Innovative Fusion of Ear and Fingerprint in Biometrics

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 216)

Abstract

Biometric-based personal identification is regarded as an effective method for identification. In multimodal systems more than one biometric sample feature is used for identification which makes duplications of feature and spoofing nearly impossible. This paper proposes an identification method for a multimodal biometric system using two traits, i.e., ear and fingerprint. A new technique is introduced here for choosing the region of interest of the ear and fingerprint image. The two local points, including the Canal Intertranguiano and the starting point of the Helix are taken as the region of interest (ROI) for ear. In case of fingerprint image also the same procedure is followed to take ROI from the fingerprint image. After feature extraction of ear and fingerprint both undergoes fusion process. The fusion of these two extracted features is done using concatenation technique. Later, matching process is carried out to identify a person.

Keywords

Multimodal system Region of interest Fusion 

References

  1. 1.
    Khan, M. K., Zhang, J.: Multimodal face and fingerprint biometrics authentication on space-limited tokens. Neurocomputing 71(13–15), 3026–3031 (2008)Google Scholar
  2. 2.
    Ross, A., Nandakumar, K., Jain, A.K.: Handbook of Multibiometrics. Springer, Heidelberg (2006)Google Scholar
  3. 3.
    Vaikole, S., Sawarkar, S.D., Hivrale, S., Sharma, T.: Minutiae feature extraction from fingerprint images. IEEE International Advance Computing Conference (IACC 2009) Patiala, India, 6–7 March (2009)Google Scholar
  4. 4.
    Kaur, R., Kamra, A.: A novel method for fingerprint feature extraction. International Conference on Networking and Information Technology, Manila, 2010Google Scholar
  5. 5.
    Choras, Michal: Ear biometrics based on geometrical feature extraction. Electron. Lett. Comp. Vis. Image Anal. 5(3), 84–95 (2005)Google Scholar
  6. 6.
    Palmer, L.R., Al-Tarawneh, M.S., Dlay, S.S., Woo, W.L.: Efficient fingerprint feature extraction algorithm and performance evaluation. Graz, Austria, IEEE, pp. 581–584, (2008)Google Scholar
  7. 7.
    Thillaikkarasi, J.T., Duraiswamy, K.: Cryptographic key generation from multiple biometric modalities: fusing minutiae with Iris feature. Int. J. Comp. Appl. 2(6), 0975–8887 (2010)Google Scholar
  8. 8.
    Lammi, H-K.: Ear Biometrics. Lappeenranta University of Technology, Department of Information Technology, Lappeenranta, FinlandGoogle Scholar

Copyright information

© Springer India 2014

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringSRM UniversityKattankulathurIndia
  2. 2.Ministry of Higher EducationCollege of Applied SciencesSoharOman

Personalised recommendations