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Face Recognition using Symbolic Data with Texture Features

Yogish Naik G.R.1 , Arun Kumar H.D.2 , Prabhakar C.J.3

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-11 , Page no. 354-358, Nov-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i11.354358

Online published on Nov 30, 2018

Copyright © Yogish Naik G.R., Arun Kumar H.D., Prabhakar C.J. . 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: Yogish Naik G.R., Arun Kumar H.D., Prabhakar C.J., “Face Recognition using Symbolic Data with Texture Features,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.11, pp.354-358, 2018.

MLA Style Citation: Yogish Naik G.R., Arun Kumar H.D., Prabhakar C.J. "Face Recognition using Symbolic Data with Texture Features." International Journal of Computer Sciences and Engineering 6.11 (2018): 354-358.

APA Style Citation: Yogish Naik G.R., Arun Kumar H.D., Prabhakar C.J., (2018). Face Recognition using Symbolic Data with Texture Features. International Journal of Computer Sciences and Engineering, 6(11), 354-358.

BibTex Style Citation:
@article{G.R._2018,
author = {Yogish Naik G.R., Arun Kumar H.D., Prabhakar C.J.},
title = {Face Recognition using Symbolic Data with Texture Features},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {11 2018},
volume = {6},
Issue = {11},
month = {11},
year = {2018},
issn = {2347-2693},
pages = {354-358},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3168},
doi = {https://doi.org/10.26438/ijcse/v6i11.354358}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i11.354358}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3168
TI - Face Recognition using Symbolic Data with Texture Features
T2 - International Journal of Computer Sciences and Engineering
AU - Yogish Naik G.R., Arun Kumar H.D., Prabhakar C.J.
PY - 2018
DA - 2018/11/30
PB - IJCSE, Indore, INDIA
SP - 354-358
IS - 11
VL - 6
SN - 2347-2693
ER -

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Abstract

Face recognition is a type of biometric identification method, it is challenging and one of the active research area in the field of Computer Vision. Variations in face image is due to changes in expression, presence of occlusion, geographical variations and illumination along with aging are some of the challenges to face recognition technique. In this paper, we attempt to solve illumination challenge for face recognition. Here, we propose a novel symbolic face recognition technique using Logarithm Gradient Histogram (LGH). Experimental results are carried out on standard benchmark databases like Extended YaleB, ORL. The performance of the proposed face recognition technique turns out to be 94.35 to 100% for the mentioned databases.

Key-Words / Index Term

Face recognition, Illumination invariant feature, Logarithm Gradient Histogram (LGH)

References

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