IJTEEE
International Journal of Technology Enhancements and Emerging Engineering Research (ISSN 2347-4289)
PREVIOUS PUBLICATIONS



IJTEEE >> Volume 3 - Issue 3, March 2015 Edition



International Journal of Technology Enhancements and Emerging Engineering Research  
International Journal of Technology Enhancements and Emerging Engineering Research

Website: http://www.ijteee.org

ISSN 2347-4289



Person Authentication Using Face And Palm Vein : A Survey Of Recognition And Fusion Techniques

[Full Text]

 

AUTHOR(S)

Preethi M, Dhanashree Vaidya, Dr. S. Kar, Dr. A. M. Sapkal, Dr. Madhuri A. Joshi

 

KEYWORDS

Keywords: Multimodal Biometrics, Face Recognition, Palm Vein, Fusion techniques

 

ABSTRACT

ABSTRACT: Biometric modalities are being used for person recognition for over 40 years. Face has been extensively analyzed as a biometric modality. Palm vein is a permanent and difficult to spoof, modality. For person authentication, palm vein performs better than face. Fusion of both the modalities yield recognition rates that are higher than those obtained individually. This paper presents a survey of various techniques used for authentication of a person, based on face, palm vein and fusion techniques involving both modalities. It discusses some iconic techniques, their limitations and how those were overcome in different ways in new techniques. It concludes with major problems to be analyzed in future and open areas of research.

 

REFERENCES

[1] C. Nastar, M. Mitschke, ‘Real time face recognition using feature combination’, Third IEEE International Conference on Automatic Face and Gesture Recognition. Nara, Japan, 1998, pp. 312-317.

[2] S. Gong, S. J. McKenna, and A. Psarrou., ‘Dynamic Vision: From Images to Face Recognition’ Imperial College Press (World Scientific Publishing Company), 2000.

[3] T. Jebara, ‘3D Pose Estimation and Normalization for Face Recognition’, Center for Intelligent Machines, McGill University, Under-graduate Thesis May, 1996.

[4] D. Blackburn, J. Bone, and P. J. Phillips, ‘Face recognition vendor test 2000’, Defense Advanced Research Projects Agency, Arlington, VA, Technical report A269514, February 16, 2001.

[5] P. J. Phillips, H. Wechsler, J.Huang, and P. J. Rauss, ‘The FERET database and evaluation procedure for face-recognition algorithm’, Image and Vision Computing, Vol.16, 1998, pp.295-306.

[6] P. J. Phillips, P. Grother, R. J. Micheals, D. M. Blackburn, E. Tabassi, and J. M. Bone, ‘Face Recognition Vendor Test (FRVT 2002)’, National Institute of Standards and Technology, Evaluation report IR 6965, March, 2003.

[7] K. Messer, J. Kittler, M. Sadeghi et al, ‘Face Authentication Test on the BANCA Database’, 17th International Conference on Pattern Recognition, Vol.4. Cambridge, UK, 2004, pp.523-532.

[8] X. Q. Ding and C. Fang, ‘Discussions on some problems in face recognition’, Advances In Biometric Person Authentication, Proceedings, Vol. 3338, Lecture Notes In Computer Science: Springer Berlin / Heidelberg, 2004, pp.47-56.

[9] J. Yang, X. Chen, and W. Kunz, ‘A PDA-based face recognition system’, Proceedings of sixth IEEE Workshop on Applications of Computer Vision. Orlando, Florida, 2002, pp.19-23.

[10] Kang-Seo Park, Rae-Hong Park, and Young-Gon Kim, ‘Face Detection Using the 3×3 Block Rank Patterns of Gradient Magnitude Images and a Geometrical Face Model’, 2011 IEEE International Conference on Consumer Electronics (ICCE), pp. 793-794.

[11] Rashmi Gupta, Anil Kishore Saxena, ‘Survey of Advanced Face Detection Techniques in Image Processing’, International Journal of Computer Science and Management Research, Vol 1 Issue 2 September 2012, ISSN 2278-733X, pp. 156-164

[12] Padma Polash Paul and Marina Gavrilova, ‘PCA Based Geometric Modeling for Automatic Face Detection’, International Conference on Computational Science and Its Applications, 2011, pp. 33-38.

