EAR RECOGNITION USING LOCAL BINARY PATTERN

BATOOL ABDULSATAR ABDULGHANI; AHMED KHORSHEED AL-SULAIFANIE

doi:10.26682/sjuod.2017.20.1.11

BATOOL ABDULSATAR ABDULGHANI Dept. of IT, Shekhan Technical Institute, Unversity of Polytechnic Dohuk, Kurdistan Region-Iraq
AHMED KHORSHEED AL-SULAIFANIE Dept. of IT ECE, College of Engineering, University of Duhok, Kurdistan Region-Iraq

DOI: https://doi.org/10.26682/sjuod.2017.20.1.11

Keywords: Biometric, Ear Recognition, Local Binary Pattern, Feature Extraction, Histogram

Abstract

In this paper an efficient complete Ear Recognition System (ERS) has been proposed based on the Local Binary Pattern (LBP) approach that can investigate maximum recognition rate; hence it can be used for surveillance applications. The feature extraction is based on calculating the LBP feature for the ear image and dividing the resultant LBP image into several overlap regions, and then extracts the histogram from each region. These histograms are considered as a similarity measure in the classification phase. To evaluate the proposed approach, the Indian Institute of Technology (IIT) Delhi processed ear image dataset has been considered, which contains 125 individual, each with at least three images acquired in the age group between 14 and 58 years.

Practical experiments are employed on the proposed ERS to find the best image division regions at best LBP parameters (radius and neighbors) that lead to maximum recognition rate. Detailed experiments show that the proposed system achieved 93.75 % rank-one recognition rate. Furthermore, an experimental study is achieved to examine the less Equal Error Rate (EER). Some identities from the database are considered as imposters. In a verification scenario, the system achieved an Equal Error Rate (EER) of 14.94 %. The Receiver Operating Characteristics (ROC) curve showed that the Genuine Acceptance Rate (GAR) is about 84%.

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References

 A baza, A., & Harrison, M. A. (2013). Ear recognition: a complete system. SPIE Defense, Security and Sensing. Biometric Technology for Human Identification (pp. 87120N-87120N-11). International Society for Optics and Photonics.
 Ahonen, T., Hadid, A., & Pietikäinen, M. (2004). Face recognition with local binary patterns. European conference on computer vision (pp. 469-481). Springer.
 Arbab-Zavar, B., & Nixon, M. S. (2011, April). On guided model-based analysis for ear biometrics. Computer Vision and Image Understanding, 115(4), 487-502.
 Bertillon, A. (1890). La photographie judiciaire : avec un appendice sur la classification et l'identification anthropométriques ( Print book : French ed.). Paris : Gauthier-Villars.
 Boodoo-Jahangeer, N., & Baichoo, S. (2013). LBP-based ear recognition. In Proceedings of the 2013 IEEE 13th International Conference on Bioinformatics and Bioengineering (BIBE) (pp. 1-4). IEEE.
 D'Alessandro, M. P. (2012). A digital library of anatomy information. Retrieved 9 19, 2016, from http://www.anatomyatlases.org/firstaid/Otoscopy.shtml
 Introna, L. D., & Nissenbaum, H. (2009). Facial Recognition Technology. A Servey of Policy and Implementation Issues, CCPR.
 Julsing, B. (2007). Face Recognition with Local Binary Patterns. University of Twente, Department of Electrical Engineering, Mathematics & Computer Science (EEMCS).

 Kumar, A. (2007). IIT Delhi Ear Database, 1.0. Retrieved 9 13, 2016, from IIT Delhi Ear Database: http://www4.comp.polyu.edu.hk/~csajaykr/IITD/Database_Ear.htm
 Kumar, V. N., & Srinivasan, B. (2014, February). Automated human identification scheme using ear biometrics technology. International Journal of Image, Graphics and Signal Processing, 6(3), 58-65.
 Mahatma, D., Jain, R., & Parihar, P. S. (2014, July). A Strong Approach of Human Recognition Using Ear Biometrics with Efficient Computation Time. International Journal of Engineering Research & Technology (IJERT), 1(7).
 Ojala, T., Pietikäinen, M., & Harwood, D. (1996, January). A comparative study of texture measures with classification based on featured distributions. Pattern recognition, 29(1), 51-59.
 Prakash, S., & Gupta, P. (2015). Ear Biometrics in 2D and 3D: Localization and Recognition (Vol. 10). Springer.
 Purkait, R. (2007). Ear Biometric: An aid to personal identification. Anthropologist Special volume(3), 215-218.