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Ear Recognition Using Texture Features - A Novel Approach

  • Conference paper
Advances in Signal Processing and Intelligent Recognition Systems

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 264))

Abstract

Ear is a new class of relatively stable biometric that is invariant from childhood to old age. It is not affected with facial expressions, cosmetics and eye glasses. Human ear is one of the representative human biometrics with uniqueness and stability. Ear Recognition for Personal Identification using 2-D ear from a side face image is a challenging problem. This paper analyzes the efficiency of using texture features such as Gray Level Co-occurrence Matrix (GLCM), Local Binary Pattern (LBP) and Gabor Filter for the recognition of ears. The combination of three feature vectors was experimented with. It is found that the combination gives better results compared to when the features were used in isolation. Further, it is found that the recognition accuracy improves by extracting local texture features extracted from sub-images. The proposed technique is tested using an ear database which contains 442 ear images of 221 subjects and obtained 94.12% recognition accuracy.

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Author information

Authors and Affiliations

  1. Saintgits College of Engineering, Kottayam, India

    Lija Jacob

  2. Department of Information Technology, Kannur University, Kannur, India

    G. Raju

Authors
  1. Lija Jacob
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  2. G. Raju
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Corresponding author

Correspondence to Lija Jacob .

Editor information

Editors and Affiliations

  1. Technopark Campus, Indian Institute of Information Technology and Management – Kerala (IIITM-K), Trivandrum, Kerala, India

    Sabu M. Thampi

  2. Center for Computing Research, National Polytechnic Institute, Mexico City, Mexico

    Alexander Gelbukh

  3. Department of Computer Science and Engineering, Indian Institute of Technology, Kharagpur, India

    Jayanta Mukhopadhyay

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© 2014 Springer International Publishing Switzerland

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Jacob, L., Raju, G. (2014). Ear Recognition Using Texture Features - A Novel Approach. In: Thampi, S., Gelbukh, A., Mukhopadhyay, J. (eds) Advances in Signal Processing and Intelligent Recognition Systems. Advances in Intelligent Systems and Computing, vol 264. Springer, Cham. https://doi.org/10.1007/978-3-319-04960-1_1

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  • DOI: https://doi.org/10.1007/978-3-319-04960-1_1

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-04959-5

  • Online ISBN: 978-3-319-04960-1

  • eBook Packages: EngineeringEngineering (R0)

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