[13] Anima Majumder, L. Behera and Venkatesh K Subramanian, ‘Automatic and Robust Detection of Facial Features in Frontal Face Images’, 13th International Conference on Modelling and Simulation, UKSim, 2011, pp. 331-336.

[14] Daesik Jang, Gregor Miller, Sid Fels, and Steve Oldridge, ‘User Oriented Language Model for Face Detection’, ISSN- 978-1-61284-035-2, IEEE 2010, pp. 21- 26.

[15] Jing-Ming Guo, Chen-Chi Lin, Min-Feng Wu, Che-Hao Chang, and Hua Lee, ‘Face Detection Using Probability- Based Face Mask Pre-filtering and Pixel-Based Hierarchical-Feature Adaboosting’, EEE SIGNAL ROCESSING LETTERS, VOL. 18, NO. 8, AUGUST 2011, pp. 447-450.

[16] R. Brunelli and T. Poggio, ‘Face recognition: features versus templates’, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.15, 1993, pp.1042- 1052.

[17] M. A. Grudin, ‘On internal representations in face recognition systems’, Pattern Recognition, Vol.33, 2000, pp.1161-1177.

[18] B. Heisele, P. Ho, J. Wu, and T. Poggio, ‘Face recognition: component-based versus global approaches’, Computer Vision and Image Understanding, Vol.91, 2003, pp.6-21.

[19] Rabia Jafri, Hamid R. Arabnia, ‘A Survey of Face Recognition Techniques’, Journal of Information Processing Systems, Vol.5, No.2, June 2009, pp. 41-67.

[20] T. Kanade, ‘Picture Processing System by Computer Complex and Recognition of Human Faces’ Kyoto University, Japan, PhD. Thesis 1973.

[21] Yuille, D. Cohen, and P. Hallinan, ‘Feature extraction from faces using deformable templates’, IEEE Computer Society Conference on Computer Vision and Tem-plates, San Diego, CA, USA, 1989, pp.104-109.

[22] N. Roeder and X. Li, ‘Experiments in analyzing the accuracy of facial feature detection’, Vision Interface '95, 1995, pp.8-16.

[23] C. Colombo, A. D. Bimbo, and S. D. Magistris, ‘Human-computer interaction based on eye movement tracking’, Computer Architectures for Machine Perception, 1995, pp.258-263.

[24] M. Nixon, ‘Eye spacing measurement for facial recognition’, SPIE Proceedings, 1985, pp.279-285.

[25] D. Reisfeld, ‘Generalized symmetry transforms: attentional mechanisms and face recognition’ Tel- Aviv University, PhD. Thesis, technical report 1994.

[26] H. P. Graf, T. Chen, E. Petajan, and E. Cosatto, ‘Locating faces and facial parts’, International Workshop on Automatic Face- and Gesture- Recognition, 1995, pp.41-46.

[27] Craw, D. Tock, and A. Bennett, ‘Finding face features’, Second European Conference on Computer Vision, 1992, pp.92-96.

[28] S. Lawrence, C. L. Giles, A. C. Tsoi, and A. D. Back, ‘Face Recognition: A Convolutional Neural Network Approach’, IEEE Transactions on Neural Networks, Special Issue on Neural Networks and Pattern Recognition, 1997, pp.1-24.

[29] L. Wiskott, J.-M. Fellous, N. Krüger, and C. von der Malsburg, ‘Face Recognition by Elastic Bunch Graph Matching’, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.19, 1997, pp.775- 779.

[30] M. Lades, J. C. Vorbrüggen, J. Buhmann, J. Lange, C. v. d. Malsburg, R. P. Würtz, and W. Konen, ‘Distortion invariant object recognition in the dynamic link architecture’, IEEE Trans. Computers, Vol.42, 1993, pp.300-311.

[31] G. Sukthankar, ‘Face recognition: a critical look at biologically-inspired approaches’, Carnegie Mellon University, Pittsburgh, PA, Technical Report: CMURITR- 00-04 2000.

[32] P. Campadelli and R. Lanzarotti, ‘A Face Recognition System Based on Local Feature Characterization’, Advanced Studies in Biometrics, Vol.3161, Lecture Notes in Computer Science, M. Tistarelli, J. Bigun, and E. Grosso, Eds. Berlin: Springer, 2005, pp.147- 152.

