Iraqi Plate Number Recognition Using Single Value Decomposition (SVD)

Abstract

Distinguishing car plate numbers is an important topic of researchers' concern, which assures the process required to be high speed and acceptable accuracy, with the need to access the database and verify it if there was a problem and give a warning if it is necessary. A method is proposed in this paper to distinguish the plate of Iraqi vehicles (new forms), which will prevail in the end, depends on the pre-processing of the image and apply some filters such as (median filter) as well as improving the image before starting the proposed method, which relies on a normalization in the horizontal and vertical direction process and then segment the image into regions. Information is extracted from each region, such as the area that defines the type of vehicle if it is a governmental, private, taxi, or others. The region that characterizes the city as well as Arabic and English, numbers region is segmented and then transform with single value decomposition (SVD) on the image and get features that will send to the database for identification. The proposed method has given a percentage of accuracy of about 90.4 % in the process of discrimination with significant time complexity on average using K-Nearest Neighbor K-NN classifier. It possible to implement the proposed method with application of emergency alarm, to give a warning alert.