A New Approach for License Plate Detection and Localization: Between Reality and Applicability


  •  Akram Moustafa    
  •  Mohammed-Issa Mousa Jaradat    

Abstract

License Plate Detection and Localization (LPDL) is known to have become one of the most progressive and growing areas of study in the field of Intelligent Traffic Management System (ITMS). LPDL provides assistance by being able to specifically locate a vehicle’s number plate which is an essential part of ITMS, that is used for automatic road tax collection, traffic signals defilement implementation, borders and payments barriers and to monitor unlike activities. Organizations can deploy the number plate detection and recognition system to track their vehicles and to monitor each of them in their vital business activities like inbound and outbound logistics, find the exact location of their vehicles and organize entrance management. A competent algorithm is proposed in this paper for number plate detection and localization based on segmentation and morphological operators. Thus, the proposed algorithm it works on enhancing the quality of the image by applying morphological operators afterwards to segment out license plate from the captured image. No assumptions about the license plate color, style of font, size of text and type of material the plate is made of. The results reveal that the proposed algorithm works perfectly on all kinds of license plates with 93.43% efficiency rate. 



This work is licensed under a Creative Commons Attribution 4.0 License.