Chinese License Plate Recognition Based on OpenCV and LPCR Net

Abstract

Aiming to solve the low accuracy and slow speed of Chinese character recognition in the traditional license plate recognition, a method of license plate location, character segmentation and recognition using computer vision library OpenCV and license plate character recognition convolutional neural network (LPCR Net) is proposed. First, the RGB three-channel image is separated from the input image, and the input image is binarized by calculating the color characteristics of the license plate, then the multiple connected regions are obtained through morphological operations such as expansion and closure, the license plate location is completed via calculating the standard license plate aspect ratio and area; secondly, the horizontal and vertical projection method used in the traditional license plate character segmentation is improved to complete the license plate character segmentation, which improves the accuracy and speed of Chinese character segmentation; finally, the license plate character recognition is completed based on LPCR Net, and the recognition accuracy rate reaches 98.33%, which is 3.11% higher than that of AlexNet. Experimental results show that the proposed method can effectively improve the accuracy of license plate location, character segmentation and recognition.