Intelligent collision warning using license plate segmentation

Given the increase of vehicles in traffic, traffic accidents have become a crucial and urgent issue for some countries. Particularly, in heavy traffic conditions, rear-end collisions make up the majority of traffic accidents, which make the traffic jam worse. This article proposes a novel approach to rear-end collision warning systems using areas of license plates acquired with a single camera mounted on a car. The edges of the front car's license plate are segmented and a rectangle is sketched to calculate the area, which is used for estimating distance between the cars. Relative speed of the front car is computed using the differences of the rectangles in a specific time. Distance and relative speed are obtained from the estimated areas of the license plates and transferred to the fuzzy inference system to send a warning signal to the driver for collision prevention, in emergency cases. The experiments are greatly encouraging, indicating that number plate segmentation can be utilized to estimate the distance and fuzzy inference system can be developed to create a warning signal to the drivers.