Extraction of Car License Plate Regions Using Line Grouping and Edge Density Methods

In this paper we propose the double chance algorithm as an approach to car license plate extraction. The first algorithm extracts the line segments and groups them based on a set of geometrical conditions. It detects a rectangle at the plate boundary accurately. The second algorithm finds plate regions at which the vertical edges appear densest. We evaluated the double chance framework with and without the verification process. The verification process is performed using the character segmentation module. Using a real-life database collected by the speed enforcement camera, we obtained a high success rate of 99.45%, through use of the double chance approach with verification.