IJCOT-book-cover International Journal of Computer & Organization Trends  (IJCOT)          
 
© 2021 by IJCOT Journal
Volume - 11 Issue - 4
Year of Publication : 2021
Authors : Hasan Thabit Rashid, Prof. Dr. Israa Hadi Ali
DOI : 10.14445/22492593/IJCOT-V11I4P301

Citation

MLA Style:Hasan Thabit Rashid, Prof. Dr. Israa Hadi Ali.  "Traffic Violations Detection Review based on Intelligent Surveillance Systems" International Journal of Computer and Organization Trends 11.4 (2021): 1-9. 

APA Style:Hasan Thabit Rashid, Prof. Dr. Israa Hadi Ali.(2021) Traffic Violations Detection Review based on Intelligent Surveillance Systems International Journal of Computer and Organization Trends, 11(4), 1-9

Abstract

Currently, IT develops our life superficially and quickly has become faster and more complicated. However, This paper offers a brief study of previous techniques for violation of vehicles on surveillance systems expressed by suitable processing methodologies to intelligent surveillance techniques (such as Wi-Fi sensors, image processing, machine learning, and object detection based on appearance and motion) and the use of different types of cameras networks(fixed, motorize, and PTZ) and area topologies(efficient FOVs). This study provides a quick look at various techniques that alert individuals and users to vehicle anomalous movements in the environments of traffic and intelligent systems.

References

[1] Nilsson, F. Intelligent Network Video: Understanding Modern Video Surveillance Systems. CRC Press. Second edition. (2017).

[2] Aghajan, H., &Cavallaro, A. (Eds.). Multi-camera networks: principles and applications. Academic Press. (2009).

[3] Pandey, S., Jain, R., & Kumar, S. An Efficient Data Aggregation Algorithm with Gossiping for Smart Transportation System. In International Conference on Communication, Networks, and Computing (191-200). Springer, Singapore. (2018).

[4] Ahmad, N., O`Nils, M., &Lawal, N. A taxonomy of visual surveillance systems. (2013).

[5] Kolekar, M. H. Intelligent Video Surveillance Systems: An Algorithmic Approach. CRC Press. (2018).

[6] Khan, M. U. K., Shafique, M., & Henkel, J. Energy Efficient Embedded Video Processing Systems: A Hardware-Software Collaborative Approach. Springer. (2017).

[7] Ahmed, S. H., Yaqub, M. A., Bouk, S. H., & Kim, D. SmartCop: Enabling smart traffic violations ticketing in vehicular named data networks. Mobile Information Systems, (2016).

[8] Aarthy, D. K., Vandanaa, S., Varshini, M., &Tijitha, K. Automatic identification of traffic violations and theft avoidance. In 2016 Second International Conference on Science Technology Engineering and Management (ICONSTEM) (2016) (72-76). IEEE.

[9] Mehboob, F., Abbas, M., & Rauf, A. Mathematical model-based traffic violations identification. Computational and Mathematical Organization Theory,(2018) 1-17.

[10] Sarikan, S. S., &Ozbayoglu, A. M. Anomaly Detection in Vehicle Traffic with Image Processing and Machine Learning. Procedia Computer Science, 140 (2018) 64-69.

[11] Yang, Z., & Pun-Cheng, L. S. Vehicle detection in intelligent transportation systems and its applications under varying environments: A review. Image and Vision Computing, 69 (2018) 143-154.

[12] Kurmasha, H. T. R., Alharan, A. F. H., Der, C. S., &Azami, N. H. Enhancement of Edge-based Image Quality Measures Using Entropy for Histogram Equalization-based Contrast Enhancement Techniques. Engineering, Technology & Applied Science Research, 7(6) (2017) 2277-2281.

[13] Sharma, K. Feature-based efficient vehicle tracking for a traffic surveillance system. Computers & Electrical Engineering, 70 (2018) 690-701.

[14] Maggio, E., &Cavallaro, A. Video tracking: theory and practice. John Wiley & Sons. (2011).

[15] Zheng, H., Chang, W., & Wu, J. Traffic flow monitoring systems in smart cities: Coverage and distinguishability among vehicles. Journal of Parallel and Distributed Computing, 127 (2019)224-23.

[16] Kurmasha, H. T. R., &Alharan, A. F. A Review and New Subjective Evaluation Experiment of Objective Metrics used to Evaluate Histogram Equalization-based Contrast Enhancement Techniques. (2017)

[17] Rashid, H. T., & Ali, I. H., Multi-Camera Collaborative Network Experimental Study Design of Video Surveillance System for Violated Vehicles Identification. In Journal of Physics: Conference Series 1879(2) 022090. IOP Publishing. (2021).).

Keywords

computer vision, intelligent surveillance systems,multi-camera networks, traffic control, video tracking.