural Nework. 1997, 8(1) : 114-131
[25] Viennet E, Soulie F F. Multiresolution scene segmentation using MLPs. IJCNN, 1992, 55-59
[26] Kwon Y H, Lobo N V. Face detection using templates. Int. Conf. IEEE, 1994, 1 :764-767
[27] Craw I, Eills H, Lishman J. Automatic extraction of human faces. Pan. Recog. Lett., 1987, 5: 183-187
[28] Akamatsu S, Sasaki T, Fukamachi, et al. Automatic extraction of target images for face identification using sub-space classification method. IEICE Trans on Inf. & Syst. 1993, E76-D(10) : 1190-1198
[29] Ying Dai, et al. Extraction of facial images from a complex from a complex background .using SGLD matrix. IEEE 12th Int. Conf. on Pan. Recog., 1994, 1:137-141
[30] Lee S Y, Hum Y K, Park R H. Recognition of human front faces using knowledge-based feature extraction and neuro-fuzzy and algorithm. Pattern Recognition, 1996,29(11) : 1863-1876
[31] Yang G Z, Huang T S. Human face detection in a complex background. Pattern Recognition, 1995． 28(8) : 1167-1179
[32] Yang G Z, Huang. T S. Human face detection in a scene. IEEE Conf on Computer Vision and Pattern Recognition, 1993, 453-457
[33] Brunelli R. Poggio T. Feature recognition: feature versus templates. IEEE Trans on PAMI. 1993． 15(10) : 1042-1052
[34] L Stringa. Eyes detection for face recognition. Applied Artificial Intelligence, 1993, 7(11) : 365-382
[35] Intrator N, Reisfeld D, Yeshurun Y. Face recognition using a hybrid supervised/unsupervised neural network. Pattern Recognition Letters, 1996, 17:67-76
[36] H Zabrodsky, S Peleg, D Avnir. Symmetry as a continuous feature. IEEE Trans on PAMI, 17: 1154-1166
[37] Y K Ham. L S Young, P R Hong. Fuzzy-based recognition of human faces using the trapezoidal membership function. IEEE Int. Conf. on Fuzzy Systems. 1995, 4: 1799-1806
[38] Yuille A L, et al. Feature extraction from faces using deformable templates. Int. J. Computer Vision, 1992,8(2) : 99-111
[39] Chen C W, Huang C L. Human face recognition from a single front view. Int. J. of Pattern Recognition and Artificial Intelligence,1992, 6:571-593
[40] Chow G, Li X B. Towards a system for automatic facial feature detection. Pattern Recognition, 1993,26(12) : 1739-1755
[41]Kamel M S, Shen H C, et al.Face recognition using perspective invariant features.Pattern Recognition Lett.,1994,15:877-883
[42]Lim K M,Sim Y C,et al. A face recognition system using fuzzy logic and artificial neural network.IEEE Int. Conf. on Fuzzy Ayatems,1992,1063-1069
[43]Ingemar Cox,Joumana Ghosn,et al. Feature-based face recognition using mixture-distance.IEEE Computer Sociely Conf.on Computer Vision and Part.Recog.,1996, 209-216
[44]Kohonen T.Associative Memory:A System Theoretic Approach. Springer,Berlin.1977
[45]A O'Toole, H Abdi, et al.Low-dimensional representation of faces in higher dimensions of the face space,J. Opt. Soc. Am., 1993, 10(3): 405-411
[46]Y Cheng, K Liu,et al. Human face recognition method based on the statistical model of small sample size.SPIE Proc.:Intelligent Robots and Computer Vision X:Alg. and Techn,1991, 1607:85-95
[47]F Samaria.F Fallside.Face identification and feature extraction using hidden markov models.Image Processing:Theory and Applications,1993:295-298
