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Ear Recognition in 2D

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Ear Biometrics in 2D and 3D

Part of the book series: Augmented Vision and Reality ((Augment Vis Real,volume 10))

Abstract

This chapter presents an efficient ear recognition technique which derives benefits from the local features of the ear and attempt to handle the problems due to pose, poor contrast, change in illumination and lack of registration. It uses (1) three image enhancement techniques in parallel to neutralize the effect of poor contrast, noise and illumination, (2) a local feature extraction technique (SURF) on enhanced images to minimize the effect of pose variations and poor image registration. SURF feature extraction is carried out on enhanced images to obtain three sets of local features, one for each enhanced image. Three nearest neighbor classifiers are trained on these three sets of features. Matching scores generated by all three classifiers are fused for final decision. The technique has been evaluated on two public databases, namely IIT Kanpur ear database and University of Notre Dame ear database (Collections E). Experimental results confirm that the use of proposed fusion significantly improves the recognition accuracy.

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Notes

  1. 1.

    Various performance measures including EER and EUC are explained in Chap. 1.

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Authors and Affiliations

  1. Computer Science and Engineering, Indian Institute of Technology Indore, Indore, India

    Surya Prakash

  2. Computer Science and Engineering, Indian Institute of Technology Kanpur, Kanpur, India

    Phalguni Gupta

Authors
  1. Surya Prakash
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  2. Phalguni Gupta
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Correspondence to Surya Prakash .

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© 2015 Springer Science+Business Media Singapore

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Prakash, S., Gupta, P. (2015). Ear Recognition in 2D. In: Ear Biometrics in 2D and 3D. Augmented Vision and Reality, vol 10. Springer, Singapore. https://doi.org/10.1007/978-981-287-375-0_3

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  • DOI: https://doi.org/10.1007/978-981-287-375-0_3

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-287-374-3

  • Online ISBN: 978-981-287-375-0

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