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An Review on Ear Recognition Techniques Based On Local Texture Descriptors

S. Saranya1 , R. Anandha Jothi2 , V. Palanisamy3

Section:Review Paper, Product Type: Journal Paper
Volume-7 , Issue-5 , Page no. 1583-1587, May-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i5.15831587

Online published on May 31, 2019

Copyright © S. Saranya, R. Anandha Jothi, V. Palanisamy . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: S. Saranya, R. Anandha Jothi, V. Palanisamy, “An Review on Ear Recognition Techniques Based On Local Texture Descriptors,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.5, pp.1583-1587, 2019.

MLA Style Citation: S. Saranya, R. Anandha Jothi, V. Palanisamy "An Review on Ear Recognition Techniques Based On Local Texture Descriptors." International Journal of Computer Sciences and Engineering 7.5 (2019): 1583-1587.

APA Style Citation: S. Saranya, R. Anandha Jothi, V. Palanisamy, (2019). An Review on Ear Recognition Techniques Based On Local Texture Descriptors. International Journal of Computer Sciences and Engineering, 7(5), 1583-1587.

BibTex Style Citation:
@article{Saranya_2019,
author = {S. Saranya, R. Anandha Jothi, V. Palanisamy},
title = {An Review on Ear Recognition Techniques Based On Local Texture Descriptors},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2019},
volume = {7},
Issue = {5},
month = {5},
year = {2019},
issn = {2347-2693},
pages = {1583-1587},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4453},
doi = {https://doi.org/10.26438/ijcse/v7i5.15831587}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i5.15831587}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4453
TI - An Review on Ear Recognition Techniques Based On Local Texture Descriptors
T2 - International Journal of Computer Sciences and Engineering
AU - S. Saranya, R. Anandha Jothi, V. Palanisamy
PY - 2019
DA - 2019/05/31
PB - IJCSE, Indore, INDIA
SP - 1583-1587
IS - 5
VL - 7
SN - 2347-2693
ER -

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Abstract

Ear biometric is considered as one of the most reliable and invariant biometrics characteristics. Ear recognition is an active area of research and automatic ear recognition is one of the challenging areas in biometric and forensic domains. Human ear contains large amount of unique features for recognition of an individual. The Ear biometric is unhurried as one of the majority unswerving and invariant biometrics approach. Ear appreciation is an active area of enquiry and instinctive ear recognition is one of the challenging areas in biometric and pathological provinces. When compared with the other biometric based recognition, human ear recognition system is universally accepted by various researchers. There are different approaches and descriptors that achieve relatively good results in ear biometric recognition. In this study, presents an overview of different local texture descriptors in the field of automatic ear recognition. Further, we have compared the various feature descriptor extraction techniques and discuss the recognition rate and accuracy for different problems.

Key-Words / Index Term

Ear Biometric, Physiological and Texture Characteristics, Recognition, Local Descriptors

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