MATLAB Implementation of License Plate Recognition System

For my graduation project, I independently developed a comprehensive license plate recognition system using MATLAB. This program automatically detects and recognizes characters on vehicle license plates, making it applicable for various real-world scenarios such as parking lot management systems, traffic monitoring applications, and automated vehicle identification solutions. The implementation includes sophisticated image processing algorithms for plate localization, character segmentation, and optical character recognition (OCR).

In my research, I conducted in-depth analysis of license plate recognition algorithm optimization and enhancement techniques to improve both recognition accuracy and processing speed. The MATLAB code implements key functions including image preprocessing (using imadjust and medfilt2 for contrast enhancement and noise reduction), plate region detection through edge detection and morphological operations (employing edge and imclose functions), and character classification using template matching or machine learning approaches. My thesis provides detailed explanations of these algorithms along with experimental results and performance analysis comparing different recognition methodologies.

For students working on graduation projects, my research offers valuable reference material demonstrating how to implement license plate recognition technology and explore its applications in broader contexts. The code structure follows modular design principles, separating plate detection, character segmentation, and recognition into distinct functional units for easier understanding and modification.