[33] G. J. Kaufman and K. J. Breeding, ‘Automatic recognition of human faces from profile silhouettes’ IEEE Transactions On Systems Man And Cybernetics, SMC, Vol.6, 1976, pp.113-121.

[34] L. D. Harmon, M. K. Khan, R. LAsch, and P. F. Raming, ‘Machine Identification of human faces’ Pattern Recognition, Vol.13, 1981, pp.97-110.

[35] Z. Liposcak and S. Loncaric, ‘A scale-space approach to face recognition from profiles’, Proceedings of the 8th International Conference on Computer Analysis of Images and Patterns, Vol. 1689, Lecture Notes In Computer Science. London, UK: Springer- Verlag, 1999, pp.243-250.

[36] R. Cendrillon and B. C. Lowell, ‘Real-Time Face Recognition using Eigenfaces’, Proceedings of the SPIE International Conference on Visual Communications and Image Processing, Vol.4067, 2000, pp.269-276.

[37] J. Cox, J. Ghosn, and P. N. Yianilos, ‘Feature based face recognition using mixture-distance’, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 1996, pp.209-216.

[38] L. Sirovich and M. Kirby, ‘Low-dimensional Procedure for the Characterization of Human Faces’, Journal of the Optical Society of America A: Optics, Image Science, and Vision, Vol.4, 1987, pp.519-524.

[39] K. Jain and R. C. Dubes, ‘Algorithms for Clustering Data’, New Jersey: Prentice-Hall, 1988.

[40] Fukunaga, ‘Introduction to Statistical Pattern Recognition’, second ed. Boston, MA: Academic Press, 1990.

[41] M. Turk and A. Pentland, ‘Face Recognition Using Eigen faces’ Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 1991, pp.586-591.

[42] M. Turk and A. Pentland, ‘Eigen faces For Recognition’, Journal Of Cognitive Neuroscience, Vol.3, pp.71-86, 1991.

[43] Pentland, B. Moghaddam, and T. Starner, ‘View based and modular eigenspaces for face recognition’, IEEE Conference on Computer Vision and Pattern Recognition, 1994, pp.84-90.

[44] P. N. Belhumeur, J. P. Hespanha, and D. J. Kriegman, ‘Eigen faces vs. Fisher faces: Recognition using class specific linear projection’ IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.19, 1997, pp.711-720.

[45] Y. Moses, Y. Adini, and S. Ullman, ‘Face recognition: the problem of compensating for changes in illumination direction’, European Conf. Computer Vision, 1994, pp.286-296.

[46] R. A. Fisher, ‘The use of multiple measures in taxonomic problems’, Annals of Eugenics, Vol.7, 1936, pp. 179-188.

[47] M. Martínez and A. C. Kak, ‘PCA versus LDA’, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.23, 2001, pp.228-233.

[48] M. A. O. Vasilescu and D. Terzopoulos, ‘Multilinear Subspace Analysis of Image Ensembles’, Proc. IEEE Int’l Conf. on Computer Vision and Pattern Recognition, 2003, pp.93-99.

[49] Q. Yang and X. Q. Ding, ‘Symmetrical Principal Component Analysis and Its Application in Face Recognition’, Chinese Journal of Computers, Vol.26, 2003, pp.1146–1151.

[50] Yang and D. Zhang, ‘Two-Dimensional PCA: A New Approach to Appearance-Based Face Representation and Recognition’, IEEE Trans. Pattern Analysis and Machine Intelligence, Vol.28, pp.131- 137, 2004.

[51] Meng and W. Zhang, ‘Volume measure in 2D PCA based face recognition’, Pattern Recognition Letters, Vol.28, 2007, pp.1203-1208.

[52] G. D. C. Cavalcanti and E. C. B. C. Filho, ‘Eigen bands Fusion for Frontal Face Recognition’, Proceedings of IEEE International Conference on Image Processing, Vol.1, 2003, pp.665–668.

[53] R. Tan and S. C. Chen, ‘Adaptively weighted subpattern PCA for face recognition’, Neurocomputing, Vol.64, 2005, pp.505-511.

