Captiosus: Rear End Collision and Accident Alert System Using Video Processing

Abstract

The population of the world is increasing and with this the number of vehicles on road is also increasing exponentially. Every household has at least 2 or 3 vehicles. This automatically leads to the rise the number of on-road accidents, in spite of government laws being enforced for the safety of the riders. This is because traffic rules are not being followed properly and many a times accidents occur with no fault of one of the driver. This is due to the fact that most accidents tend to happen when there is collision at the rear end. Hence there is a need of technology in vehicles which detects probable accidents by taking into account various factors around the vehicle and sending appropriate alerts.  Keeping all this in mind, this paper proposes a system that uses image processing to detect the vehicles approaching from the rear end and alert the driver accordingly. Image processing is the analysis and manipulation of a digitized image, especially in order to improve its quality. We propose an algorithm which can detect vehicles from images with varying levels of brightness.  If implemented in ITS (Intelligent transport system), this algorithm can revolutionize accident alert and detection systems and make them more effective.