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  3. Vol. 8, No. 1, February 2023
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Vol. 8, No. 1, February 2023

Issue Published : Feb 28, 2023
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Object Detection and Monitor System for Building Security Based on Internet of Things (IoT) Using Illumination Invariant Face Recognition

https://doi.org/10.22219/kinetik.v8i1.1622
Ivan Chatisa
Politeknik Caltex Riau
Yoanda Alim Syahbana
Politeknik Caltex Riau
Agus Urip Ari Wibowo
Politeknik Caltex Riau

Corresponding Author(s) : Yoanda Alim Syahbana

yoanda@pcr.ac.id

Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, Vol. 8, No. 1, February 2023
Article Published : Feb 28, 2023

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Abstract

Theft and intrusion are crimes that often occur in neighborhoods when there is opportunity or negligence by owners and security personnel. Many studies have been carried out to improve environmental security by applying cameras as a surveillance medium. However, the camera is not optimal in detecting objects when the lighting conditions are lacking. Therefore, in this study, a monitoring and object detection system was built by applying the Illumination Invariant model. This model is used to improve the appearance of the image from light and shadow reflections. The process of detecting and identifying objects is done by using human facial features (face detection) captured by the camera. The camera used is a Logitec C270 Webcam 720p which is connected via a USB port on the Raspberry Pi 4. The Raspberry Pi 4 processes human face image data and sends the processing results to a MySQL database using the HTTP protocol. Data transmission is done using the Python Flask web framework. The system was successfully run 100% by using black box testing of all functional requirements. Tests on the object detection feature were carried out based on different lighting conditions 15 times by comparing the original image and the results of the Illumination Invariant implementation. Based on the test results obtained object detection accuracy of 86.7%.

Keywords

crime Illumination Invariant Face Detection HTTP protocol Python Flask web framework
Chatisa, I., Syahbana, Y. A., & Wibowo, A. U. A. (2023). Object Detection and Monitor System for Building Security Based on Internet of Things (IoT) Using Illumination Invariant Face Recognition. Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, 8(1), 485-498. https://doi.org/10.22219/kinetik.v8i1.1622
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References
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  2. J. Celine, and S. Agustina, “Face Recognition in CCTV Systems,” IEEE Internet of Things Journal., 2018. https://doi.org/10.1109/ICSSIT46314.2019.8987961
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  5. E. Rohadi, S. A. Suwignjo, M. C. Pradana, and Team “Internet of Things: CCTV Monitoring by Using Raspberry Pi,” IEEE Internet of Things Journal., 2018. https://doi.org/10.1109/iCAST1.2018.8751612
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  25. S. Subiyanto, D. Priliyana, M. E. Riyadani, and Team, “Face recognition system with PCA-GA algorithm for smart home door security using Rasberry Pi,” Jurnal Teknologi dan Sistem Kompute., 2020. https://doi.org/10.14710/jtsiskom.2020.13590
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References


W. S. Yuwono, D. W. Sudiharto, and C. W. Wijiutomo, “Design and Implementation of Human Detection Feature on Surveillance Embedded IP Camera,” IEEE Internet of Things Journal., 2018. https://doi.org/10.1109/SIET.2018.8693180

J. Celine, and S. Agustina, “Face Recognition in CCTV Systems,” IEEE Internet of Things Journal., 2018. https://doi.org/10.1109/ICSSIT46314.2019.8987961

R. F. Navea, P. G. Arroyo, D. Dacalcap, and Team “Design and Implementation of a Human Tracking CCTV System using IP-Cameras,” IEEE TENCON., 2018. http://dx.doi.org/10.1109/TENCON.2018.8650246

M. Mahajan, R. RajeshwariBajre, L. Sharma, and S. L. Varma, “Computer Vision Based Campus Surveillance,” IEEE Internet of Things Journal., 2020. https://doi.org/10.1109/ICACCCN51052.2020.9362776

E. Rohadi, S. A. Suwignjo, M. C. Pradana, and Team “Internet of Things: CCTV Monitoring by Using Raspberry Pi,” IEEE Internet of Things Journal., 2018. https://doi.org/10.1109/iCAST1.2018.8751612

N. Surantha, and W. R. Wicaksono, “Design of Smart Home Security System using Object Recognition and PIR Senso,” Procedia Computer Science., Vol 8, Pages 465-472., 2018. https://doi.org/10.1016/j.procs.2018.08.198

B. N. Rao, and R. Sudheer, “Surveillance Camera using IoT and Raspberry Pi,” IEEE Journal., 2020. https://doi.org/10.1109/ICIRCA48905.2020.9182983

A. M. Husein, “Motion Detect Application With Frame Difference Method On A Surveillance Camera,” Journal of Physics Conference Series., 2018. http://dx.doi.org/10.1088/1742-6596/1230/1/012017

S. K. Yedla, V. M. Manikandan, and V. Panchami, “Real-time Scene Change Detection with Object Detection for Automated Stock Verification,” IEEE Journal., 2020. https://doi.org/10.1109/ICDCS48716.2020.243571

