http://iet.metastore.ingenta.com
1887

Palm vein recognition with local texture patterns

Palm vein recognition with local texture patterns

For access to this article, please select a purchase option:

Buy article PDF
£12.50
(plus tax if applicable)
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
IET Biometrics — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

Biometric recognition using the palm vein characteristics is emerging as a touchless and spoof-resistant hand-based means to identify individuals or to verify their identity. One of the open challenges in this field is the creation of fast and modality-dependent feature extractors for recognition. This article investigates features using local texture description methods. The local binary pattern (LBP) operator as well as the local derivative pattern (LDP) operator and the fusion of the two are studied in order to create efficient descriptors for palm vein recognition by systematically adapting their parameters to fit palm vein structures. Results of experiments are reported on the CASIA multi-spectral palm print image database V1.0 (CASIA database). It is found that the local texture patterns proposed in this study can be adapted to the vein description task for biometric recognition and that the LDP operator consistently outperforms the LBP operator in palm vein recognition.

References

    1. 1)
      • 1. Watanabe, M., Endoh, T., Shiohara, M., Sasaki, S.: ‘Palm vein authentication technology and its applications’. Proc. Biometrics Symp., 2005, pp. 3738.
    2. 2)
      • 2. Wilson, C.: Vein pattern recognition: a privacy-enhancing biometric(CRC press, 2010).
    3. 3)
      • 3. Toh, K.A., Eng, H.L., Choo, Y.S., Cha, Y.L., Yau, W.Y., Low, K.S.: ‘Identity verification through palm vein and crease texture’. Advances in Biometrics, 2005(LNCS, 3832), pp. 546553.
    4. 4)
      • 4. Wu, X., Gao, E., Tang, Y., Wang, K.: ‘A novel biometric system based on hand vein’. In 5th Int. Conf. on Frontier of Comput. Science and Technol., 2010, pp. 522526.
    5. 5)
      • 5. Zhang, D., Guo, Z., Lu, G., Zhang, L., Zuo, W.: ‘An online system of multi-spectral palmprint verification’, IEEE Trans. Instrum. Meas., 2010, 59, (2), pp. 480490 (doi: 10.1109/TIM.2009.2028772).
    6. 6)
      • 6. Kumar, A., Hanmandlu, M., Sanghvi, H., Gupta, H.M.: ‘Decision level biometric fusion using ant colony optimization’. Seventeenth IEEE Int. Conf. Image Processing (ICIP), 2010, pp. 31053108.
    7. 7)
      • 7. Singh, S., Ramalho, M., Correia, P.L., Soares, L.D.: ‘Biometric identification through palm and dorsal hand vein patterns’. Int. Conf. Computer as a Tool (EUROCON), 2011, pp. 14.
    8. 8)
      • 8. Chen, H., Lu, G., Wang, R.: ‘A new palm vein matching method based on ICP algorithm’. Proc. Second Int. Conf. Interaction Sciences: Information Technology, Culture and Human, 2009, pp. 12071211.
    9. 9)
      • 9. Greitans, M., Pudzs, M., Fuksis, R.: ‘Palm vein biometrics based on infrared imaging and complex matched filtering’. Proc. 12th ACM Workshop on Multimedia and Security, 2010, pp. 101106.
    10. 10)
      • 10. Wang, J.G., Yau, W.Y., Suwandy, A., Sung, E.: ‘Person recognition by fusing palmprint and palm vein images based on ‘Laplacianpalm’ representation’, Pattern Recognit., 2008, 41, (5), pp. 15141527 (doi: 10.1016/j.patcog.2007.10.021).
    11. 11)
      • 11. Zhou, Y., Kumar, A.: ‘Human identification using palm-vein images’, IEEE Trans. Inf. Forensics Sec., 2011, 6, (4), pp. 12591274 (doi: 10.1109/TIFS.2011.2158423).
    12. 12)
      • 12. Li, Q., Zeng, Y., Peng, X., Yang, K.: ‘Curvelet-based palm vein biometric recognition’, Chin. Opt. Lett., 2010, 8, (6), pp. 577579 (doi: 10.3788/COL20100806.0577).
    13. 13)
      • 13. Sun, J., Abdulla, W.: ‘Palm vein recognition using curvelet transform’. Proc. 27th Conf. Image and Vision Computing New Zealand (IVCNZ ’12), New York, NY, USA, 2012, pp. 435439.
    14. 14)
      • 14. Ladoux, P.O., Rosenberger, C., Dorizzi, B.: ‘Palm vein verification system based on SIFT matching’. Advances in Biometrics, 2009(LNCS, 5558), pp. 12901298.
    15. 15)
      • 15. Zhang, H., Hu, D.: ‘A palm vein recognition system’. Int. Conf. Intelligent Computation Technology and Automation, 2010, vol. 1, pp. 285288.
    16. 16)
