Call for Paper - March 2023 Edition
IJCA solicits original research papers for the March 2023 Edition. Last date of manuscript submission is February 20, 2023. Read More

Review of Hand Feature of Unimodal and Multimodal Biometric System

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Juberahmad Shaikh, Uttam D. Kolekar

Juberahmad Shaikh and Uttam D Kolekar. Article: Review of Hand Feature of Unimodal and Multimodal Biometric System. International Journal of Computer Applications 133(5):19-24, January 2016. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

	author = {Juberahmad Shaikh and Uttam D. Kolekar},
	title = {Article: Review of Hand Feature of Unimodal and Multimodal Biometric System},
	journal = {International Journal of Computer Applications},
	year = {2016},
	volume = {133},
	number = {5},
	pages = {19-24},
	month = {January},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}


In this age of digital impersonation, biometric techniques are being used increasingly for authentication technique to prevent unauthorized access. As only biometrics, the authentication of individuals using biological identities, can offer true proof of identity. The increasing interest of biometrics is related to security, forensics and remote managing. Extensive research has been conducted in this area with different techniques. In this paper, unimodal, multimodal and fusion techniques are reviewed for authentication.


  1. A. Kong and D. Zhang, “Palmprint Identification Based on Generalization of Iris Code”, A thesis presented to the University of Waterloo, Canada, 2007.
  2. A. Kong and D. Zhang, “Palmprint texture analysis based on low-resolution images for personal authentication”, in Proceedings of 16th International Conference on Pattern Recognition, vol. 3, pp. 807-810, 2002.
  3. A. Kong, D. Zhang and G. Lu, “A study of identical twins palmprint for personal verification”, Pattern Recognition, vol. 39, no, 11, pp. 2149-2156, 2006.
  4. A. Kong and D. Zhang, “Competitive coding scheme for palmprint verification”, in Proceedings of International Conference on Pattern Recognition, vol. 1, pp. 520-523, 2004.
  5. A. Kong, D. Zhang and M. Kamel, “Palmprint identification using feature-level fusion”, Pattern Recognition, vol. 39, no. 3, pp. 478-487, 2006.
  6. A. Kong, D. Zhang and M. Kamel, “A analysis of brute-force break-ins of a palmprint verification system”, IEEE Transactions on Systems, Man and Cybernetics, Part B, vol. 36, no. 5, pp. 1201-1205, 2006.
  7. A. Kong, K.H. Cheung, D. Zhang, M. Kamel and J. You, “An analysis of Biohashing and its variants”, Pattern Recognition, vol. 39, no. 7, pp. 1359-1368, 2006.
  8. D. Zhang, W.K. Kong, J. You and M. Wong, “On-line palmprint identification”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 25, no. 9, pp. 1041-1050, 2003.
  9. X. Wu, D. Zhang and K. Wang, “Fisher palms based palm print recognition”, Pattern Recognition Letters, vol. 24, no, 15, pp. 2829-2838, 2003.
  10. X. Wu, D. Zhang, K. Wang and B. Huang, “Palmprint classification using principal lines”, Pattern Recognition, vol. 37, no. 10, pp. 1987-1998, 2004.
  11. G. Lu, D. Zhang and K. Wang, “Palmprint recognition using eigenpalms features”, Pattern Recognition Letters, vol. 24, no. 9, pp. 1463-1467, 2003.
  12. G. Lu, K. Wang and D. Zhang “Wavelet based feature extraction for palm print identification”, in Proceeding of Second International Conference on Image and Graphics, pp. 780-784, 2002.
  13. X.Y. Jing and D. Zhang, “A face and palmprint recognition approach based on discriminant DCT feature extraction”, IEEE Transactions on Systems, Man, and Cybernetics Part B:Cybernetics, vol. 34, no. 6, pp. 2405-2415, 2004.
  14. “Artifical Neural Networks Technology” prepared For: Rome laboratory, RL/C3C.Griffiss AFB, NY 13441-5700,
  15. Raymond Thai, “Fingerprint Image Enhancement and Minutiae Extraction”,Technical Report, The University of Western Australia, 2003.
  16. A. K. Jain, K. Nandakumar, & A. Ross, “Score Normalization in multimodal biometric systems”. The Journal of Pattern Recognition Society, 38(12), 2005, 2270-2285.
  17. Fuertes, J.J. Travieso, C.M. ;  Ferrer, M.A. and Alonso, J.B. “Intra-modal biometric system using hand-geometry and palmprint texture “,IEEE International Conference on Security Technology (ICCST), Carnahan, Oct. 2010, 318 - 322
  18. Dhananjay, D.M. Rao, C.V.G. ;  Muralikrishna, I.V. “ Preliminary classification of palmprint-A novel approach “,International Conference on Signal Processing, Communication, Computing and Networking Technologies (ICSCCN), 2011.
  19. VassiliosChatzis,,“Multimodal Decision-Level Fusion for Person Authentication”IEEE transactions on systems, man, and cybernetics—part a: systems and humans, vol. 29, no. 6, November 1999.
  20. Pavesic N. “Finger based personal authentication” IEEE transaction on signal processing, IET vol 3, Issue 4, 2009, page no.269-281