[48]Garrison W Cottrell,et al.Face recognition using unsupervised feature extraction.Proc.Int.Neural Network Conf.,1990 322-325
[49]Michael Fleming, Garrison W Cottrell. Categorization of faces using unsupervised feature extraction.Proc. Int.J.Conf on Neural Networks, 1990, 2:65-70
[50]Lawerence S,Giles C Lee,et al.Face recognition: A convolutional neural-network approach.IEEE Trans Neural Networks,1997, 8(1):114-131
[51]Lin S,Kung S Y,Lin L J.Face recognition/detection by probabilistic decision-based neural network.IEEE 10th Int. Conf. Patt. Recog.,1990, 2:738-741
[52]周杰，卢春雨，张长水，李衍达．人脸自动识别方法综述．电子学报，2000，4(28)：1-5
[53]张翠平，苏光大．人脸识别技术综述．中国图象图形学报2000，5A(11)：885-894
[54]周激流，张毕．人脸识别理论研究进展．计算机辅助设计与图形学学报，1999，11(2)：180-185
[55]彭辉，张长水，朵钢等．基于K-L变换的人脸识别方法．清华大学学报，1997，37(3)：67-70
[56]郭跃飞，杨靖宇．求解广义最佳矢量集的一种迭代算法和人脸识别．计算机学报，2000，23(11)：1189-1195
[57]金忠，杨靖宇，胡钟山．有效最佳鉴别特征的抽取与维数问题．计算机学报，2000，23(1)：108-112
[58]赖剑煌，阮邦志，冯国灿．频谱脸：一种基于小波变化和Fourier变换的人像识别新方法．中国图象图形学报，1999，4(A)，10，811-817
[59]梁路宏，艾海舟，何克忠．基于多模板匹配的单人脸检测．中国图象图形学报，1999，4(A)：825-830
[60]严超，苏光大．人脸特征定位与提取．中国图象图形学报，1998，3A(5)：375-379
[61]张欣，徐彦君，杜立民．彩色图像中主要人脸特征的全自动标定．中国图象图像学报，2000，2(5)：138-143
[62]陆宗骐，梁诚．用Sobel算子细化边缘．中国图象图形学报．2000，5(A)：516-520
[63]周激流，张华，郭晶等．基于先验模板的人脸面部特征提取的研究．计算机辅助设计与图形学学报，2000，5(12)：337-339
[64]王展，黄甫堪，万建伟．基于模板匹配的人脸图像特征提取．计算机辅助设计与图形学学报，2000，5(12)：333-336
[65]杨靖宇，金忠，郭跃飞．人脸图像有效鉴别特征抽取与识别．南京理工大学学报，2000，24(3)：193-198
[66]施可为，傅锡天，蔡安妮等．含人脸的前景在活动图像序列中的分割．北京邮电大学学报，2000，1(23)：66-70
[67]付瑶，刘志镜，谷明坡．基于小波分析的人脸特征提取方法．计算机工程瑟科学[己录用]
[68]刘超远．人脸识别技术与计算机视觉场．上海交大学博士论文．1995
[69]王磊．基于单样本正面人脸图像识别的研究．上海交通大学博士论文．1998
[70]李建平，唐远炎，小波分析方法的应用．重庆大学出版社，1999年版
[71]边肇祺、张学工等．模式识别．清华大学出版社．2000年版
[72]徐建华．图像处理分析．北京科学出版社，1992版
[2] Samal A, Iyengar A. Automatic recognition and analysis for human faces and facial expressions: A survey. Pattern Recognition, 1992, 25(1) : 65-77
[3] Allen A L, Personal descriptions. London: Butterworth, 1950
[4] Parke F I. Computer generated animation of faces. Proc. ACM ann. Conf, 1972, 1: 451:457
[5] Goldstion R J, Harmon L D, Lesk A B. Man-machine interaction in human face identification. Bell Systech Journal, 1972, 51: 399-427
[6] Harmon L D. The recognition of faces. Science of America. 1973,229: 71-82
[7] Kaya Y, Kobayashi K. A basic study on human recognition. In Frontier of Pattern Recognition, New York: Academic, 1971, 51: 265-289
[8] Anderson J A, Silverstein J W, et al. Distinctive features, categorical perception, and probability learning: some application of a neural model. Psych. Rev., 1977, 84: 413-451
[9] Valentin D, et al. Connectionist model of face processing: A survey. Pattern Recognition, 1994． 27:1209-1230
[10] Daugman J. High-confidence visual recognition of person by a test of statistical independence. IEEE Trans on PAMI, 1993 15(11) : 1148-1161
[11] M Neginr T A Chmielewski Jr, et al. An iris biometric system for public and personal use. IEEE Computer, 2000, 33(2) : 70-75
[12] Lawrence O'Gorman. An overview of fingerprint verification technologies. Information Security Technical Report. 1998, 3(1) : 21-32
[13] Huang C L, Chen C W. Human facial feature extraction for face interpretation and recognition. Pattern Recognition, 1992, 25( 12) : 1435-1444
