A Novel Deep Learning based IoT Enabled Computerized Vehicle Number Plate Recognition System using OCR Principles

A kind of intelligent transportation and detecting method is the license plate recognition system. The system can automatically recognize and read the license id of a vehicle’s number plate from digitally taken photographs thanks to this mix of technologies. The term “automatically capturing the license plate” refers to a technique that detects license plates and converts their pixel data into plain text or ASCII text. Modified Learning based Character Recognition (MLCR) is an analytical operation-based approach to vehicle number plate recognition that is part of this system. For the purpose of evaluating the suggested scheme’s efficiency, it is cross-validated with the traditional learning model known as Convolution Neural Network (CNN). The primary goal is to properly recognize and translate a specific vehicle’s license plate by using and combining several morphological techniques. Image enhancement, grayscale transformation, filtering, edge detection, and number plate extraction from vehicle images are some of the operations upon which this is built. Following the completion of the aforementioned processes, the segmentation process is being utilized to detect the text on the number plate. This is achieved by utilizing template matching and optical character recognition. From a photograph of the car, our method can swiftly and reliably deduce the license plate.