Automated Human Identification Scheme using Ear Biometrics Technology

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Author(s)

V.K. Narendira Kumar 1,* B. Srinivasan 1

1. Gobi Arts & Science College (Autonomous), Gobichettipalayam – 638 453, Erode District, Tamil Nadu, India.

* Corresponding author.

DOI: https://doi.org/10.5815/ijigsp.2014.03.08

Received: 1 Nov. 2013 / Revised: 4 Dec. 2013 / Accepted: 7 Jan. 2014 / Published: 8 Feb. 2014

Index Terms

Ear, Biometrics, Recognition, Detection, Extraction

Abstract

Biometrics identification methods have proved to be very efficient, more natural and easy for users than traditional methods of human identification. Biometrics methods truly identify humans, not keys and cards they posses or passwords they should remember. Ear on the other hand, has a more uniform distribution of color, so almost all information is conserved when converting the original image into gray scales. We propose the ear as a biometric and investigate it with both 2D and 3D data. The ICP-based algorithm also demonstrates good scalability with size of dataset. These results are encouraging in that they suggest a strong potential for 3D ear shape as a biometric. Multi-biometric 2D and 3D ear recognition are also explored. The proposed automatic ear detection method will integrate with the current system, and the performance will be evaluated with the original one. The investigation of ear recognition under less controlled conditions will focus on the robustness and variability of ear biometrics. Multi-modal biometrics using 3D ear images will be explored, and the performance will be compared to existing biometrics experimental results.

Cite This Paper

V.K. Narendira Kumar, B. Srinivasan,"Automated Human Identification Scheme using Ear Biometrics Technology", IJIGSP, vol.6, no.3, pp. 58-65, 2014. DOI: 10.5815/ijigsp.2014.03.08

Reference

[1]B. Bhanu and H. Chen, Human ear recognition in 3D. In Workshop on Multimodal User Authentication, pages 91–98 (2003).

[2]M. Burge and W. Burger, Ear biometrics. In Biometrics: Personal Identification in Networked Society, pages 273–286, Kluwer Academic (1999).

[3]M. Burge and W. Burger, Ear biometrics in computer vision. In 15th International Conference of Pattern Recognition, volume 2, pages 822–826 (2000).

[4]K. Chang, K. Bowyer and V. Barnabas, Comparison and combination of ear and face images in appearance-based biometrics. In IEEE Trans. Pattern Anal. Machine Intell. volume 25, pages 1160–1165 (2003).

[5]K. Chang, K. Bowyer and P. Flynn, Face recognition using 2D and 3D facial data. In Workshop on Multimodal User Authentication, pages 25–32 (2003).

[6]A. Iannarelli, Ear identification. In Forensic identification series, Fremont, California, Paramont Publishing Company (1989).

[7]B. Victor, K. Bowyer and S. Sarkar, An evaluation of face and ear biometrics. In 16th International Conference of Pattern Recognition, pages 429–432 (Aug. 2002).

[8]K. Pulli, Multiview registration for large data sets. In Second International Conference on 3-D Imaging and Modeling (3DIM '99), pages 160–168 (October 04-08, 1999).

[9]D. Huttenlocher, G. Klanderman and W. Rucklidge, Comparing images using the hausdorff distance. In IEEE Trans. Pattern Anal. Machine Intell. Volume 15(9), pages 850–863 (1993).