A novel algorithm for license plate location based on the RGB features and the texture features

Sheng-Feng Yu, Zhi-Jiang Xu, Biaobiao Zhang, Li-Min Meng, Ke-Lin Du

Abstract: In order to locate license plates in a complex environment, we develop a novel license plate location algorithm by combing the texture features of plate and features in the RGB color space. A picture is first filtered with a custom convolutional kernel in order to enhance the texture of characters, followed by morphological processing to get region set A. The RGB features of the license plate are then extracted from the picture, and region set B is obtained by performing morphological processing. Region set C is obtained by performing intersection operation of A and B. Finally, through elimination of pseudo-regions, the real license plate region is located. Evaluation of this algorithm on pictures sampled from different illuminations and road conditions demonstrates an accuracy of 98%.