Akhil Kumar Reddy G, Akshay Patil, Anantaraj Katti, Anirudh SS, Bhaskar Reddy P. V


Using technology to detect traffic violators in many developing countries is challenging. And people in these countries really don’t care about rules or doesn’t know that rules exist. This gives inspiration for developing automated stop-line crossing detection system. This paper presents about cost effective system that uses Arduino-UNO and simple camera to detect people standing on zebra crossing when signal turns red. It also prevents the human intervention and detects stop-line violators swiftly. The system is autonomous and can detect more than one vehicle at a time and immediately send notification to violator. The system presents Automatic number plate recognition techniques and some other image manipulation techniques for number plate detection and character detection.




Arduino, Mat lab, Stop-line violation detection, LED, ANPR.

Full Text:



R. Sundar, S. Hebbar and V. Golla, “Implementing Intelligent Traffic Control System for Congestion Control, Ambulance Clearance, and Stolen Vehicle Detection,” IEEE Sensors Journal, 2015.

M. Uddin and T. Shioyama, “Detection of Pedestrian Crossing using Bipolarity and Projective Invariant,” in IAPR Conference on Machine VIsion Applications,, Tsukuba Science City, Japan, 2005.

C. Setchell, “Applications of computer vision to road traffic monitoring,” Ph.D thesis, Computer Vision Group, Bristol University, 1997.

Ludwig Lausser, Friedhelm Schwenker and Gunther Palm, “Detecting zebra crossings utilizing AdaBoost,” In 16th European Symposium on Artificial Neaural Networks Bruges, Belgium, April 23-25, 2008.

J. Sampathkumar and K. Rajamani, “Automatic Detection of Zebra Crossing Violation,” In Proc Fourth International Conference on Signal and Image Processing, ICSIP, Dr. N.G.P. Institute of Technology, Kalapatti, Coimbatore, 2012.

D. Ahmetovic, C. Bernareggi, A. Gerino and S. Mascetti, “ZebraRecognizer: Efficient and Precise Localization of Pedestrian Crossings,” in Proc. 22nd International Conference on Pattern Recognition, 2014.

Rahman, A & Hossain, Md & Mehdi, Md & Nirob, Eftakhar & Uddin, Jia. An Automated Zebra Crossing using Arduino-UNO. Published in International Conference on Computer, Communication, Chemical, Material and Electronic Engineering (IC4ME2), 2018.

Sanyoukta Shukla, Vaishali Sahu, Sakshi Sharma, Prof. Vinay Kumar Patel “Intelligent Traffic Signal with Zebra Crossing Stoppage,” International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, Issue 4, April 2018.

Dragan Ahmetovic, Roberto Manduchi, James M. Coughlan, Sergio Mascetti, “Zebra Crossing Spotter: Automatic Population of Spatial Databases for Increased Safety of Blind Travelers,” Published in ASSETS '15, Computer Science, Engineering, Medicine, 2015.

Young-Woo Seo and Ragunathan (Raj) Rajkumar, “A Vision System for Detecting and Tracking of Stop-Lines,” IEEE 17th international Conference on Intelligent Transportation Systems (ITSC) Qingdao, China, October 8-11, 2014.

“What is an Arduino? -,”, 2015. [online].

Y. Wang, E. K. Teoh, and D. Shen. Lane detection and tracking using b-snake. Image and Vision Computing, 2004

Witold Czajewski, Piotr s Olszewski and Paweł Dąbkowski, “innovative solutions for improving safety at pedestrian crossings”, May 2013.

Takuma Ito, Kyoichi Tohriyama & Minoru Kamata , “Detection of damaged Stop lines on public roads by focusing on Piece distribution of paired Edges”, January 2020

Sagar R.Sarawgi, Mayuri B. Pakhare, Ketaki D. Padhye, Prof. Vikrant A. Agaskar,” Computerized Vehicle Number Plate Recognition and Fine Generation”,Mar-2018

B. Jyothi Sravya, V. Naga Lakshmi, J.Rajasekhar, “Recognition of Vehicle Number Plate and Measure the Distance”, March-2019

“What is MATLAB?-,”




  • There are currently no refbacks.

Copyright (c) 2020 International Journal of Advanced Research in Computer Science