[54] P. Kumar, S. Das, and V. Kamakoti, ‘Face recognition using weighted modular principle component analysis’, Neural Information Processing, Vol.3316, Lecture Notes In Computer Science: Springer Berlin / Heidelberg, 2004, pp.362-367.

[55] V. D. M. Nhat and S. Lee, ‘An Improvement on PCA Algorithm for Face Recognition’, Advances in Neural Networks - ISNN 2005, Vol.3498, Lecture Notes in Computer Science. Chongqing: Springer, 2005, pp.1016-1021.

[56] N. Sun, H.-x.Wang, Z.-h.Ji, C.-r. Zou, L. Zhao, ‘An efficient algorithm for Kernel two-dimensional principal component analysis’, Neural Computing & Applications, Vol.17, 2008, pp.59-64.

[57] D. Zhang, Z.-H. Zhoua,S. Chen, ‘Diagonal principal component analysis for face recognition’, Pattern Recognition, Vol.39, 2006, pp.140-142.

[58] H. Yu and J. Yang, ‘A Direct LDA Algorithm for High-dimensional Data with Application to Face Recognition’, Pattern Recognition, Vol.34, 2001, pp.2067- 2070.

[59] F. Song, D. Zhang, J. Wang, H. Liu, and Q. Tao, "A parameterized direct LDA and its application to face recognition’, Neuro-computing, Vol.71, 2007, pp.191-196.

[60] D. Zhou and X. Yang, ‘Face Recognition Using Direct-Weighted LDA’, 8th Pacific Rim International Conference on Artificial Intelligence. Auckland, New Zealand, 2004, pp.760-768.

[61] Chen, H. Liao, M. Ko, L. J., and G. Yu, ‘A New LDA-based Face Recognition System Which Can Solve the Small Samples Size Problem’, Journal of Pattern Recognition, Vol.33, 2000, pp.1713–1726.

[62] W. Liu, Y. Wang, S. Z. Li, and T. Tan, ‘Null Space Approach of Fisher Discriminant Analysis for Face Recognition’, Biometric Authentication, Vol.3087, Lecture Notes in Computer Science: Springer Berlin / Heidel-berg, 2004, pp.32-44.

[63] X. Wang and X. Tang, ‘Dual-space Linear Discriminant Analysis for Face Recognition’, Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition, 2004, pp.564–569.

[64] Loog, R. P. W. Duin, and R. Haeb-Umbach, ‘Multiclass Linear Dimension Reduction by Weighted Pairwise Fisher Criteria’, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.23, 2001, pp.762-766.

[65] J. H. Friedman, ‘Regularized Discriminant Analysis’, Journal of the American Statistical Association, Vol.84, 1989, pp.165-175.

[66] P. Howland and H. Park, ‘Generalized Discriminant Analysis Using the Generalized Singular Value Decomposition’, IEEE Trans. On Pattern Analysis and Machine Intelligence, Vol.260, 2004, pp.995–1006.

[67] J. P. Ye, R. Janardan, C. H. Park, and H. Park, ‘An Optimization Criterion for Generalized Discriminant Analysis on Undersampled Problems’, IEEE Trans. On Pattern Analysis and Machine Intelligence, Vol.26, 2004, pp.982–994.

[68] J. W. Lu, K. N. Plataniotis, and A. N. Venetsanopoulos, ‘Face Recognition Using LDA-based Algorithms’, IEEE Trans. On Neural Networks, Vol.14, 2003, pp.195- 200.

[69] J. W. Lu, K. N. Plataniotis, and A. N. Venetsanopoulos, ‘Boosting Linear Discriminant Analysis for Face Recognition’, Proceedings of IEEE International Conference on Image Processing, Vol.1, 2003, pp.657-660.

[70] Q. Yang and X. Q. Ding, ‘Discriminant Local Feature Analysis of Facial Images’, IEEE International Conference on Image Processing, Vol.2, 2003, pp.863-866.

[71] Q. Liu, H. Lu, and S. Ma, ‘Improving Kernel Fisher Discriminant Analysis for Face Recognition’, IEEE Transactions on Circuits and Systems for VideoTechnology, Vol.14, 2004, pp.42-49.

