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Occluded Ear Recognition Using Block-Based PCA

  • V. Ratna Kumari
  • P. Rajesh KumarEmail author
  • S. Srinivasa Kumar
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 898)

Abstract

In the real world, two non-intrusive biometric methods, namely face recognition and ear recognition, are interesting as they have flexibility in scanning the subject being tested. In particular, ear recognition is quite interesting as the ear pattern is stable in all emotions. This paper presents a novel way using block-based PCA to recognize ear even in case of partial occlusion. The other significance of the proposed method is that it can decide whether an input image is occluded or not. Conducted experiments, used a standard data set and shown that min–min fusion technique with city block distance metric is the apt ear recognition method when block-based PCA is used. The recognition rate with the proposed method is greater than 94%, and the equal error rate (EER) is less than 15% for a 25% occluded ear image.

Keywords

Ear recognition Principal component analysis Euclidean distance City block distance Recognition rate Equal error rate 

Notes

Acknowledgements

This work is supported by University Grants Commission of India under the scheme—Minor Research Project No. MRP6023 Dated: 31. 10. 2016.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • V. Ratna Kumari
    • 1
  • P. Rajesh Kumar
    • 1
    Email author
  • S. Srinivasa Kumar
    • 2
  1. 1.Department of ECEPrsad V. Potluri Siddhartha Institute of TechnologyKanuruIndia
  2. 2.Department of ECEJNT UniversityKakinadaIndia

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