IJSTR

International Journal of Scientific & Technology Research

IJSTR@Facebook IJSTR@Twitter IJSTR@Linkedin
Home About Us Scope Editorial Board Blog/Latest News Contact Us
CALL FOR PAPERS
AUTHORS
DOWNLOADS
CONTACT
QR CODE
IJSTR-QR Code

IJSTR >> Volume 4 - Issue 3, March 2015 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Improved Palmprint Identification System

[Full Text]

 

AUTHOR(S)

Harshala C. Salave, Dr. Sachin D. Pable

 

KEYWORDS

Keywords: PCA, DWT, Gaussian Filter, Canny Edge Detector, texture.

 

ABSTRACT

Abstract: Generally private information is provided by using passwords or Personal Identification Numbers, which is easy to implement but it is very easily stolen or forgotten or hack. In Biometrics, for individuals identification uses human physiological (which are constant throughout life like palm, face, DNA, iris etc.) or behavioral characteristics(which is not constant in life like voice, signature, keystroke, etc.). But mostly gain more attention to palmprint identification and is becoming more popular technique using for identification and promising alternatives to the traditional password or PIN based authentication techniques. In this paper propose palmprint identification using veins on the palm and fingers. Here use fusion of techniques such as Discrete Wavelet transform(DWT), Canny Edge Detector, Gaussian Filter, Principle Component Analysis(PCA).

 

REFERENCES

[1] A.K. Jain and J. Feng, “Latent palmprint matching,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 31, no. 6, pp. 1032- 1047, Jun. 2009.

[2] D.R. Ashbaugh, Quantitative-Qualitative Friction Ridge Analysis: Introduction to Basic Ridgeology, CRC Press, 1999.

[3] H. Cummins and M. Midlo, Finger Prints, Palms and Soles: An Introduction to Dermatoglyphics. Dover Publications, 1961.

[4] D. Zhang, W.K. Kong, J. You, and M. Wong, “Online palmprint identification,” IEEE Trans. Pattern Analysis and Machine Intelli- gence, vol. 25, no. 9, pp. 1041-1050, Sep. 2003.

[5] PolyU-Palmprint-Database, www.comp.polyu.edu.hk/~bio-metrics/, Accessed on Jun. 30, 2014.

[6] W. Jia, D. Huang, and D. Zhang, “Palmprint verification based on principal lines,” Pattern Recognition, vol. 41, no. 4, pp. 1316- 1328, Apr. 2008.

[7] L. Shang, D. Huang, J. Du, and C. Zheng, “Pamlprint recogni- tion using FastICA algorithm and radial basis probabilistic neu- ral network,“ Neurocomputing, vol. 69, no. 13, pp. 1782-1786, Aug. 2006.

[8] X. Wu, D. Zhang, and K. Wang, “Fisherpalms based palmprint recognition,“ Pattern Recognition Letters, vol. 24, no. 15, pp. 2829- 2838, Nov. 2003.

[9] L. Zhang and D. Zhang, “Characterization of palmprints by wavelet signatures via directional context modeling,” IEEE Trans. Systems, Man and Cybernetics, Part B, vol. 34, no. 3, pp. 1335–1347, Jun. 2004.

[10] A. Kong and D. Zhang, “Competitive coding scheme for palm- print verification,” Proc. Int’l Conf. Pattern Recognition, pp. 520- 523, 2004.

[11] Z. Sun, T. Tan, Y. Wang, and S.Z. Li, “Ordinal palmprint repre- sentation for personal identification,” Proc. IEEE Int’l Conf. Com- puter Vision and Pattern Recognition, pp. 279-284, 2005.

[12] “Data format for the interchange of fingerprint facial, & other biometric information,” ANSI/NIST-ITL, 1-2007, http://www. nist.gov/customcf/get_pdf.cfm?pub_id=51174, 2012.

