Research on Driver’s License OCR Based on CRNN Deep Network

A driver’s license OCR method based on deep learning was designed, in response to the poor performance of traditional methods in driver’s license recognition. Disturbed by equipment issues and external environment, the collected driver’s license images suffer from uneven lighting and tilting, which seriously affect the recognition effect. Carry out driver’s license pre-processing through image enhancement, tilt correction, red stamp localization, text ROI extraction, and character region segmentation. Then, recognize the extracted text regions based on the CRNN deep learning network model. The experimental results show that this method can achieve significantly better recognition performance than traditional methods, with character and field recognition accuracy respectively reaching 92.89% and 8.87%, proving its effectiveness.