  21. Slobodan Ribaric, “A Biometric Identification System Based on Eigen palm and Eigen finger Features”IEEE transactions on pattern analysis and machine intelligence, vol. 27, no. 11, November 2005.
  22. RaffaeleCappelli,,“Performance Evaluation of Fingerprint Verification Systems” IEEE transactions on pattern analysis and machine intelligence, vol. 28, no. 1, January 2006.
  23. Damer, N et al, Biometric source weighting in multi-biometric fusion: Towards a generalized and robust solution Signal Processing Conference (EUSIPCO), Sept. 2014
  24. Miguel A. Ferrer, “low cost multimodal biometric identification system based on handgeometry, palm and finger print texture” Security Technology,2007, 41st Annual IEEE International Carnahan Conference on 2007,page No-52-58
  25. Fernando Alonso-Fernandez,, “A Comparative Study of Fingerprint Image-Quality Estimation Methods” IEEE transactions on information forensics and security, vol. 2, no. 4, December 2007
  26. Mustafa Mumtaz,, “Wavelet Based Palm print Authentication System” Biometrics and security Technologies,2008.ISBAST 2008.International symposium on 23-24 April 2008 page(s):1-7
  27. Norman Poh,, “Benchmarking Quality-Dependent and Cost-Sensitive Score-Level Multimodal Biometric Fusion Algorithms”, IEEE transactions on information forensics and security, vol. 4, no. 4, December 2009 849.
  28. Vincenzo Conti,,“A Frequency-based Approach for Features Fusion in Fingerprint and Iris Multimodal Biometric Identification Systems”, IEEE transactions on systems, man,and cybernetics—part c: applications and reviews, vol. 40, no. 4, July 2010.
  29. Li Xiuyan,,“Theoretical Analysis and Experimental Study on Multimodal Biometric” International Conference on Control, Automation and Systems Engineering (CASE), 2011 page(s): 1-4
  30. Lang Zhai,, “The Research of Double-biometric Identification Technology Based on Finger Geometry & Palm print”.Artificial intelligence,Mangement science and Electronic Commerce (AIMSEC),2011 second International Conference on No:3530-3533.
  31. Dr. V. Vijayalakshmi, et. al, “India Finger and Palm print based Multi biometric Authentication System with GUI Interface” International conference on Communication and Signal Processing, April 3-5, 2013.
  32. Javier Galbally,,“Image Quality Assessment for Fake Biometric Detection: Application to Iris, Fingerprint, and Face Recognition”, IEEE transactions on image processing, vol. 23, no.2, February 2014.
  33. Rupali Telgad,, “Combination Approach to Score Level Fusion for Multimodal Biometric System By Using Face and Fingerprint” IEEE International Conference on Recent Advances and Innovations in Engineering (ICRAIE-2014), May 09-11, 2014, Jaipur, India.
  34. Allen George,, “An Efficient System for Palm Print Recognition using Ridges”, International Conference on Intelligent Computing Applications, 2014 .
  35. Kevin W. Bowyer,,“Multi-Modal Biometrics: An Overview”
  36. Divyakant T. Meva ,et al. Comparative Study of Different Fusion Techniques inMultimodal Biometric Authentication, International Journal of Computer Applications (0975 – 8887) Volume 66– No.19, March 2013
  37. A Fast Personal Palmprint Authentication Based On 3d-Multi Wavelet Transnational Journal Of Science And Technology September 2012 Edition Vol.2,No.8.
  38. Heeseung Choi, Kyoungtaek Choi, and Jaihie Kim, Fingerprint Matching Incorporating Ridge Features With Minutiae, IEEE Transactions On Information Forensics And Security, Vol. 6, No. 2, June 2011.
  39. Anil K. Jain, Salil Prabhakar, Lin Hong, and Sharath Pankanti, Filterbank-Based Fingerprint Matching, IEEE Transactions On Image Processing, Vol. 9, No. 5, May 2000.
  40. Lin Hong, Yifei Wan, and Anil Jain, Fingerprint Image Enhancement: Algorithm and Performance Evaluation, IEEE Transactions On Pattern Analysis And Machine Intelligence, Vol. 20, No. 8, August 1998.
  41. Yuliang He, Jie Tian, Senior Member, IEEE, Liang Li, Hong Chen, and Xin Yang, Fingerprint Matching Based on Global Comprehensive Similarity, IEEE Transactions On Pattern Analysis And Machine Intelligence, Vol. 28, No. 6, June 2006.
  42. Shlomo Greenberg, Mayer Aladjem, Daniel Kogan and Itshak Dimitrov, Fingerprint Image Enhancement Using Filtering Techniques. Pattern recognition,2000.proceedings 15th International Conference on(Volume:3) page(s): 322-325
  43. YingHAO, Tieniu TAN, Yunhong WANG, An Effecitve Algorithm For Fingerprint Matching. TENCON ’02.Proceedings.2002 IEEE Region 10 Conference on Computers,Communications ,Control and power Enfineering(Volume:1),Oct.2002,Page(s)519-522 Vol1.
  44. A. Montesanto, P. Baldassarri, G. Vallesi, G. Tascini, Fingerprints Recognition Using Minutiae Extraction: a Fuzzy Approach Image Analysis and Processing,2007.ICIAP 2007 Page(s):229-234
  45. Raghavendra R, Rao A, Hemantha Kumar G. Multimo Score fusion using Gaussian mixture model and Monte Carlo method. Journal of Computer Science And Technology 25(4): 771–782 Jul 2010. DOI 10.1007/s11390-010-1060-0


unimodal, multimodal, score level fusion, FAR, FRR