[13] M. Liu and L. Li, “Cross-correlation based binary image regis- tration for 3D palmprint recognition,” Proc. Int’l Conf. Signal Processing, pp. 1597-1600, 2012. [27] J. Cui, “2D and 3D palmprint fusion and recognition using PCA plus TPTSR method,” Neural Comput. Applic., vol. 24, no. 3, pp. 497-502, Mar. 2014.

[14] J. Funada, N. Ohta, M. Mizoguchi, T. Temma, K. Nakanishi, A. Murai, T. Sugiuchi, T. of Wakabayashi, and Y. Yamada, “Feature Extraction Method for Palmprint Considering Elimination Creases,” Proc. 14th Int’l Conf. Pattern Recognition, vol. 2, pp. 1849-1854, 1998

[15] A. Jain and J. Feng, “Latent Palmprint Matching,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 31, no. 6, pp. 1032- 1047, June 2009.

[16] J. Dai and J. Zhou, “Multifeature-Based High-Resolution Palm- print Recognition,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 33, no. 5, pp. 945-957, May 2011.

[17] J. Dai, J. Feng, and J. Zhou, “Robust and Efficient Ridge-Based Palmprint Matching,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 34, no. 8, pp. 1618-1632, Aug. 2012, doi:10.1109/ TPAMI.2011.237.

[18] A. Jain and M. Demirkus, “On Latent Palmprint Matching,” technical report, Michigan state., http://biometrics.cse.msu.edu/Publications/Palmprints/JainDemirkusOnLatent PalmprintMatching08.pdf, 2008.

[19] J. Wang, W. Yau, A. Suwandy, and E. Sung, “Fusion of palmprint and palm vein images for person recognition based on laplacianpalm feature,” in CVPR, 2007, pp. 1–8.

[20] G. Lu, D. Zhang, and K. Wang, “Palmprint recognition using eigen- palms features,” Pattern Recognition Letters, vol. 24, no. 9-10, pp. 1463–1467, 2003.

[21] X. Wu, D. Zhang, and K. Wang, “Fisherpalms based palmprint recognition,” Patt. Recog. Lett., vol. 24, no. 15, pp. 2829–2838, 2003.

[22] X. Xu and Z. Guo, “Multispectral palmprint recognition us- ing quaternion principal component analysis,” IEEE Workshop on Emerging Techniques and Challenges for Hand-Based Biometrics, pp. 1–5, 2010.

[23] A. Kong and D. Zhang, “Competitive coding scheme for palmprint verification,” in ICPR, 2004, pp. 520–523.

[24] Z. Sun, T. Tan, Y. Wang, and S. Z. Li, “Ordinal palmprint representation for personal identification” in CVPR, 2005, pp. 279–284.

[25] Y. Hao, Z. Sun, T. Tan, and C. Ren, “Multispectral palm image fusion for accurate contact-free palmprint recognition,” in Proc. ICIP, 2008, pp. 281–284.

[26] D. Kisku, P. Gupta, J. Sing, and C. Hwang, “Multispectral palm image fusion for person authentication using ant colony optimiza- tion,” in IEEE Workshop on Emerging Techniques and Challenges for Hand-Based Biometrics, 2010, pp. 1–

[27] Z. Guo, D. Zhang, L. Zhang, and W. Zuo, “Palmprint verification using binary orientation co-occurrence vector,” Pattern Recognition Letters, vol. 30, no. 13, pp. 1219–1227, 2009.

[28] D. Han, Z. Guo, and D. Zhang, “Multispectral palmprint recognition using wavelet-based image fusion,” in ICSP, 2008, pp. 2074–2077.

[29] D. Zhang, Z. Guo, G. Lu, L. Zhang, and W. Zuo, “An online system of multispectral palmprint verification,” IEEE Transactions on In- strumentation and Measurement, vol. 59, no. 2, pp. 480–490, 2010.

[30] Y. Zhou and A. Kumar, “Human identification using palm-vein images,” IEEE Trans. Inf. Forensics Security, vol. 6, no. 4, pp. 1259–1274, Dec. 2011.