Speeded Up Robust Factor for Tongue Biometrics- Person Identification Method

Vibhooti Markandey*
*Assistant Professor, Department of Information Technology, Shrishankaracharya Group of Institutions, Shrishankaracharya Technical Campus, Junwani, Bhilai (C.G.), India.
Periodicity:June - August'2016
DOI : https://doi.org/10.26634/jpr.3.2.8265

Abstract

Just like the uniqueness of physiological features of various biometric modalities, Tongue Print of a person possesses uniqueness in itself. Tongue print of every Human is different and unique. Besides being unique it the least manipulated organ that it enhances security for identification and authentication of a person, avoiding most of the forgery cases. This paper introduces the feature extraction and the methodology for the study of person identification using tongue print. Speeded Up Robust Factor (SURF) is used, which is a local invariant interest point detector and descriptor.

Keywords

Biometrics, Tongue Print, Unique Physiology, SURF

How to Cite this Article?

Markandey, V. (2016). Speeded Up Robust Factor for Tongue Biometrics- Person Identification Method. i-manager’s Journal on Pattern Recognition, 3(2), 24-29. https://doi.org/10.26634/jpr.3.2.8265

References

[1]. David Zhang, et al. (2010). “Dynamic Tongue Print: A Novel Biometric Identifier”. Pattern Recognition, Vol. 43, pp. 1071-1082.
[2]. Herbert Bay, et al. (2008). Speeded-Up Robust Features (SURF), Preprint submitted to Elsevier.
[3]. S.Z. Li, and L. Juwei, (1999). “Face recognition using the nearest feature line method”. IEEE Transactions on Neural Networks, Vol. 10, pp. 439–443.
[4]. A.F. Abate, M. Nappi, D. Riccio, and G. Sabatino, (2007). “2D and 3D face recognition: A survey”. Pattern Recognition Letters, Vol. 28, pp. 1885–1906.
[5]. J. Daugman, (2004). “How iris recognition works”. IEEE Transactions on Circuits and Systems for Video Technology, Vol. 14, pp. 21–30.
[6]. K.W. Bowyer, K. Hollingsworth, and P.J. Flynn, (2008). “Image understanding for iris biometrics: A survey”. Computer Vision and Image Understanding, Vol. 110, No. 2, pp. 281–307.
[7]. N.K. Ratha, K. Karu, C. Shaoyun, and A.K. Jain, (1996). “A real-time matching system for large fingerprint databases”. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 18, pp. 799–813.
[8]. D. Zhang, K. Wai-Kin, J. You, and M. Wong, (2003). “Online palmprint identification”. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 25, pp. 1041–1050.
[9]. Kuragano, T., Yamaguchi, A., and Furukawa, S., (2005). “A Method to Measure Foot Print Similarity for Gait Analysis”. IEEE Computer Society- 2005 International Conference on Computational Intelligence for Modelling, Control and Automation, and International Conference Intelligent Agents, Web Technologies and Internet Commerce (CIMCA-IAWIC'05).
[10]. V. Wan, and S. Renals, (2005). “Speaker verification using sequence discriminant support vector machines”. IEEE Transactions on Speech and Audio Processing, Vol. 13, pp. 203–210.
[11]. L.L. Lee, T. Berger, and E. Aviczer, (1996). “Reliable online human signature verification systems”. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 18, pp. 643–647.
[12]. Zhi Liu, et al. (2007). “A Tongue-Print Image Database for Recognition”. Proceedings of the Sixth International Conference on Machine Learning and Cybernetics, Hong Kong, pp. 19-22.
[13]. Norman Poh, et al. (2010). “A multimodal biometrics test bed for quality-dependent, cost sensitive and clientspecific score-level fusion algorithm”. Pattern Recognition, Vol. 43, pp. 1094-1105.
[14]. V. Haxby, et al., (2000). “The Distributed Human Neural System for Face Perception”. Trends in Cognitive Sciences, Vol. 4, pp. 223–233.
[15]. C. Harris, and M. Stephens, (1988). “A combined corner and edge detector”. Proceedings of the Alvey Vision Conference, pp. 147-151.
[16]. T. Lindeberg, (1988). “Feature detection with automatic scale selection”. IJCV, Vol. 30, No. 2, pp. 79-116.
[17]. T. Kadir, and M. Brady, (2001). “Scale, saliency and image description”. IJCV, Vol. 45, No. 2, pp. 83-105.
[18]. D. Lowe, (2004). “Distinctive image features from scale-invariant key points, cascade altering approach”. IJCV, Vol. 60, No. 2, pp. 91-110.
[19]. H. Bay, T. Tuytelaars, and L. Van Gool, (2006). “SURF: Speeded up robust features”. European Conference on Computer Vision.
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