License Plate Number Recognition Using Support Vector Machine (SVM)

Abstract

Detecting license plates number from vehicle is a modern technology that being use for various purpose such as in traffic application and various security such as control access to enter a car park, find stolen vehicle and gathering traffic flow statistic. However, there is a problem if a user lost their access card, and they are not allowed enter a car park. Due to this problem, it can cause traffic jammed. Besides that, during heavily raining, the barriers gate will be opened to allow staffs, postgraduate students, and visitors to enter the parking lot without scan the access card. Therefore, in this study, license plate number recognition (LPNR) with support vector machine (SVM) is applied. It is used in managing the control access to enter a secure parking lot. The aims of this study are to develop an algorithm for LPNR using multiclass SVM and apply the developed algorithm on a set of number plate images. 26 sets of number plate images will be used in the experimental studies. In developing the algorithm, it consists of seven steps which; input image, pre-processing image, license plate localization, pre-recognition of character segmentation, character enhancement, character recognition and storing recognized image. The experimental processes are successfully applied using MATLAB R2020A. Based on the result, it is shown that 77% license plate number images have been successful being recognized using the developed algorithm. As conclusion, the developed algorithm which is SVM in detect a license plate number of images are applied and plate number being recognized.