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Review of Ear Biometrics

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Abstract

As one of the most important biometrics, ear biometrics is getting more and more attention. Ear recognition has unique advantages and can make identification more secure and reliable together with other biometrics (e.g. face and fingerprint). Therefore, we investigate related information about ear recognition and classify the entire process of ear recognition, including detection, preprocessing, unimodal recognition including feature extraction and decision of classification or matching, and multimodal recognition based on inter-level and intra-level fusion. Unimodal and multimodal recognition are proposed comprehensively. In addition, inter-level and intra-level fusion are divided into different fusion ways. At the same time, we compare recognition results under the same dataset and analyze the difficulty of some datasets. In the end, challenges and outlook of ear recognition are also mentioned to expect to provide readers with some help about future directions and problems that should be overcome.

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Acknowledgements

Authors would like to thank editors and all reviewers for their valuable and constructive suggestions.

Funding

This work was jointly supported by Fundamental Research Funds for the Central Universities (lzuxxxy-2018-it73) and National Science Foundation of China (Grant No. 61201421).

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Authors and Affiliations

  1. School of Information Science and Engineering, Lanzhou University, Lanzhou, China

    Zhaobin Wang & Jing Yang

  2. Key Laboratory of Microbial Resources Exploitation and Application of Gansu Province, Institute of Biology, Gansu Academy of Sciences, Lanzhou, China

    Ying Zhu

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  1. Zhaobin Wang
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  2. Jing Yang
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Wang, Z., Yang, J. & Zhu, Y. Review of Ear Biometrics. Arch Computat Methods Eng 28, 149–180 (2021). https://doi.org/10.1007/s11831-019-09376-2

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