[72] B. Schölkopf, ‘Nonlinear Component Analysis as a Kernel Eigen value Problem’, Neural Computation, Vol.10, 1998, pp.1299-1319.

[73] Q. Liu, X. Tang, H. Lu, and S. Ma, ‘Kernel Scatter- Difference Based Discriminant Analysis for Face Recognition’, Proc. IEEE International Conference on Pattern Recogni-tion, 2004, pp.419-422.

[74] Li and B. Yuan, ‘2D-LDA: A statistical linear discriminant analysis for image matrix’, Pattern Recognition Letters, 2005, Vol.26, pp.527-532.

[75] H. L. Xiong, M. N. S. Swamy, and M. O. Ahmad, ‘Two-dimensional FLD for face recognition’, Pattern Recognition, 2005, Vol.38, pp.1121-1124.

[76] X. Y. Jing, Y. Y. Tang, and D. Zhang, ‘A Fourier- LDA approach for image recognition’, Pattern Recognition, 2005, Vol.38, pp.453-457.

[77] Y. W. Pang, L. Zhang, M. J. Li, Z. K. Liu, and W. Y. Ma, ‘A novel Gabor-LDA based face recognition method’, Advances In Multimedia Information Processing - Pcm 2004, Pt 1, Proceedings, vol. 3331, Lecture Notes In Computer Science, 2004, pp.352- 358.

[78] V. D. M. Nhat and S. Lee, ‘Block LDA for Face Recognition’, Computational Intelligence and Bioinspired Systems, Vol.3512, Lecture Notes in Computer Science: Springer Berlin / Heidelberg, 2005, pp.899-905.

[79] D. Zhou and X. Yang, ‘Face Recognition Using Enhanced Fisher Linear Discriminant Model with Facial Combined Feature’, PRICAI 2004: Trends in Artificial Intelligence, Vol.3157, Lecture Notes in Computer Science: Springer Berlin / Heidelberg, 2004, pp.769-777.

[80] W. C. Zhang, S. G. Shan, W. Gao, Y. Z. Chang, and B. Cao, ‘Component-based cascade linear discriminant analysis for face recognition’, Advances In Biometric Person Authentication, Proceedings, Vol.3338, Lecture Notes In Computer Science, 2004, pp.288-295.

[81] H. Zhao and P. C. Yuen, ‘Incremental Linear Discriminant Analysis for Face Recognition’, IEEE Transactions on Systems, Man & Cybernetics: Part B, Vol.38, 2008, pp.210-221.

[82] J. Li, S. Zhou, and C. Shekhar, ‘A Comparison of Subspace Analysis for Face Recognition’, Proc. IEEE Int’l Conf. on Acoustics, Speech, and Signal Processing, 2003, pp.121–124.

[83] C. Liu and H. Wechsler, ‘Evolutionary Pursuit and Its Application to Face Recognition’, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.22, 2000, pp.570-582.

[84] H.-L. Huang, H.-M. Chen, S.-J. Ho, and S.-Y. Ho, ‘Advanced Evolutionary Pursuit for Face Recognition’, Journal of VLSI Signal Processing-Systems for Signal, Image, and Video Technology, 2006.

[85] J. Lu, K. N. Plataniotis, A. N. Venetsanopoulos, and S. Z. Li, ‘Ensemble-based Discriminant Learning with Boosting for Face Recognition’, IEEE Transactions on Neural Networks, Vol.17, 2006, pp.166-178.

[86] J. Lu and K. N. Plataniotis, ‘Boosting face recognition on a large-scale database’, Proceedings of IEEE International Conference on Image Processing, Vol.2. Rochester, NY, 2002, pp.109-112.

[87] Y. Freund and R. E. Schapire, ‘A decision-theoretic generalization of on-line learning and an application to boosting’, Journal of Computer and System Sciences, Vol.55, 1997, pp.119-139.

[88] R. E. Schapire, ‘The boosting approach to machine learning: An overview’ MSRI Workshop Nonlinear Estimation and Classification, 2002, pp.149-172.

[89] Yongkang Wong, Mehrtash T. Harandi, Conrad Sanderson, ‘On robust face recognition via sparse coding’, IET Biometrics, 10.1049/iet-bmt.2013.0033, 14 pp.

