A Novel Approach for License Plate Character Segmentation

Abstract

Character segmentation is an important step in license plate recognition (LPR) system. In this paper, a novel character segmentation method of license plate is presented combining Laplacian Transformation, region growing and prior knowledge of license plate. In the proposed methodology, image preprocessing is performed to the license plate at first, and the character region in license plate is enhanced in the following. Then the edges of the characters are detected by using Laplacian Transformation and the candidate regions of characters are located by using region growing algorithm. And the character segmentation regions are determined by using prior knowledge of license plate. Finally the characters are segmented from original license plate and binarization is performed to the characters, which can make it more efficient for character recognition in OCR system. The proposed method in character segmentation is fast and accurate, and is tolerant to license plate with deformations, rotations, plate frame, rivet, the space mark, and so on. And promising results have been obtained in experiments on Chinese license plates.