Research on vehicle license plate detection and recognition system based on threshold segmentation

License plate detection plays a relatively important role in highway traffic safety management and community parking lot management. This paper studies an algorithm for license plate detection. Firstly, the license plate image is preprocessed using grayscale binarization and edge detection. Then, the image is corrected through mathematical morphology and Radon transform. Finally, the purpose of license plate detection is achieved by segmenting characters and template matching. Experimental results show that the detection accuracy of the algorithm for square license plate images and tilted license plate images is 97.5% and 87.5%, respectively, with an average detection rate of 91.17%. The conclusion indicates that the algorithm in this paper can provide an effective tool for license plate detection systems in various fields.