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Genetic Algorithm Based Facial Sentiments Recognition using Edge Feature

Rahul Chaurasia1 , Jitendra Agrawal2

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-9 , Page no. 913-917, Sep-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i9.913917

Online published on Sep 30, 2018

Copyright © Rahul Chaurasia, Jitendra Agrawal . 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: Rahul Chaurasia, Jitendra Agrawal, “Genetic Algorithm Based Facial Sentiments Recognition using Edge Feature,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.913-917, 2018.

MLA Style Citation: Rahul Chaurasia, Jitendra Agrawal "Genetic Algorithm Based Facial Sentiments Recognition using Edge Feature." International Journal of Computer Sciences and Engineering 6.9 (2018): 913-917.

APA Style Citation: Rahul Chaurasia, Jitendra Agrawal, (2018). Genetic Algorithm Based Facial Sentiments Recognition using Edge Feature. International Journal of Computer Sciences and Engineering, 6(9), 913-917.

BibTex Style Citation:
@article{Chaurasia_2018,
author = {Rahul Chaurasia, Jitendra Agrawal},
title = {Genetic Algorithm Based Facial Sentiments Recognition using Edge Feature},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {9 2018},
volume = {6},
Issue = {9},
month = {9},
year = {2018},
issn = {2347-2693},
pages = {913-917},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=2963},
doi = {https://doi.org/10.26438/ijcse/v6i9.913917}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i9.913917}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=2963
TI - Genetic Algorithm Based Facial Sentiments Recognition using Edge Feature
T2 - International Journal of Computer Sciences and Engineering
AU - Rahul Chaurasia, Jitendra Agrawal
PY - 2018
DA - 2018/09/30
PB - IJCSE, Indore, INDIA
SP - 913-917
IS - 9
VL - 6
SN - 2347-2693
ER -

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Abstract

Most of sentiment based image classification approaches have done lots of complex calculation such as number of feature was collected for identifying correct class. In case of supervised learning models prediction of sentiment class for the unknown image leads to false alarm. So this work take facial input image features and find the sentiment of image by genetic approach. In this work grouping of various sort of information was managed without bargaining the security using genetic algorithm TLBO teacher Learning Based Optimization. Experiment was done on real dataset of JAFEE Images. Results show that execution time for the sentiment identification of image information was low. Here proposed work was capable to classify input data with high accuracy as compared to previous machine learning approaches.

Key-Words / Index Term

Color format, digital image processing, facial sentiment detection, and genetic algorithm

References

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