Lucrative Method for License Plate Recognition

Recent research initiatives have addressed the need for improved performance of license plate recognition accuracy that would profit many applications, ITS in particular. Different image processing techniques have been implemented for this purpose specifically edge detection, binarization, segmentation algorithm and tesseract. Each of these steps has its own strengths and weaknesses and it has been proved that using each of these methods individually does not provide a suitable solution that answers today's character recognition needs. This project endeavors to provide improved license plate recognition accuracy by using a novel approach that involves integrating image processing techniques and tesseract according to some constraints. Experimental results prove that this integration provides better recognition accuracy than using traditional techniques for license plate recognition.