[90] S. Tiwari S.K. Singh, ‘Face recognition for newborns’, IET Biometrics, Vol. 1, Iss. 4, 2012, pp. 200–208

[91] S.-M. Huang J.-F. Yang, ‘Subface hidden Markov models coupled with a universal occlusion model for partially occluded face recognition’, IET Biometrics, Vol. 1, Iss. 3, 2012, pp. 149–159

[92] J. Ma¨a¨ tta¨ A. Hadid M. Pietika¨ inen, ‘Face spoofing detection from single images using texture and local shape analysis’, IET Biometrics, Vol. 1, Iss. 1, 2012, pp. 3–10

[93] C. Beumier and M. Acheroy, ‘Automatic Face Recognition’, Proceedings symposium IMAGING. Eindhoven, The Netherlands, 2000, pp.77-89.

[94] Shigeru Sasaki, and Akira Wakabayashi, ‘Business Expansion of Palm Vein Pattern Authentication Technology’, Fujitsu Sci. Tech. J., 41, 3, 2005, pp. 341-347.

[95] ‘Palm Vein Pattern Authentication Technology’, Fujitsu white paper, 2005.

[96] Hao luo,Fa-Xin Yu,Jeng-Shyang Pan,Shu-Chuan Chu and Pei-Wei Tsai, ‘A Survey of Vein Recognition Techniques’, Information technology Journal,vol.9,no 6,2010,pp.1142-1149.

[97] Bhudev Sharma, ‘Palm Vein Technology’, Sardar Vallabhbhai National Institute of Technology, December-2010.

[98] Ishani Sarkar, Farkhod Alisherov, Tai-hoon Kim, and Debnath Bhattacharyya, ‘Palm Vein Authentication System: A Review’, International Journal of Control and Automation, Vol. 3, No. 1, March, 2010, pp.27-34.

[99] Hassan Soliman, Abdelnasser Saber Mohamed and Ahmed Atwan, ‘Feature Level Fusion of Palm Veins and Signature Biometrics’, International Journal of Video & Image Processing and Network Security IJVIPNS-IJENS Vol: 12 No: 01, 2012, pp.28-39.

[100] Debnath Bhattacharyya , Poulami Das, Tai-hoon Kim and Samir Kumar Bandyopadhyay, ‘Vascular Pattern Analysis towards Pervasive Palm Vein Authentication’ , Journal of Universal Computer Science, vol. 15, no. 5,2009, pp.1081-1089.

[101] Yingbo Zhou and Ajay Kumar, ‘Human Identifi-cation Using Palm-Vein Images’ , IEEE transactions on information forensics and security, vol. 6, no. 4, December 2011, pp.1259- 1247.

[102] Y.-B. Zhang, Q. Li, J. You, and P. Bhattacharya, ‘Palm vein extraction and matching for personal authentication’, in Lecture Notes in Computer Science. Springer, 2007, pp. 154–164.

[103] Qiang Li, Yan'an Zeng , Xiaojun Peng and Kuntao Yang, ‘Curvelet-based palm vein biometric recognition’, CHINESE OPTICS LETTERS / Vol. 8, No. 6, June 2010, pp.577- 579.

[104] Pierre-Olivier Ladoux, Christophe Rosenberger and Bernadette Dorizzi , ‘Palm Vein Verification System based on SIFT matching’, Third International Conference on Advances in Biometrics, June 2009, pp. 1290-1298.

[105] Yingbo Zhou and Ajay Kumar, ‘Contactless Palm Vein Identification using Multiple Representations’, 4th IEEE international conference on biometrics: Theory applications and systems (BTAS), September 2010, pp. 1-6.

[106] David Zhang, Zhenhua Guo, Guangming Lu, Lei Zhang, Yahui Liu, Wangmeng Zuo, ‘Online joint palmprint and palmvein verification’ , Expert Systems with Applications, No.11, 2010, pp. 2621-2631.

[107] M.Deepamalar and M.Madheswaran, ‘An En-hanced Palm Vein Recognition System Using Multi-level Fusion of Multimodal Features and Adaptive Resonance Theory’, International Journal of Computer Applications (0975 - 8887) vol. 1 – No. 20, 2010, pp.95-101.

