Localized Background Subtraction Feature-Based Approach for Vehicle Counting

El-Khoreby, Mohamed A.; Abu-Bakar, S. A. R.; Mokji, Musa Mohd; Omar, Syaril Nizam; Malik, Najeeb ur Rehman

doi:10.1109/icsipa45851.2019.8977795

Cited by 2 publications

(1 citation statement)

References 3 publications

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“…The background subtraction method has disadvantages in terms of lighting, but it is also difficult to detect objects that move very fast. Therefore, this system is made in real time by increasing the frames per second so that the system always updates the background by itself and is able to cover other shortcomings [11]. Formula 1 is the background substraction calculation formula.…”

Section: Methodsmentioning

confidence: 99%

Implementation of Traffic Monitoring Technology Using Smart Surveillance in Intelligent Transportation System

Rimra,

Lifwarda,

Komanjali

et al. 2023

Int. J. of Adv. Sci. Comp. and Eng.

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Currently transportation is very attached to human life, almost every family and even every adult human being has a vehicle as a means of transportation. Based on this, a conclusion can be drawn that population growth will trigger an increase in the number of vehicles in Indonesia. The implementation of Traffic Monitoring Using Smart Surveillance in the Intelligent Transportation System is research on information and communication technology in the transportation system in order to increase mobility, reduce congestion resulting from the buildup of vehicles in one lane, and be taken into consideration by road users before crossing a road section. This system uses the Background Subtraction method, and object detection. This system was created by utilizing OpenCV and Python programming language. This research obtained an accuracy of 93.1% on camera A and 93.5% on camera B in calculating passing vehicles in the test using simulations monitored via cameras in real time.

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Section: Methodsmentioning

confidence: 99%