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Online 3D Ear Recognition by Combining Global and Local Features

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  • Yahui Liu
  • Bob Zhang
  • Guangming Lu
  • David Zhang

Abstract

The three-dimensional shape of the ear has been proven to be a stable candidate for biometric authentication because of its desirable properties such as universality, uniqueness, and permanence. In this paper, a special laser scanner designed for online three-dimensional ear acquisition was described. Based on the dataset collected by our scanner, two novel feature classes were defined from a three-dimensional ear image: the global feature class (empty centers and angles) and local feature class (points, lines, and areas). These features are extracted and combined in an optimal way for three-dimensional ear recognition. Using a large dataset consisting of 2,000 samples, the experimental results illustrate the effectiveness of fusing global and local features, obtaining an equal error rate of 2.2%.

Suggested Citation

  • Yahui Liu & Bob Zhang & Guangming Lu & David Zhang, 2016. "Online 3D Ear Recognition by Combining Global and Local Features," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-19, December.
    • Handle: RePEc:plo:pone00:0166204
    DOI: 10.1371/journal.pone.0166204
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    References listed on IDEAS

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    1. Lin Zhang & Zhixuan Ding & Hongyu Li & Ying Shen, 2014. "3D Ear Identification Based on Sparse Representation," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-9, April.
    2. Long Chen & Zhichun Mu & Baoqing Zhang & Yi Zhang, 2015. "Ear Recognition from One Sample Per Person," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-16, May.
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