[108] D. Zhang, Z. Guo, G. Lu, L. Zhang, and W. Zuo, ‘An online system of multispectral palmprint verification’, IEEE Trans. Instrum. Meas., vol. 59, no. 2, Feb. 2010, pp. 480–490.

[109] J.-G.Wang,W.-Y. Yau, A. Suwandy, and E. Sung, ‘Person recognition by fusing palmprint and palm vein images based on Laplacian palm representation’, Pattern Recognit., vol. 41, Oct. 2007, pp. 1514– 1527.

[110] Y. Hao, Z. Sun, T. Tan, and C. Ren, ‘Multispectral palm image fusion for accurate contact-free palmprint recognition’, International Conference on Image Processing, 2008, pp. 281–284.

[111] Leila Mirmohamadsadeghi, Andrzej Drygajlo, ‘Palm vein recognition with local texture pattern’, IET Biometrics, 10.1049/iet-bmt.2013.0041, 9 pp.

[112] Yiding Wang, Ke Zhang, Lik-Kwan Shark, ‘Personal identification based on multiple keypoint sets of dorsal hand vein images’, IET Biometrics, doi: 10.1049/iet-bmt.2013.0042, pp. 1–12

[113] D. Hartung, M. Aastrup Olsen, H. Xu, H. Thanh Nguyen1 C. Busch, ‘Comprehensive analysis of spectral minutiae for vein pattern recognition’, IET Biometrics, Vol. 1, Iss. 1, 2012, pp. 25–36

[114] Ross and A. Jain, ‘Information Fusion in Biometrics’, Pattern Recognition Letters, vol. 24, pp. 2115-2125, 2003.

[115] K. Jain, K. Nandakumar and A. Ross, ‘Score Normalization in Multimodal Biometric Systems’, Pattern Recognition, Vol. 38, 2005.

[116] Slobodan Ribarić and Ivan Fratrić, ‘A Matching-Score Normalization Technique for Multimodal Biometric Systems’, Proc. 3rd COST 275 Workshop: Biometrics on the Internet, Hatfield, UK, October 2005, pp. 27-28.

[117] Slobodan Ribarić and Ivan Fratrić, ‘Experimental Evaluation of Matching-Score Normalization Techniques on Different Multimodal Biometric Systems’, Proc. 13th IEEE Mediterranean Electrotechnical Con-ference, Malaga, Spain, May 2006, pp.16-19.

[118] Dhanashree Vaidya, Sheetal Pawar, Madhuri A Joshi, S. Kar, A.M. Sapkal, ‘Feature-level Fusion of Palm Print and Palm Vein for Person Authentication Based on Entropy Technique’, IJECT Vol. 5, Issue spl-1, Jan - March 2014, pp. 53- 57.

[119] S.F.Bahgat, S. Ghoniemy, M. Alotaibi, ‘Proposed Multi-Modal Palm Veins-Face Biometric Authentication’, International Journal of Advanced Computer Science and Applica-tions, Vol. 4, No. 6, 2013, pp. 92-96.

[120] Q. Yang and X. Tang, ‘Recent Advances in Subspace Analysis for Face Recognition’, SINOBIOMETRICS, 2004, pp.275-287.

[121] Torres, ‘Is there any hope for face recognition?’, Proc. of the 5th International Workshop on Image Analysis for Multimedia Interactive Services (WIAMIS 2004). Lisboa, Portugal, 2004.

[122] Mona A. Ahmed, Hala M. Ebied, El-Sayed M. El-Horbaty, Abdel-Badeeh M. Salem, ‘Analysis of Palm Vein Pattern Recognition Algorithms and Systems’, Analysis of Palm Vein Pattern Recognition Algorithms and Systems, Volume 1, No.1, June – July 2013, ISSN 2321-9017.

[123] Kresimir Delac,Mislav Grgic, “A Survey Of Bio-metric Recognition Methods”, 46th International SyrnPoSium Electronics in Marine. ELMAR-2004. 16-18 June 2004. Zadar. Croatia

[124] Anil K. Jain, Patrick Flynn and Arun A. Ross, “Handbook of Biometrics”.

