Volume 12, Number 2
Mustapha Saidallah, Fatimazahra Taki, Abdelbaki El Belrhiti El Alaoui and Abdeslam El Fergougui, Moulay Ismail University, Morocco
The Intelligent Transportation Systems (ITS) are the subject of a world economic competition. They are the application of new information and communication technologies in the transport sector, to make the infrastructures more efficient, more reliable and more ecological. License Plates Recognition (LPR) is the key module of these systems, in which the License Plate Localization (LPL) is the most important stage, because it determines the speed and robustness of this module. Thus, during this step the algorithm must process the image and overcome several constraints as climatic and lighting conditions, sensors and angles variety, LPs’ no-standardization, and the real time processing. This paper presents a classification and comparison of License Plates Localization (LPL) algorithms and describes the advantages, disadvantages and improvements made by each of them.
License Plate Localization, LPL constraints, performance, real time, multi-localization, convolutional neural network, deep learning.