Knowledge Agora



Similar Articles

Title An Adaptive Video-based Vehicle Detection, Classification, Counting, and Speed-measurement System for Real-time Traffic Data Collection
ID_Doc 44579
Authors Ghosh, A; Sabtrj, MS; Sonet, HH; Shatabda, S; Farid, DM
Title An Adaptive Video-based Vehicle Detection, Classification, Counting, and Speed-measurement System for Real-time Traffic Data Collection
Year 2019
Published
Abstract Intelligent Transportation System (ITS) is an integral part for efficiently and effectively managing road-transport network in metros and smart cities. ITS provides several important features including public transportation management, route information, safety and vehicle control, electronic timetable and payment system etc. In this paper, we have designed and developed an adaptive video-based vehicle detection, classification, counting, and speed-measurement tool using Java programming language and OpenCV for real-time traffic data collection. It can he used for traffic flow monitoring, planning, and controlling to manage transport network as part of implementing intelligent transport management system in smart cities. The proposed system can detect, classify, count, and measure the speed of vehicles that pass through on a particular road. It can extract traffic data in csv/xml format from real-time video and recorded video, and then send the data to the central data-server. The proposed system extracts image frames from video and apply a filter based on the user-defined threshold value. We have applied MOG2 background subtraction algorithm for subtracting background from the object, which separates foreground objects from the background in a sequence of image frames. The proposed system can detect, classify, and count vehicles of different types and size as a plug & play system. We have tested the proposed system at six locations under different traffic and environmental conditions in Dhaka city, which is the capital of Bangladesh. The overall average accuracy is above 80% for classifying all types of vehicles in Dhaka city.
PDF

Similar Articles

ID Score Article
37334 Trivedi, J; Devi, MS; Dhara, D Vehicle Counting Module Design in Small Scale for Traffic Management in Smart City(2018)
44747 Megha, HN; Goudar, RH Next Generation Intelligent Traffic Management System and Analysis for Smart Cities(2017)
43882 Komasilovs, V; Zacepins, A; Kviesis, A; Estevez, C Traffic Monitoring using an Object Detection Framework with Limited Dataset(2019)
41868 Othman, NA; Saleh, ZZ; Ibrahim, BR A Low-Cost Embedded Car Counter System by using Jetson Nano Based on Computer Vision and Internet of Things(2022)
38379 Rathore, MM; Son, H; Ahmad, A; Paul, A Real-time video processing for traffic control in smart city using Hadoop ecosystem with GPUs(2018)Soft Computing, 22, 5
41058 Sofwan, A; Surur, FA; Arfan, M; Handoyo, E; Alvin, ASY; Somantri, M; Enda, WS Implementation of Vehicle Traffic Analysis Using Background Subtraction in The Internet of Things (IoT) Architecture(2018)
43800 Anandhalli, M; Baligar, P; Saraf, SS; Deepsir, P Image projection method for vehicle speed estimation model in video system(2022)Machine Vision And Applications, 33, 1
36062 Wong, SF; Mak, HC; Ku, CH; Ho, WI Developing Advanced Traffic Violation Detection System with RFID Technology for Smart City(2017)
43506 Kutlimuratov, A; Khamzaev, J; Kuchkorov, T; Anwar, MS; Choi, A Applying Enhanced Real-Time Monitoring and Counting Method for Effective Traffic Management in Tashkent(2023)Sensors, 23, 11
40818 Lingani, GM; Rawat, DB; Garuba, M Smart Traffic Management System using Deep Learning for Smart City Applications(2019)
Scroll