Iraqi Kurdistan Vehicle License Plate Recognition System based on Client-server Network

Shakhawan H. Wady1, Faraidoon H. Ahmad2 , Hawkar O. Ahmed3

1 Department of Mathematics, School of Science Education, University of Sulaimani, Kurdistan Region, Iraq

2 Department ofInformation Technology(IT),Faculty of Medical Sciences, School of Pharmacy, University of Sulaimani, Kurdistan Region, Iraq

3 Department of Statistic & Computing, College of Commerce, University of Sulaimani, Kurdistan Region, Iraq

Original: 20 February2016,Revised: 13 July 2016,Accepted: 16 October2016,Published online: 20March 2017

DOI: https://doi.org/10.17656/jzs.10603

Abstract

Vehicle license plate recognition (VLPR) system has a wide range of applications in real life, such as parking lots, private and public entrances, theft and border control. This paper presents a system overview of client-server license plate recognition system for vehicles in Kurdistan Region of Iraq besides, the vehicle type and city in each plate is identified. The client/server model consist of two components called client-side and server-side. The images are provided by the client side and will be sent over the server to be processed. The process of license plate recognition is done in the server side with the integration with the Matlab software. The proposed recognition system is developed based on digital images and the main component of the system consist of: preprocessing, license plate detection, segmentation and recognition process. A preprocessing step using image enhancement, filtering, and adaptive thresholding is employed. For localizing and extracting the license plate region, Haar wavelet transformation and edge detection algorithm are used. license plate number segmentation is carried out using bounding box based morphological operations and finally color histogram technique and correlation coefficient based similarity measurement are used for recognition task. The experimental results show that our proposed system for the license plate detection and recognition process have obviously higher recognition accuracy rate.

Key Words: 

License plate detection; Character recognition, Client-server network, Edge detection, Haar Transform, Bounding box, Correlation, Color histogram

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