Extraction of Egyptian License Plate Numbers and Characters Using SURF and Cross Correlation

Abstract

In Egypt, Traffic police or traffic officers usually write down the car license numbers and characters to enforce traffic rules. This is subject to errors of writing or reading the numbers and characters. The proposed work can utilise the advantage of widely spread of mobile phones. Officers can take pictures of car plate licenses and the system converts the pictures of car plate numbers and characters into digital numbers and letters. Arabic characters are challenging because some are very similar to each other's unlike the English characters.. For example, feh (ف) and Qaaf (ق), noon (ن) and ba (ب) difference is minor. The challenge of this work is to extract the Arabic characters and numbers with high accuracy from pictures of new and old car plate design and pictures by regular people. The algorithm has five steps image acquisition, pre-processing, segmentation, feature extraction, and character recognition. To improve the performance time, in the pre-processing step, the developed system tests the cropped area, converts the picture into gray scale, reverses color, and converts it into binary image. Then, it uses morphological operations which is dilation. To improve the accuracy, in the feature extraction step it uses SURF (Speeded Up Robust Features) and cross correlation algorithms in the character recognition. The system is tested with 21 plate pictures and the accuracy is 95% and only one plate picture was missed.