Detecting and counting vehicles using adaptive background subtraction and morphological operators in real time systems
محورهای موضوعی : Image, Speech and Signal Processing
Lida Shahmiri
1
(Department of Computer Engineering, Sari Branch, Islamic Azad University, Sari, Iran)
Sajad Tavassoli
2
(Department of Computer Engineering, Sari Branch, Islamic Azad University, Sari, Iran)
Seyed Navid Hejazi Jouybari
3
(Department of Computer Engineering, Sari Branch, Islamic Azad University, Sari, Iran)
کلید واژه: background subtraction, morphological operators, machine vision, image processing, vehicle detection,
چکیده مقاله :
vehicle detection and classification of vehicles play an important role in decision making for the purpose of traffic control and management.this paper presents novel approach of automating detecting and counting vehicles for traffic monitoring through the usage of background subtraction and morphological operators. We present adaptive background subtraction that is compatible with weather and lighting changes. Among the various challenges involved in the background modeling process, the challenge of overcoming lighting scene changes and dynamic background modeling are the most important issues. The basic architecture of our approach is done in 3 steps: 1-background subtraction 2- segmentation module 3- detection of objects and counting vehicles. We present an adaptive background at each frame after using binary motion mask to create instantaneous image of background. To remove noises we use morphological operators and then start to segment images, detect vehicles and count them. Algorithm is efficient and able to run in real-time. Some experimental results and conclusions are presented
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