To address the current limitations of license plate recognition due to environmental factors such as lighting,angle,and location,research on license plate recognition based on deep learning is constantly deepening.Before li-cense plate localization,the license plate image was preprocessed with grayscale processing,eliminating noise by mean filtering,edge detection,binarization,and multiple features such as geometry and color were combined for lo-calization;Then vertical projection method was used to find the boundary area of each character and perform character segmentation one by one;Finally,a convolutional neural network was created to construct a training and testing set.Through deep learning,license plate characters were recognized and output,and tested and validated on MATLAB with an accuracy of 98.6%.
NETL
NSTL
万方数据
