Automatic License Plate Detection & Recognition using deep learning

The 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: The detected plates are compared to those of the reported vehicles. In order to detect licence we will use Yolo ( You Only Look One) deep learning object detection architecture based on convolution neural networks. This architecture was introduced by Joseph Redmon, Ali Farhadi, Ross Girshick and Santosh Divvala first version in 2015 and later version 2 and 3. Yolo is a single network trained end to end to perform a regression task predicting both object bounding box and object class.