[125] Madhavi Gudavalli, Dr.S.Viswanadha Raju,Dr. A. Vinaya Babu, Dr.D.Srinivasa Kumar, "Multimodal Biometrics - Sources , Architecture & Fusion Techniques: An Overview", IEEE Transactions 978-0-7695-4696-4/12 2012

[126] Faundez-Zanuy, "Data fusion in biometrics," IEEE Aerospace and Electronic Systems Magazine, vol. 20, pp. 34-38, 2005.

[127] K. Jain and A. Ross, "Multibiometric Systems," Interagency Information Exchange on Biometrics, 2003.

[128] Sheetal Chaudhary , Rajender Nath, “A Multi-modal Biometric Recognition System Based on Fusion of Palmprint, Fingerprint and Face”, International Conference on Advances in Recent Technologies in Communication and Computing, 2009.

[129] M.1. Ahmad, W.L. Woo and S.S. Dlay, “Multimodal Biometric Fusion at Featu re Level: Face and Palmprint”, IEEE, 978-1-86135-369-6/101,2010

[130] Erik Hjelm˚as and Boon Kee Low, “Face Detec-tion: A Survey”, Computer Vision and Image Understanding 83, 236–274 (2001), http://www.idealibrary.com

[131] Muhammad Sharif, Sajjad Mohsin and Mu-hammad Younas Javed, “A Survey: Face Recognition Techniques”, Research Journal of Applied Sciences, Engineering and Tech-nology, ISSN: 2040-7467, 2012

[132] Xiaoguang Lu and Anil K. Jain, “Automatic Feature Extraction for Multiview 3D Face Recognition”, Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition, 2006

[133] Hesher, A. Srivastava, and G. Erlebacher, “A Novel Technique for Face Recognition Using Range Imaging,” Proc. Int’l Symp. Signal Processing and Its Applications, pp. 201-204, 2003.

[134] G. Medioni and R. Waupotitsch, “Face Modeling and Recognition in 3-D,” Proc. IEEE Int’l Workshop Analysis and Modeling of Faces and Gestures, pp. 232-233, Oct. 2003.

[135] J. Cook, V. Chandran, S. Sridharan, and C. Fookes, “Face Recognition from 3D Data Using Iterative Closest Point Algorithm and Gaussian Mixture Models,” Proc. Second Int’l Symp

[136] Kevin W. Bowye, Kyong Chang, Patrick Flynn, “A survey of approaches and challenges in 3D and multi-modal 3D + 2D face recognition”, Computer Vision and Image Understanding 101 (2006) 1–15, Science Direct

[137] G. Gordon, "Face Recognition Based on Depth Maps and Surface Curvature," in SPIE Proceedings: Geometric Methods in Computer Vision, Vol.1570, 1991, pp.234-- 247.

[138] U. Castellani, M. Bicego, G. Iacono, and V. Murino, "3D Face Recognition Using Stereoscopic Vision," in Advanced Studies in Biometrics, Vol.3161, Lecture Notes in Computer Science, M. Tistarelli, J. Bigun, and E. Grosso, Eds.: Springer Berlin / Heidel-berg, 2005, pp.126-137

[139] Y. Wang, C. Chua, and Y. Ho, "Facial feature detection and face recognition from 2D and 3D images," Pattern Recognition Letters, Vol.23, pp.1191-1202, 2002.

[140] Xin Geng, Zhi-Hua Zhou and Kate Smith-Miles, “Automatic Age Estimation Based on Facial Aging Patterns” IEEE Transactions On Pattern Analysis And Machine Intelligence, Vol. 29, No. 12, December 2007

[141] F. S. Samaria and A. C. Harter, "Parameterisa-tion of a stochastic model for human face identification," in Proceedings of the 2nd IEEE Workshop on Appli-cations of Computer Vision. Sarasota, FL, USA, 1994, pp.138-142.

[142] G. C. Zhang, X. S. Huang, S. Z. Li, Y. S. Wang, and X. H. Wu, "Boosting local binary pattern (LBP) based face recognition," in Advances In Biometric Person Authentication, Proceedings, Vol.3338, Lecture Notes In Computer Science, 2004, pp.179-186.