Smart Vehicle Number Plate Scanning System using Optical Character Recognition Strategy

Due to the ever-increasing number of automobiles and transportation systems, it's becoming increasingly difficult for people to keep track of everything. Tracking stolen automobiles and parking tolls are two examples of traffic surveillance. Red-light enforcement is another. To make matters worse, there are several plate types, sizes, rotations, and lighting conditions that must be taken into account throughout the photo capture process, making it a challenging challenge to tackle. This approach is commonly used in toll booths in India. Tollbooth operators lose a great deal of money as a result of widespread misconduct and irregularities at the toll booths. Among the methods for identifying vehicles employed in the proposed approach is the Intelligent Neural Classifier Algorithm. Identifying the registration information in digital frames acquired by a camera is the main focus of this study. Typically, Intelligent Neural Classifier uses an algorithm called Number Plate Classifier Algorithm that mainly used for vehicle identification and Object Character Recognition (OCR) that recognize the character from the license plate. Surveillance systems assess their results and provide a detailed report on each object after it has been identified and as a means of determining whether or not a vehicle is legal or not.