[14] Turk M. Pentland A. Eigen-faces for recognition, J of Cognitive Neuroscience, 1991, 3 (1) : 71-86
[15] Chen C W, Huang L H. Human Face Recognition from a Single Front View. Int. J of Pattern Recognition.1992, 6(4) 571-593
[16] T. Kanade. Picture Processing System by Computer Complex and Recognition of Human Faces, PH.D, Kyoto University, November, 1973
[17] Zhang Hui, Zhou Hong-Xiang, He Zhen-Ya. Face image feature extraction and recognition based on principal component analysis neural networks. Pattern Recognition and Artificial Intelligence, 1996, 9(1) : 52-57
[18] Samaria F, Young S. HMM-based architecture for face identification. Image and Vision Computing, 1994,12(8) : 537-543
[19] Ming-Hsuan Yang, Narendra Ahuja. Detecting human faces in color images. Proc. IEEE, 1998, 1(8) : 127-130
[20] Rowley H A, Baluja S, Kanada T. Neural-network based face detection. IEEE Computer Society
Conf. on Computer Vision and Pattern Recognition. 1996,209-216
[21] Juell P, Marsh R. A hierarchical neural network for human face detection. Pattern Recognition, 1996, 29(25) : 781-787
[22] Burel G, Carnel D. Detection and location effaces on digital images. Pattern Recognition, 1994, 15:963-967
[23] Vincent J M. Face finding in images. (In:) Application of Neural Network. Murray N F (ed.). 1995,35-70
[24] Lin S H, Kung S Y, Lin L J. Face recognition/detection by probabilistic decision-based neural netvvok. IEEE Trans on Neural Nework. 1997, 8(1) : 114-131
[25] Viennet E, Soulie F F. Multiresolution scene segmentation using MLPs. IJCNN, 1992, 55-59
[26] Kwon Y H, Lobo N V. Face detection using templates. Int. Conf. IEEE, 1994, 1 :764-767
[27] Craw I, Eills H, Lishman J. Automatic extraction of human faces. Pan. Recog. Lett., 1987, 5: 183-187
[28] Akamatsu S, Sasaki T, Fukamachi, et al. Automatic extraction of target images for face identification using sub-space classification method. IEICE Trans on Inf. & Syst. 1993, E76-D(10) : 1190-1198
[29] Ying Dai, et al. Extraction of facial images from a complex from a complex background .using SGLD matrix. IEEE 12th Int. Conf. on Pan. Recog., 1994, 1:137-141
[30] Lee S Y, Hum Y K, Park R H. Recognition of human front faces using knowledge-based feature extraction and neuro-fuzzy and algorithm. Pattern Recognition, 1996,29(11) : 1863-1876
[31] Yang G Z, Huang T S. Human face detection in a complex background. Pattern Recognition, 1995． 28(8) : 1167-1179
[32] Yang G Z, Huang. T S. Human face detection in a scene. IEEE Conf on Computer Vision and Pattern Recognition, 1993, 453-457
[33] Brunelli R. Poggio T. Feature recognition: feature versus templates. IEEE Trans on PAMI. 1993． 15(10) : 1042-1052
[34] L Stringa. Eyes detection for face recognition. Applied Artificial Intelligence, 1993, 7(11) : 365-382
[35] Intrator N, Reisfeld D, Yeshurun Y. Face recognition using a hybrid supervised/unsupervised neural network. Pattern Recognition Letters, 1996, 17:67-76
[36] H Zabrodsky, S Peleg, D Avnir. Symmetry as a continuous feature. IEEE Trans on PAMI, 17: 1154-1166
[37] Y K Ham. L S Young, P R Hong. Fuzzy-based recognition of human faces using the trapezoidal membership function. IEEE Int. Conf. on Fuzzy Systems. 1995, 4: 1799-1806
