License plate recognition technology uses OpenCV(open source computer vision library) computer open source machine vision library to process the image to extract the license plate information contained in the image to achieve the purpose of license plate recognition. By using the HAAR feature, the AdaBoost (Adaptive Boosting) classifier is trained to find the license plate area in the picture; At the same time, the Sobel operator is used for edge detection and other operations to find the license plate area; Finally, the SVM(Support Vector Machine) algorithm is used to finalize the two suspected license plate areas; After the confirmation of the license plate area, character division and other operations are performed to separate characters; The trained back propagation (BP) neural network is used to identify the characters and finally output the license plate information. The research results show that it can effectively identify license plate information and has great practical value.