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Simulation Based Exploration of SKC Block Cipher Algorithm

S.Wilson 1 , A. Lenin Fred2

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-9 , Page no. 496-501, Sep-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i9.496501

Online published on Sep 30, 2018

Copyright © S.Wilson, A. Lenin Fred . 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.Wilson, A. Lenin Fred, “Simulation Based Exploration of SKC Block Cipher Algorithm,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.496-501, 2018.

MLA Style Citation: S.Wilson, A. Lenin Fred "Simulation Based Exploration of SKC Block Cipher Algorithm." International Journal of Computer Sciences and Engineering 6.9 (2018): 496-501.

APA Style Citation: S.Wilson, A. Lenin Fred, (2018). Simulation Based Exploration of SKC Block Cipher Algorithm. International Journal of Computer Sciences and Engineering, 6(9), 496-501.

BibTex Style Citation:
@article{Fred_2018,
author = {S.Wilson, A. Lenin Fred},
title = {Simulation Based Exploration of SKC Block Cipher Algorithm},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {9 2018},
volume = {6},
Issue = {9},
month = {9},
year = {2018},
issn = {2347-2693},
pages = {496-501},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=2898},
doi = {https://doi.org/10.26438/ijcse/v6i9.496501}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i9.496501}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=2898
TI - Simulation Based Exploration of SKC Block Cipher Algorithm
T2 - International Journal of Computer Sciences and Engineering
AU - S.Wilson, A. Lenin Fred
PY - 2018
DA - 2018/09/30
PB - IJCSE, Indore, INDIA
SP - 496-501
IS - 9
VL - 6
SN - 2347-2693
ER -

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Abstract

Video based Face Recognition (VFR) has significantly more challenges when compared to Still Image-based Face Recognition (SIFR). The objective of this paper is to identify faces in video more precisely. In this paper, the minute details of the face are identified by block based technique. It is classified using neural network. The proposed method is tested with four publicly available datasets: Multiple Biometric Grand Challenge (MBGC), Face and Ocular Challenge Series (FOCS), Honda/UCSD and UMD Comcast10 datasets. The proposed method achieves higher recognition rate when compared to other recent methods.

Key-Words / Index Term

Keyframe, Block matching algorithm, face recognition

References

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