[38] Yuille A L, et al. Feature extraction from faces using deformable templates. Int. J. Computer Vision, 1992,8(2) : 99-111
[39] Chen C W, Huang C L. Human face recognition from a single front view. Int. J. of Pattern Recognition and Artificial Intelligence,1992, 6:571-593
[40] Chow G, Li X B. Towards a system for automatic facial feature detection. Pattern Recognition, 1993,26(12) : 1739-1755
[41]Kamel M S, Shen H C, et al.Face recognition using perspective invariant features.Pattern Recognition Lett.,1994,15:877-883
[42]Lim K M,Sim Y C,et al. A face recognition system using fuzzy logic and artificial neural network.IEEE Int. Conf. on Fuzzy Ayatems,1992,1063-1069
[43]Ingemar Cox,Joumana Ghosn,et al. Feature-based face recognition using mixture-distance.IEEE Computer Sociely Conf.on Computer Vision and Part.Recog.,1996, 209-216
[44]Kohonen T.Associative Memory:A System Theoretic Approach. Springer,Berlin.1977
[45]A O'Toole, H Abdi, et al.Low-dimensional representation of faces in higher dimensions of the face space,J. Opt. Soc. Am., 1993, 10(3): 405-411
[46]Y Cheng, K Liu,et al. Human face recognition method based on the statistical model of small sample size.SPIE Proc.:Intelligent Robots and Computer Vision X:Alg. and Techn,1991, 1607:85-95
[47]F Samaria.F Fallside.Face identification and feature extraction using hidden markov models.Image Processing:Theory and Applications,1993:295-298
[48]Garrison W Cottrell,et al.Face recognition using unsupervised feature extraction.Proc.Int.Neural Network Conf.,1990 322-325
[49]Michael Fleming, Garrison W Cottrell. Categorization of faces using unsupervised feature extraction.Proc. Int.J.Conf on Neural Networks, 1990, 2:65-70
[50]Lawerence S,Giles C Lee,et al.Face recognition: A convolutional neural-network approach.IEEE Trans Neural Networks,1997, 8(1):114-131
[51]Lin S,Kung S Y,Lin L J.Face recognition/detection by probabilistic decision-based neural network.IEEE 10th Int. Conf. Patt. Recog.,1990, 2:738-741
[52]周杰，卢春雨，张长水，李衍达．人脸自动识别方法综述．电子学报，2000，4(28)：1-5
[53]张翠平，苏光大．人脸识别技术综述．中国图象图形学报2000，5A(11)：885-894
[54]周激流，张毕．人脸识别理论研究进展．计算机辅助设计与图形学学报，1999，11(2)：180-185
[55]彭辉，张长水，朵钢等．基于K-L变换的人脸识别方法．清华大学学报，1997，37(3)：67-70
[56]郭跃飞，杨靖宇．求解广义最佳矢量集的一种迭代算法和人脸识别．计算机学报，2000，23(11)：1189-1195
[57]金忠，杨靖宇，胡钟山．有效最佳鉴别特征的抽取与维数问题．计算机学报，2000，23(1)：108-112
[58]赖剑煌，阮邦志，冯国灿．频谱脸：一种基于小波变化和Fourier变换的人像识别新方法．中国图象图形学报，1999，4(A)，10，811-817
[59]梁路宏，艾海舟，何克忠．基于多模板匹配的单人脸检测．中国图象图形学报，1999，4(A)：825-830
[60]严超，苏光大．人脸特征定位与提取．中国图象图形学报，1998，3A(5)：375-379
[61]张欣，徐彦君，杜立民．彩色图像中主要人脸特征的全自动标定．中国图象图像学报，2000，2(5)：138-143
[62]陆宗骐，梁诚．用Sobel算子细化边缘．中国图象图形学报．2000，5(A)：516-520
[63]周激流，张华，郭晶等．基于先验模板的人脸面部特征提取的研究．计算机辅助设计与图形学学报，2000，5(12)：337-339
[64]王展，黄甫堪，万建伟．基于模板匹配的人脸图像特征提取．计算机辅助设计与图形学学报，2000，5(12)：333-336
[65]杨靖宇，金忠，郭跃飞．人脸图像有效鉴别特征抽取与识别．南京理工大学学报，2000，24(3)：193-198
[66]施可为，傅锡天，蔡安妮等．含人脸的前景在活动图像序列中的分割．北京邮电大学学报，2000，1(23)：66-70
[67]付瑶，刘志镜，谷明坡．基于小波分析的人脸特征提取方法．计算机工程瑟科学[己录用]
[68]刘超远．人脸识别技术与计算机视觉场．上海交大学博士论文．1995
[69]王磊．基于单样本正面人脸图像识别的研究．上海交通大学博士论文．1998
[70]李建平，唐远炎，小波分析方法的应用．重庆大学出版社，1999年版
[71]边肇祺、张学工等．模式识别．清华大学出版社．2000年版
[72]徐建华．图像处理分析．北京科学出版社，1992版