International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 125 - Number 6 |
Year of Publication: 2015 |
Authors: Kiran Sonavane, Badal Soni, Umakanta Majhi |
10.5120/ijca2015905920 |
Kiran Sonavane, Badal Soni, Umakanta Majhi . Survey on Automatic Number Plate Recognition (ANR). International Journal of Computer Applications. 125, 6 ( September 2015), 1-4. DOI=10.5120/ijca2015905920
Day by day we have been heard about the news of vehicle getting stolen from parking or from any other place in the city. So, to keep track of that stolen vehicle we should have to install the CCTV camera on every signal in the city. Also we have to install the number plate detection system which can detect the number plate of every vehicle on the traffic signal. For detecting the number plate from the moving vehicle there are many algorithm has been developed but still this area always remain evolving each every year, In number plate detection system image processing plays an important role, the system consist of basic operations preprocessing, image conversion from RGB to Gray, apply edge detection, apply morphological operators on same image then extract plate region from image and last process the plate region using OCR (optical character recognition).Every algorithm in this category always follows this basic steps, each algorithm has some pros and cons, because same algorithm cannot be useful for different environmental condition. The Algorithm’s efficiency is totally depends upon the quality of input image. E.g. resolution of camera, intensity of the image, illumination of image, shadow effect etc. In this paper we are focusing on which are different algorithm has been developed so far to improve the efficiency of the number plate detection system.