Abstract
Biometrics, which use human physiological or behavioral features for personal identification, currently face the challenge of designing a secure biometric system that will accept only the legitimate presentation of the biometric identifiers without being fooled by the doctored or spoofed measurements that are input into the system. More biometric traits are required for improving the performance of authentication systems. In this chapter, we present a new number for the biometrics family, i.e. tongueprint, which uses particularly interesting properties of the human tongue to base a technology for noninvasive biometric assessment. The tongue is a unique organ which can be stuck out of the mouth for inspection, whose appearance is amenable to examination with the aid of a machine vision system. Yet it is otherwise well protected in the mouth and difficult to be forged. Furthermore, the involuntary squirm of the tongue is not only a convincing proof that the subject is alive, but also a feature for recognition. That is to say, the tongue can present both static features and dynamic features for authentication. However, little work has hitherto been done on the tongue as a biometric identifier. In this work, we make use of a database of tongue images obtained over a long period to examine the performance of the tongueprint as a biometric identifier. Our research shows that tongueprint is a promising candidate for biometric identification and worthy of further research.
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References
Abate A, Nappi M, Riccio D, Sabatino G (2007) 2D and 3D face recognition: a survey. Pattern Recogn Lett 28:1885–1906
Bowyer K, Hollingsworth K, Flynn P (2007) Image understanding for iris biometrics: a survey. Comput Vis Image Underst 110(2):281–307
Brand R, Isselhard D (1998) Anatomy of orofacial structures, 6th edn. St. Louis, Missouri
Daugman J (1993) High confidence visual recognition of persons by a test of statistical independence. IEEE Trans Pattern Anal Mach Intell 15:1148–1161
Daugman J (2004) How iris recognition works. IEEE Trans Circuits Syst Video Technol 14:21–30
Haxby J, Hoffman E, Gobbini M (2000) The distributed human neural system for face perception. Trends Cogn Sci 4:223–233
Jain A, Healey G (1998) A multiscale representation including opponent color features for texture recognition. IEEE Trans Image Process 7:124–128
Jain A, Bolle R, Pankanti S (1998) Biometrics: personal identification in networked society. Kluwer Academic, Boston
Jain A, Pankanti S, Prabhakar S, Lin H, Ross A (2004) Biometrics: a grand challenge. In: Proceedings of the 17th international conference on pattern recognition (ICPR), vol 2, pp 935–942
Kittler J, Hatef M, Duin R, Matas J (1998) On combining classifiers. IEEE Trans Pattern Anal Mach Intell 20:226–239
Knight B, Johnston A (1997) The role of movement in face recognition. Vis Cogn 4:265–274
Kokiopoulou E, Saad Y (2007) Orthogonal neighborhood preserving projections: a projection-based dimensionality reduction technique. IEEE Trans Pattern Anal Mach Intell 29:2143–2156
Kollreider K, Fronthaler H, Bigun J (2005) Evaluating liveness by face images and the structure tensor. In: Proceedings of the fourth IEEE workshop on automatic identification advanced technologies, pp 75–80
Kollreider K, Fronthaler H, Bigun J (2009) Non-intrusive liveness detection by face images. Image Vis Comput 27(3):233–244
Kong W, Zhang D, Li W (2003) Palmprint feature extraction using 2-D Gabor filters. Pattern Recogn 36:2339–2347
Lee L, Berger T, Aviczer E (1996) Reliable online human signature verification systems. IEEE Trans Pattern Anal Mach Intell 18:643–647
Li S, Juwei L (1999) Face recognition using the nearest feature line method. IEEE Trans Neural Netw 10:439–443
Lin H, Anil J (1998) Integrating faces and fingerprints for personal identification. IEEE Trans Pattern Anal Mach Intell 20:1295–1307
Moon Y, Chen J, Chan K, So K, Woo K (2005) Wavelet based fingerprint liveness detection. Electron Lett 41:1112–1113
O’Gorman L (2003) Comparing passwords, tokens, and biometrics for user authentication. Proc IEEE 91:2021–2040
OToole A, Roark D, Abdi H (2002) Recognizing moving faces: a psychological and neural synthesis. Trends Cogn Sci 6:261–266
Pang B, Zhang D, Wang K (2005) The bi-elliptical deformable contour and its application to automated tongue segmentation in chinese medicine. IEEE Trans Med Imaging 24:946–956
Phillips P, Hyeonjoon M, Rizvi S, Rauss P (2000) The FERET evaluation methodology for face-recognition algorithms. IEEE Trans Pattern Anal Mach Intell 22:1090–1104
Pikaz A, Dinstein I (1995) Matching of partially occluded planar curves. Pattern Recogn 28:199–209
Ratha N, Karu K, Shaoyun C, Jain A (1996) A real-time matching system for large fingerprint databases. IEEE Trans Pattern Anal Mach Intell 18:799–813
Roweis S, Saul L (2000) Nonlinear dimensionality reduction by locally linear embedding. Science 290:2323–2326
Sanchez-Reillo R, Sanchez-Avila C, Gonzalez-Marcos A (2000) Biometric identification through hand geometry measurements. IEEE Trans Pattern Anal Mach Intell 22:1168–1171
Sandström M (2004) Liveness detection in fingerprint recognition systems. Department of Electrical Engineering, Linköping University
Tistarelli M, Bicego M, Grosso E (2009) Dynamic face recognition: from human to machine vision. Image Vis Comput 27(3):222–232
Toth B (2005) Biometrics liveness detection. Inf Secur Bull 10:291–297
Turk M, Pentland A (1991) Eigenfaces for recognition. J Cogn Neurosci 3:71–86
Wan V, Renals S (2005) Speaker verification using sequence discriminant support vector machines. IEEE Trans Speech Audio Process 13:203–210
Wang L, Tan T, Ning H, Hu W (2003) Silhouette analysis-based gait recognition for human identification. IEEE Trans Pattern Anal Mach Intell 25:1505–1518
Wenxin L, David Z, Zhuoqun X (2002) Palmprint identification by Fourier transform. Int J Pattern Recogn Artif Intell 16:417–432
Zhang D (2000) Automated biometrics – technologies and systems. Kluwer Academic, Boston
Zhang D, Wai-Kin K, You J, Wong M (2000) Online palmprint identification. IEEE Trans Pattern Anal Mach Intell 25:1041–1050
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Zhang, D., Lu, G., Zhang, L. (2018). Dynamic Tongueprint Recognition. In: Advanced Biometrics. Springer, Cham. https://doi.org/10.1007/978-3-319-61545-5_13
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DOI: https://doi.org/10.1007/978-3-319-61545-5_13
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