A New Method for Positioning Persian License Plates

Today the necessity of using smart systems which are able to diagnose the cars plague correctly from pictures is felt more than ever by expanding the number of vehicles. In License Plate Recognition systems, detecting plaque location is considered the most important phase so that the correct rate of it, will affect all subsequent phases. There are different images with different resolutions and sever changes in the size of images which taken through being far or near to the camera, it makes many existing methods face problems or longer processing. In this paper a new method is suggested based on simulation concepts which used in spectra analysis for accurate and fast position detection by using edge concepts and morphological operators in image processing. The suggested method is a compound method and fast enough and it extracts the plague location from vehicle image correctly. The algorithm is implemented in MATLAB and the results obtained agreed with theoretical predictions. The proposed method has 93.3 % of correct detection rate and 150 ms of processing time. Index Terms—LPR, Edge detection, Morphological operators, Spectral analysis. I. INTRODUCTION Intelligent Transportation Systems (ITSs) have many interactions with the people lives. On the other hand, License Plate Recognition systems (LPRS) play a major role in automatic monitoring of traffic rules and maintaining law enforcement on public roads. LPRSs are considered as a branch of machine vision that they extract and read plague by using of image processing. In addition, these systems are used in several other cases, such as identifying stolen vehicles and car racing. These systems usually include a digital camera, a software module which is used connecting the camera to the License plate recognition software, and detecting, extracting software. The camera prepares images by using a predetermined quality and passes them to software modules. Plate recognition systems perform this task using three steps including finding location of plate in the vehicle image; plate segmentation; and finally character recognition. The plate region extraction is the most challenging part of the entire system and different method has been proposed for it. License plate positioning quality has influence on the accuracy of license plate recognition. The algorithms which are used to identify the license plate location can generally be divided into four general categories: methods based on classification, methods based on edge detection, methods based on morphological operators, and methods based on spectral analysis. The most popular method which is