Accident Detection & Traffic Regulation Using Image Processing

Accident Detection & Traffic Regulation Using Image Processing
Author(s):
RUTUJA VIJAYKUMAR MANE, P. B. GHEWARI
Keywords:
Convolutional Neural Network, Traffic Signal Control, openCV, Image denoising; object detection
Abstract
As the problem of urban traffic congestion spreads, there is a pressing need for the introduction of advanced technology and equipment to improve the state-of-the-art of traffic control. Traffic problems now-a-days are increasing because of the growing number of vehicles and the limited resources provided by current infrastructures. The simplest way for controlling a traffic light uses timer for each phase. Another way is to use electronic sensors in order to detect vehicles, and produce signal that cycles. Proposed system control the traffic light by image processing. The system will detect vehicles through images instead of using electronic sensors embedded in the pavement. A camera will be installed alongside the traffic light. It will capture image sequences. The image sequence will then be analyzed using digital image processing for vehicle detection, and according to traffic conditions on the road traffic light can be controlled.
Article Details
Unique Paper ID: 156641 Publication Volume & Issue: Volume 9, Issue 4 Page(s): 334 - 338
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