Automatic License Plate Detection
IntroductionThe massive integration of information technologies, under different aspects of the modern world, has led to the treatment of vehicles as conceptual resources in information systems. Since an autonomous information system has no meaning without any data, there is a need to reform vehicle information between reality and the information system.This can be achieved by human agents or by special intelligent equipment that will allow identification of vehicles by their registration plates in real environments. Among intelligent equipment, mention is made of the system of detection and recognition of the number plates of vehicles.The system of vehicle number plate detection and recognition is used to detect the plates then make the recognition of the plate that is to extract the text from an image and all that thanks to the calculation modules that use location algorithms, segmentation plate and character recognition.The detection and reading of license plates is a kind of intelligent system and it is considerable because of the potential applications in several sectors which are quoted:
Licence plate detectionIn order to detect licence we will use Yolo ( You Only Look One ) deep learning object detection architecture based on convolution neural networks. First, we prepared a dataset composed of 700 images of cars that contains Tunisian licence plate, for each image, we make an xml file ( Changed after that to text file that contains coordinates compatible with Darknet config file input.
Licence plate segmentationNow we have to segment our plate number. The input is the image of the plate, we will have to be able to extract the unicharacter images. The result of this step, being used as input to the recognition phase, is of great importance. In a system of automatic reading of number plates.
Segmentation is one of the most important processes for the automatic identification of license plates, because any other step is based on it. If the segmentation fails, recognition phase will not be correct.To ensure proper segmentation, preliminary processing will have to be performed.