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TerrorBot- Python Based Cascade Classifier to Detect Terrorists and Soldiers

Kavya R1 , Keerthana A2 , Keerthana H N3 , Meena K N4 , Chetana Srinivas5

Section:Research Paper, Product Type: Journal Paper
Volume-07 , Issue-15 , Page no. 59-64, May-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7si15.5964

Online published on May 16, 2019

Copyright © Kavya R, Keerthana A, Keerthana H N, Meena K N, Chetana Srinivas . 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: Kavya R, Keerthana A, Keerthana H N, Meena K N, Chetana Srinivas, “TerrorBot- Python Based Cascade Classifier to Detect Terrorists and Soldiers,” International Journal of Computer Sciences and Engineering, Vol.07, Issue.15, pp.59-64, 2019.

MLA Style Citation: Kavya R, Keerthana A, Keerthana H N, Meena K N, Chetana Srinivas "TerrorBot- Python Based Cascade Classifier to Detect Terrorists and Soldiers." International Journal of Computer Sciences and Engineering 07.15 (2019): 59-64.

APA Style Citation: Kavya R, Keerthana A, Keerthana H N, Meena K N, Chetana Srinivas, (2019). TerrorBot- Python Based Cascade Classifier to Detect Terrorists and Soldiers. International Journal of Computer Sciences and Engineering, 07(15), 59-64.

BibTex Style Citation:
@article{R_2019,
author = { Kavya R, Keerthana A, Keerthana H N, Meena K N, Chetana Srinivas},
title = {TerrorBot- Python Based Cascade Classifier to Detect Terrorists and Soldiers},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2019},
volume = {07},
Issue = {15},
month = {5},
year = {2019},
issn = {2347-2693},
pages = {59-64},
url = {https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=1201},
doi = {https://doi.org/10.26438/ijcse/v7i15.5964}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i15.5964}
UR - https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=1201
TI - TerrorBot- Python Based Cascade Classifier to Detect Terrorists and Soldiers
T2 - International Journal of Computer Sciences and Engineering
AU - Kavya R, Keerthana A, Keerthana H N, Meena K N, Chetana Srinivas
PY - 2019
DA - 2019/05/16
PB - IJCSE, Indore, INDIA
SP - 59-64
IS - 15
VL - 07
SN - 2347-2693
ER -

           

Abstract

Most of the defense organization now takes the help of robots to carry out many risky jobs that cannot be done by soldiers. These robots used in defense or usually employed with integrated system, including video screens, sensors, laser gun, metal detector and cameras. The defense robots also have different shapes according to various purposes. Here the new system is proposed with the help of camera through we can trace out the intruders and the robot will be employed with integrated system, including video camera, sensors, gripper and weapon. The intruders face detection by Haar Cascade Classifier and face recognition by LBPH (Local Binary Pattern Histogram). This is specially designed robotic system to protect the country from enemies and to save soldiers life. The proposed algorithm is implemented using Opensource Computer Vision (OpenCV) and image processing with python.

Key-Words / Index Term

Face detection; Haar Cascade Classifiers; Face recognition; LBPH; OpenCV

References

[1] “Context-Aware local binary feature learning for face recognition” Yueqi Duan, Jiwen Lu, Jianjiang Feng,Jie Zhou,IEEE Transactions on pattern analysis and machine intelligence, vol 40, no 5, May 2018.
[2] “Simultaneous Local Binary Feature Learning and encoding for homogenous and heterogenous face recognition”,Jiwen Lu, Venice Erin Liong,Jie Zhou, IEEE Transactions on pattern analysis and machine intelligence,vol 40,no 8, August 2018.
[3]”Trunk- Branch Ensemble Convulational neuaral network for video based face recognition” Changxing Ding,” Dancheng Tao, IEEE Transcations on pattern analysis and machine intelligence, vol 40, no 4,April 2018.
[4]”Panoric Face Recogntion” Yun-Fu liu, Jing-Ming Guo,Po-Hisen Liu, Jiann-Der Lee, Chen-ChichYao, IEEE Transactions on circuits and systems for video Technology, Vol 28,No 8,August 2018.
[5]”Real-time face detection based on YOLO” Wang Yang,Zheng Jiachun,1st IEEE International conference on knowledge Innovation and Invention 2018
[6] “Face Recogntion based door lock system using OpenCv and C# with Remote Access and Security Features”Prathamesh Timse,Pranav Aggarwal, Prakhar Sinha, Neel Vora, Prathamesh Timse et al Int. Journal of Engineering Research and Applications, ISSN: 2248-9622,Vol 4 ,Issue 4(Version 6),April 2018,pg.52-57
[7] “Face Recogntion and Tracking System based and Embedded Platform” Chen Zhang, Tianygue Li, Boquan Li,Xi Ye, 10th International conference on modelling Identification and control,July,2-4,2018, Guiyang, China
[8]”Multi- Faces Recognition Process Using Haar Cascades and EigebFace Methods” Teddy Mantoro,Suhendi, 10th International Conference, august ,2018
[9] “Automatic Door Access System Using Face Recogntion” Htelk Htar Lwin,Aung Soe Khaing,Hla Myo Tun,International Journal of Scientific and technology Research volume 4, Issue 06,June 2015