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Ear Biometric Recognition in Unconstrained Conditions

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International Telecommunications Conference

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 504))

Abstract

Recognizing identity from morphological shape of the human ear using one sample image per person in training-set (i.e. only one model of the individual to be identified is registered in the database and available for the task of identification), with insufficient and incomplete training data, dealing with strong person-specificity can be very challenging. In addition, most encountered testing-images in real world applications are not in high quality due to their acquisitions in difficult conditions (ex, video-surveillance) which cause more challenges like: rotated images or images with low resolution. In continuation to our previous works on ear recognition, we present in this paper an experimental and comparative study on the effects of rotation and scaling of ear images using only one sample image per person in training-set which are considered as problems largely encountered in real world applications. Several local color texture descriptors are tested and compared under several color spaces. Support Vector Machine (SVM) is used as a classifier. We experiment with USTB-1 ear database. The experiments show very acceptable and interesting results in comparison to those reported in literature.

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Author information

Authors and Affiliations

  1. Department of Electrical Engineering, Faculty of Sciences and Applied Sciences, University of Akly Mohand Oulhadj, Bouira, Algeria

    Amir Benzaoui

  2. Laboratory of Inverse Problems, Modeling, Information and Systems (PI:MIS) Department of Electronics and Telecommunications, Faculty of Sciences and Technology, University of May 08th 1945, Guelma, Algeria

    Abdelhani Boukrouche

Authors
  1. Amir Benzaoui
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  2. Abdelhani Boukrouche
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Corresponding author

Correspondence to Amir Benzaoui .

Editor information

Editors and Affiliations

  1. Department of Electrical-Electronics Engineering, Istanbul Commerce University, Istanbul, Turkey

    Ali Boyaci

  2. Department of Information Technology, Balıkesir University, ‎Balıkesir, Turkey

    Ali Riza Ekti

  3. Computer Engineering Department, Istanbul University, Istanbul, Turkey

    Muhammed Ali Aydin

  4. Istanbul Commerce University, Istanbul, Turkey

    Serhan Yarkan

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Benzaoui, A., Boukrouche, A. (2019). Ear Biometric Recognition in Unconstrained Conditions. In: Boyaci, A., Ekti, A., Aydin, M., Yarkan, S. (eds) International Telecommunications Conference. Lecture Notes in Electrical Engineering, vol 504. Springer, Singapore. https://doi.org/10.1007/978-981-13-0408-8_22

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  • DOI: https://doi.org/10.1007/978-981-13-0408-8_22

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-0407-1

  • Online ISBN: 978-981-13-0408-8

  • eBook Packages: EngineeringEngineering (R0)

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