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Significant number of researches have been developed recently aroundintelligent system for traffic management, especially, OCR based license platerecognition, as it is considered as a main step for any automatic trafficmanagement system. Good quality data sets are increasingly needed and producedby the research community to improve the performance of those algorithms.Furthermore, a special need of data is noted for countries having specialcharacters on their licence plates, like Morocco, where Arabic Alphabet isused. In this work, we present a labeled open data set of circulation platestaken in Morocco, for different type of vehicles, namely cars, trucks andmotorcycles. This data was collected manually and consists of 705 unique anddifferent images. Furthermore this data was labeled for plate segmentation andfor matriculation number OCR. Also, As we show in this paper, the data can beenriched using data augmentation techniques to create training sets with fewthousands of images for different machine leaning and AI applications. Wepresent and compare a set of models built on this data. Also, we publish thisdata as an open access data to encourage innovation and applications in thefield of OCR and image processing for traffic control and other applicationsfor transportation and heterogeneous vehicle management.

Open data for Moroccan license plates for OCR applications : data collection, labeling, and model construction