Journal Title : International Journal of Modern Trends in Engineering and Science

Author’s Name : M Logapreethi | N B Mahesh Kumar

Volume 01 Issue 12  Year 2014  

ISSN no:  2348-3121 

Page no: 8-11

Abstract— The palm print is one of the most reliable and robust physiological characteristics that can be used to distinguish between individuals. Current palm print based systems are more user friendly, more cost effective than traditional fingerprint-based identification systems. Palm print consists of principal lines, wrinkles, and epidermal ridges. In that Principle lines are most stable feature to identify an individual. Palm print identification system generally acquires an image from the data-set, per-processes the image, extracts the feature and matches and verifies it with the database and identifies the result.  Palm print identification system must be accurate, reliable, fast and robust for identifying an individual.

Keywords— Principal palm lines, consistency, image acquisition, image pre-processing, feature extraction, identification


[1] F. Yue and W. Zuo “Consistency analysis on orientation features for fast and accurate palm print identification,” Elsevier Trans. on Information Sci., Vol. 268, No. 1, pp. 78-90, Aug (2013).
[2] W. Zuo, F. Yue and D. Zhang, “On accurate orientation extraction and appropriate distance measure for low-resolution palm print recognition,” Elsevier Trans. on Pattern Recog., Vol. 44, No. 4, pp. 964–972, Apr (2011).
[3] Jayshri Patil and Chhaya Nayak, “A Survey of Multispectral Palm print Identification Techniques,” Int. J. Scientific Engg. and Technol., Vol. 3, No. 8, pp. 1051-1053, Aug (2014).
[4] L. Zhang and D. Zhang, “Characterization of palm prints by wavelet signatures via directional context modeling,” IEEE Trans. on System Man Cyber., Vol. 34, No. 3, pp. 1335–1347, May (2004).
[5] W. Zuo, Z. Lin, Z. Guo and D. Zhang, “The multiscale competitive code via sparse representation for palm print verification,” in proc. of IEEE conf. on Com. Vision and Pattern Recog., pp. 2265– 2272, Jun (2010).
[6] PolyU, Polyu palm print database, (2012). <http://www.comp.polyu.edu.hk/biometric>.
[7] D. Zhang, W. Kong, J. You and M. Wong “Online Palm print Identification,” IEEE Trans. on Pattern Analysis and Machine Intell., Vol. 25, No. 9, pp. 1041-1050, Sep (2003).
[8] X. Wu, D. Zhang, K. Wang and B. Huang, “Palm print classification using principal lines,” Elsevier Trans. on Pattern Recog., Vol. 37, No. 10, pp. 1987-1998,Feb (2004).
[9] J. Zhou, J. W. Gu, “A model-based method for the computation of fingerprints orientation field,” IEEE Trans. on Image Proc., Vol. 13 , No. 6, pp. 821–835, Jun (2004).
[10] F. Yue, W. M. Zuo, D. Zhang, K. Q. Wang, “Competitive code-based palm print recognition using fcm-based orientation selection,” Elsevier Trans on Pattern Recog., Vol. 42, No. 11, pp. 2841–2849, Mar (2009).
[11] Z. N. Sun, T. N. Tan, Y. Wang, S. Li, “Ordinal palm print representation for personal identification,” in Proc. of Int. Conf. on Computer Vision and Pattern Recog., Vol. 1, pp. 279–284, May (2005).
[12] J. You, W. X. Li, D. Zhang, “Hierarchical palm print identification via multiple feature extraction,” Elsevier Trans on Pattern Recog., Vol. 35, No. 4, pp. 847–859, Apr (2002).
[13] L. Zhang, D. Zhang, “Characterization of palm prints by wavelet signatures via directional context modeling,” IEEE Trans. on Systems, Man and Cybern., Vol. 34, No. 3, pp. 1335-1347, May (2004).

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