Implementing a Robust License Plate Detection System – A Review

This review study explores the role of license plate detection systems, aiming to develop an intelligent system capable of automatically detecting and reading license plates in images or video streams. Leveraging recent advancements in technology, including Python, OpenCV for image processing, and Tesseract for OCR, this study provides an in-depth analysis of the subject matter. It traces the history of license plate detection, surveys existing systems, and compares the performance of its system against others. Beyond technicalities, this study analyzes the complexities of system implementation, addressing the challenges encountered during the coding process. The comparative analysis evaluates the system's accuracy and efficiency relative to others, revealing the strengths and potential shortcomings of Python, OpenCV, and Tesseract. Concluding with reflective discussions on challenges and directions for future enhancements, this study serves as a comprehensive roadmap for advancing the intelligence of license plate detection systems.