      • 16. Wang, J.-G., Yau, W.-Y., Suwandy, A.: ‘Feature-level fusion of palmprint and palm vein for person identification based on a junction point representation’. Fifteenth IEEE Int. Conf. Image Processing, 2008, pp. 253256.
    17. 17)
      • 17. Hartung, D., Olsen, M.A., Xu, H., Busch, C.: ‘Spectral minutiae for vein pattern recognition’. Int. Joint Conf. Biometrics, 2011.
    18. 18)
      • 18. Fischer, M., Rybnicek, M., Tjoa, S.: ‘A novel palm vein recognition approach based on enhanced local Gabor binary patterns histogram sequence’. Nineteenth Int. Conf. Systems, Signals and Image Processing, 2012, pp. 429432.
    19. 19)
      • 19. Malki, S., Spaanenburg, L.: ‘Hand veins feature extraction using DT-CNNS’. Society of Photo-Optical Instrumentation Engineering Conf. Series, 2007, vol. 6590 (doi: 10.1117/12.722920).
    20. 20)
      • 20. Hao, Y., Sun, Z., Tan, T., Ren, C.: ‘Multispectral palm image fusion for accurate contact-free palmprint recognition’. Fifteenth IEEE Int. Conf. Image Processing (ICIP), 2008, pp. 281284.
    21. 21)
      • 21. Pietikäinen, M., Hadid, A., Zhao, G., Ahonen, T.: ‘Computer vision using local binary patterns’ (Springer, 2011).
    22. 22)
      • 22. Ahonen, T., Hadid, A., Pietikainen, M.: ‘Face description with local binary patterns: application to face recognition’, IEEE Trans. Pattern Anal. Mach. Intell., 2006, 28, (12), pp. 20372041 (doi: 10.1109/TPAMI.2006.244).
    23. 23)
      • 23. Lee, E.C., Lee, H.C., Park, K.R.: ‘Finger vein recognition using minute-based alignment and local binary pattern-based feature extraction.Int. J. Imaging Syst., and Technol., 19, (3), 2009, pp. 179186 (doi: 10.1002/ima.20193).
    24. 24)
      • 24. Wang, Y., Li, K., Cui, J., Shark, L.-K., Varley, M.: ‘Study of hand-dorsa vein recognition’. Advanced Intelligent Computing Theories and Applications, 2010(LNCS), pp. 490498.
    25. 25)
      • 25. Zhang, B., Gao, Y., Zhao, S., Liu, J.: ‘Local derivative pattern versus local binary pattern: face recognition with high-order local pattern descriptor’, IEEE Trans. Image Process., 2010, 19, (2), pp. 533544 (doi: 10.1109/TIP.2009.2035882).
    26. 26)
      • 26. Lee, E.C., Jung, H., Kim, D.: ‘New finger biometric method using near infrared imaging’, Sensors, 2011, 11, (3), pp. 23192333 (doi: 10.3390/s110302319).
    27. 27)
      • 27. Mirmohamadsadeghi, L., Drygajlo, A.: ‘Palm vein recognition with local binary patterns and local derivative patterns’. Int. Joint Conf. Biometrics, 2011.
    28. 28)
      • 28. Ojala, T., Pietikäinen, M., Mäenpää, T.: ‘Multiresolution gray-scale and rotation invariant texture classification with local binary patterns’, IEEE Trans. Pattern Anal. Mach. Intell., 2002, 24, pp. 971987 (doi: 10.1109/TPAMI.2002.1017623).
    29. 29)
      • 29. CASIA Multi-Spectral Palm Print Image Database V1.0 (CASIA database) http://www.cbsr.ia.ac.cn/MS_Palmprint Database.asp.
    30. 30)
      • 30. Kailath, T.: ‘The divergence and Bhattacharyya distance measures in signal selection’, IEEE Trans. Commun. Technol., 1967, 15, (1), pp. 5260 (doi: 10.1109/TCOM.1967.1089532).
    31. 31)
      • 31. Swain, M.I.J., Ballard, D.H.: ‘Color indexing.Int. J. Comput. Vis., 1991, 7, pp. 1132 (doi: 10.1007/BF00130487).
    32. 32)
      • 32. Li, S.Z.: ‘Encyclopedia of biometrics’ (Springer, New York, 2009, 1st edn.), pp. 1068.
    33. 33)
      • 33. University of Oulu Machine Vision Group: http://www.cse.oulu.fi/cmv/downloads/lbpmatlab.
    34. 34)
      • 34. Paris, S.: http://www.mathworks.com/matlabcentralfileexchange/29800scenesobjects-classification-toolbox.
    35. 35)
      • 35. Ross, A.A., Nandakumar, K., Jain, A.K.: ‘Handbook of multibiometrics (International Series on Biometrics)’ (Springer-Verlag New York, Inc., 2006), Ch. 4 pp. 98.
    36. 36)
      • 36. Zhang, Y.B., Li, Q., You, J., Bhattacharya, P.: ‘Palm vein extraction and matching for personal authentication’, Adv. Vis. Inf., 2007, 4781, pp. 154–164.
    37. 37)
      • 37. Fuksis, R., Kadikis, A., Greitans, M.: ‘Biohashing and fusion of palmprint and palm vein biometric data’. Int. Conf. Hand-Based Biometrics (ICHB), 2011, pp. 16.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-bmt.2013.0041
Loading

Related content

content/journals/10.1049/iet-bmt.2013.0041
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address