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Ear Biometric Recognition Using Gradient-Based Feature Descriptors

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Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2018 (AISI 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 845))

Abstract

Recently, intensive research efforts are conducted on the human ear as a promising biometric modality for identity recognition. However, one of the main challenges facing ear recognition systems is to find robust representation for the image information that is invariant to different imaging variations. Recent studies indicate that using the distribution of local intensity gradients or edge directions can better discriminate the shape and appearance of objects. Moreover, gradient-based features are robust to global and local intensity variations as well as noise and geometric transformation of images. This paper presents an ear biometric recognition approach based on the gradient-based features. To this end, four local feature extractors are investigated, namely: Histogram of Oriented Gradients (HOG), Weber Local Descriptor (WLD), Local Directional Patterns (LDP), and Local Optimal Oriented Patterns (LOOP). Extensive experiments are conducted for both identification and verification using the publicly available IIT Delhi-I, IIT Delhi-II, and AMI ear databases. The obtained results are encouraging, where the LOOP features excel in all cases achieving recognition rates of approximately 97%.

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Author information

Authors and Affiliations

  1. Department of Mathematics, Faculty of Science, South Valley University, Qena, 83523, Egypt

    Hammam A. Alshazly & Mourad Ahmed

  2. Department of Computer Science, Faculty of Computers and Information, South Valley University, Luxor, Egypt

    M. Hassaballah

  3. Department of Computer Science, Faculty of Computers and Information, Minia University, Al Minia, 61519, Egypt

    Abdelmgeid A. Ali

Authors
  1. Hammam A. Alshazly
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  2. M. Hassaballah
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  3. Mourad Ahmed
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  4. Abdelmgeid A. Ali
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Corresponding author

Correspondence to Hammam A. Alshazly .

Editor information

Editors and Affiliations

  1. Information Technology Department, Faculty of Computers and Information, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

  2. Ain Shams University, Cairo, Egypt

    Mohamed F. Tolba

  3. Dubai International Academic City, The British University in Dubai, Dubai, United Arab Emirates

    Khaled Shaalan

  4. Faculty of Computers and Information, Benha University, Benha, Egypt

    Ahmad Taher Azar

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Alshazly, H.A., Hassaballah, M., Ahmed, M., Ali, A.A. (2019). Ear Biometric Recognition Using Gradient-Based Feature Descriptors. In: Hassanien, A., Tolba, M., Shaalan, K., Azar, A. (eds) Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2018. AISI 2018. Advances in Intelligent Systems and Computing, vol 845. Springer, Cham. https://doi.org/10.1007/978-3-319-99010-1_40

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