C. Zhao, B. Fan, J. Hu, Z. Zhang, and B. Zheng, “Motion Target Correlation Method Based On Structural Similarity In Camera Array,” IEEE Journal., 2018. https://doi.org/10.1109/CCDC.2018.8407325

H. S. Kanyal, M. Geol, A. S. Tomar, and Team, “Object Recognition and Security Improvement by Enhancing the Features of CCTV,” IEEE Journal., 2020. https://doi.org/10.1109/SMART50582.2020.9337065

A. A. Wazwaz, A. O. Herbawi, M. J. Teeti, and S. Y. Hmeed, “Raspberry Pi And Computers-Based Face Detection And Recognition System,” IEEE Internet of Things Journal., 2018. https://doi.org/10.1109/CATA.2018.8398677

B. Wang, C. L. P. Chen, Y. Li, and Y. Zhao, “Hard Shadows Removal Using an Approximate Illumination Invariant,” IEEE Journal., 2018. https://doi.org/10.1109/ICASSP.2018.8461695

M. Mehra, V. Sahai, P. Chowdhury, and E. Dsouza, “Home Security System using IOT and AWS Cloud Services,” IEEE Journal., 2019. https://doi.org/10.1109/ICAC347590.2019.9089839

S. Mehra, A. Khatri, P. Tanwar, and V. Khatri, “Intelligent Embedded Security control system for Maternity ward based on IoT and Face recognition,” International Conference on Advances in Computing, Communication Control and Networking (ICACCCN)., 2018. http://dx.doi.org/10.1109/ICACCCN.2018.8748516

R. Akhawaji, M. Sedky, and A. H. Soliman, “Illegal Parking Detection Using Gaussian Mixture Model and Kalman Filter,” IEEE Journal., 2017. https://doi.org/10.1109/AICCSA.2017.212

S. Pandya, H. Ghayvat, and K. Kotecha, “Smart Home Anti-Theft System: A Novel Approach for Near Real-Time Monitoring and Smart Home Security for Wellness Protocol,” Applied System Innovation., 2018. http://dx.doi.org/10.3390/asi1040042

R. A. Nadafa, S. M. Hatturea, V. M. Bonala and S. P. Baikb, “Home Security against Human Intrusion using Raspberry Pi,” Procedia Computer Science., Vol 167, Pages 1811-1820., 2020. https://doi.org/10.1016/j.procs.2020.03.200

A. M. Arfi, D. Bal, M. A. Hasan, and Team, “Real Time Human Face Detection and Recognition Based on Haar Features,” IEEE Region 10 Symposium (TENSYMP)., 2020. https://doi.org/10.1109/TENSYMP50017.2020.9230857

M. R. Firmanda, B. S. B. Dewantara, and R. Sigit, “Implementation of Illumination Invariant Face Recognition for Accessing User Record in Healthcare Kiosk,” International Electronics Symposium (IES)., 2020. http://dx.doi.org/10.1109/IES50839.2020.9231644

V. Markapuri, N. Penumajii, and M. Neilsen, “PiBase: An IoT-based Security System Using Google Firebase and Raspberry Pi,” IEEE Journal., 2021. https://doi.org/10.1109/SIET.2018.8693180

R. Bairagi, R. Ahmed, S. A. Tisha, and Team, “A Real-time Face Recognition Smart Attendance System with Haar Cascade Classifiers,” IEEE Journal., 2021. https://doi.org/10.1109/ICIRCA51532.2021.9544872

S. Palaniswamy, and S. Saxena, “A Robust Pose & Illumination Invariant Emotion Recognition from Facial Images using Deep Learning for Human-Machine Interface,” International Conference on Computational Systems and Information Technology for Sustainable Solution (CSITSS)., 2019. http://dx.doi.org/10.1109/CSITSS47250.2019.9031055

B. S. B. Dewantara, M. M. Bachtiar, and S. E. Lantang, “Door Access Control based on Illumination Invariant Face Recognition in Embedded System,” IEEE Journal., 2020. https://doi.org/10.1109/EECCIS49483.2020.9263482

S. Subiyanto, D. Priliyana, M. E. Riyadani, and Team, “Face recognition system with PCA-GA algorithm for smart home door security using Rasberry Pi,” Jurnal Teknologi dan Sistem Kompute., 2020. https://doi.org/10.14710/jtsiskom.2020.13590

N. Hema, and J. Yadav, “Secure Home Entry Using Raspberry Pi with Notification via Telegram,” IEEE Journal., 2020. https://doi.org/10.1109/ICSC48311.2020.9182778

N. A. Othman, and I. Aydin, “A Face Recognition Method In The Internet Of Things For Security Applications In Smart Homes And Cities,” International Istanbul Smart Grids and Cities Congress and Fair (ICSG)., 2018. https://doi.org/10.1109/SGCF.2018.8408934

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KINETIK: Game Technology, Information System, Computer Network, Computing, Electronics, and Control
eISSN : 2503-2267
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