Vehicle Number Plate Recognition System Using TESSERACT-OCR

Abstract

Abstract: With the increase in the number of vehicles, automated systems to store vehicle information are becoming increasingly necessary. Communication is critical for traffic management and crime reduction, and it cannot be overlooked. Automatic vehicle identification using number plate recognition is a reliable method of identifying vehicles. It requires a lengthy time and a lot of practice to develop satisfactory results using present algorithms that are based on the idea of learning. Even so, accuracy is not a significant concern. It has been devised as an efficient approach for recognizing vehicle number plates, which is included in the suggested algorithm. The technique is intended to address the difficulties of scaling and recognition of the position of characters as long as the accuracy is maintained. Automatic Number Plate Detection is a unique application in Machine Learning as it detects images and converts them to text form. The algorithm detects and captures the vehicle image and extracts the vehicle number plate using image segmentation. The extracted image is later sent to optical character recognition technology for character recognition. This system is implemented in areas like traffic surveillance, military zones, apartments, etc. Keywords: Optical Character Recognition, tesseract ocr, matplotlib, Number Plate Recognition.