Vehicle VIN code recognition based on deep learning and OCR

This paper presents a deep learning-based OCR system for Vehicle Identification Number (VIN) recognition, addressing the limitations of traditional methods in complex environments. VINs are critical for vehicle management, but conventional techniques often fail under poor lighting, reflections, dirt, or tilt angles. The system uses high-resolution cam-eras and image preprocessing, like grayscale conversion, to improve image quality. Deep learning models, including Long Short-Term Memory (LSTM) networks, extract key features for accurate VIN recognition. Additionally, character verification ensures correct formatting and distinguishes confusing characters, improving accuracy and preventing misuse of vehicle resources.