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Dynamic Tongueprint Recognition

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Book cover Advanced Biometrics

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

    Article  Google Scholar 

  • Bowyer K, Hollingsworth K, Flynn P (2007) Image understanding for iris biometrics: a survey. Comput Vis Image Underst 110(2):281–307

    Article  Google Scholar 

  • Brand R, Isselhard D (1998) Anatomy of orofacial structures, 6th edn. St. Louis, Missouri

    Google Scholar 

  • Daugman J (1993) High confidence visual recognition of persons by a test of statistical independence. IEEE Trans Pattern Anal Mach Intell 15:1148–1161

    Article  Google Scholar 

  • Daugman J (2004) How iris recognition works. IEEE Trans Circuits Syst Video Technol 14:21–30

    Article  Google Scholar 

  • Haxby J, Hoffman E, Gobbini M (2000) The distributed human neural system for face perception. Trends Cogn Sci 4:223–233

    Article  Google Scholar 

  • Jain A, Healey G (1998) A multiscale representation including opponent color features for texture recognition. IEEE Trans Image Process 7:124–128

    Article  Google Scholar 

  • Jain A, Bolle R, Pankanti S (1998) Biometrics: personal identification in networked society. Kluwer Academic, Boston

    Google Scholar 

  • 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

    Google Scholar 

  • Kittler J, Hatef M, Duin R, Matas J (1998) On combining classifiers. IEEE Trans Pattern Anal Mach Intell 20:226–239

    Article  Google Scholar 

  • Knight B, Johnston A (1997) The role of movement in face recognition. Vis Cogn 4:265–274

    Article  Google Scholar 

  • Kokiopoulou E, Saad Y (2007) Orthogonal neighborhood preserving projections: a projection-based dimensionality reduction technique. IEEE Trans Pattern Anal Mach Intell 29:2143–2156

    Article  Google Scholar 

  • 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

    Google Scholar 

  • Kollreider K, Fronthaler H, Bigun J (2009) Non-intrusive liveness detection by face images. Image Vis Comput 27(3):233–244

    Article  Google Scholar 

  • Kong W, Zhang D, Li W (2003) Palmprint feature extraction using 2-D Gabor filters. Pattern Recogn 36:2339–2347

    Article  Google Scholar 

  • Lee L, Berger T, Aviczer E (1996) Reliable online human signature verification systems. IEEE Trans Pattern Anal Mach Intell 18:643–647

    Article  Google Scholar 

  • Li S, Juwei L (1999) Face recognition using the nearest feature line method. IEEE Trans Neural Netw 10:439–443

    Article  Google Scholar 

  • Lin H, Anil J (1998) Integrating faces and fingerprints for personal identification. IEEE Trans Pattern Anal Mach Intell 20:1295–1307

    Article  Google Scholar 

  • Moon Y, Chen J, Chan K, So K, Woo K (2005) Wavelet based fingerprint liveness detection. Electron Lett 41:1112–1113

    Article  Google Scholar 

  • O’Gorman L (2003) Comparing passwords, tokens, and biometrics for user authentication. Proc IEEE 91:2021–2040

    Article  Google Scholar 

  • OToole A, Roark D, Abdi H (2002) Recognizing moving faces: a psychological and neural synthesis. Trends Cogn Sci 6:261–266

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Pikaz A, Dinstein I (1995) Matching of partially occluded planar curves. Pattern Recogn 28:199–209

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Roweis S, Saul L (2000) Nonlinear dimensionality reduction by locally linear embedding. Science 290:2323–2326

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Sandström M (2004) Liveness detection in fingerprint recognition systems. Department of Electrical Engineering, Linköping University

    Google Scholar 

  • Tistarelli M, Bicego M, Grosso E (2009) Dynamic face recognition: from human to machine vision. Image Vis Comput 27(3):222–232

    Article  Google Scholar 

  • Toth B (2005) Biometrics liveness detection. Inf Secur Bull 10:291–297

    Google Scholar 

  • Turk M, Pentland A (1991) Eigenfaces for recognition. J Cogn Neurosci 3:71–86

    Article  Google Scholar 

  • Wan V, Renals S (2005) Speaker verification using sequence discriminant support vector machines. IEEE Trans Speech Audio Process 13:203–210

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Wenxin L, David Z, Zhuoqun X (2002) Palmprint identification by Fourier transform. Int J Pattern Recogn Artif Intell 16:417–432

    Article  Google Scholar 

  • Zhang D (2000) Automated biometrics – technologies and systems. Kluwer Academic, Boston

    Book  Google Scholar 

  • Zhang D, Wai-Kin K, You J, Wong M (2000) Online palmprint identification. IEEE Trans Pattern Anal Mach Intell 25:1041–1050

    Article  Google Scholar 

Download references

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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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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-61544-8

  • Online ISBN: 978-3-319-61545-5

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