International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395 -0056
Volume: 04 Issue: 03 | Mar -2017
p-ISSN: 2395-0072
www.irjet.net
License Plate Recognition System for Moving Vehicles Using Laplacian Edge Detector and Feature Extraction Utkarsh Dwivedi1, Pranjal Rajput2, Manish Kumar Sharma3 1UG
Scholar, Dept. of CSE, GCET, Greater Noida, UP, India Scholar, Dept. of CSE, GCET, Greater Noida, UP, India 3Assistant Professor, Dept. of CSE, GCET, Greater Noida, UP, India 2UG
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Abstract - License Plate Recognition is an important field of
research for various reasons. When it comes to recognising the number of a moving vehicle, it has its own challenges needed to be taken care of. In this paper, a real time system has been proposed to locate and identify the license plate of moving vehicles. First, the Otsu method is applied to handle the noise in the captured image of the vehicle. The image is then binarized and the license plate is located using the Laplacian operator. Further the characters in the plate are segmented and normalised. Lastly, characters in the plate are recognised using the Feature Extraction technique. The proposed system has the capability of extracting the characters under different environmental conditions. It can also detect broken characters in the license plate and characters written in multiple scripts. The experimental results applied on the proposed system promise a high efficiency rate . The end of this paper suggests some future advances to the License Plate recognition system. Key Words: Binarization, Laplacian operator, Feature extraction, Segmentation, Normalization
1. INTRODUCTION The number of vehicles on the roads is increasing day by day. This has led to the need and development of latest technologies like Intelligent Transportation Systems (ITS). Vehicle License Plate recognition (VLPR) is a popular application of this technology. This system is widely being used to curb criminal activities around the globe. Other areas using this system include parking facilities, traffic management by ensuring the enforcement of traffic rules and regulations, and automating the task of manually comparing vehicle number plates thereby reducing human efforts . An efficient VLPR system can be used for the real time tracking of the vehicles which proves to be a boon for the traffic management system. Although the plate recognition system seems to be a very useful model, it has certain challenges to be resolved before a solution can be proposed. This system takes as an input the image of the vehicle captured by an optical device ( typically a high resolution camera with night vision capability ). The image received might still be blurred due to the motion of the vehicle. The number plate of the vehicles is sometimes dirty which further increases the complexity of handling such images. Most of the times, The camera captures the © 2017, IRJET
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Impact Factor value: 5.181
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image of the vehicle from a different height which results in tilted images and skewness. Another major issue faced by number plate recognition systems is the different fonts and styles of writing the number . Most of the countries have a standard format of writing the number on a vehicle plate. Due to this fact, it happens that a system designed to recognise the number from the license plate of one country does not work successfully in another. Countries like France, Russia, America are using recognition systems at real time for traffic management. But in India we rely upon manual traffic control and such systems are still under research. A main challenge to design the license plate recognition system in India is that we do not have a standard format of the license plate.The numbers are written in multiple scripts like English, Hindi and sometimes even in other regional languages. The system proposed in this paper can handle numbers written in English as well as in Hindi. A typical VLPR system input and output is shown in the Figure 1. It can be divided into three major processes – License plate localization, character segmentation and finally character recognition. The most crucial step and also the most complex one is the localization of the plate in the image of the vehicle.There are a number of techniques for localization like mathematical morphology, edge detection, wavelet analysis, sliding window technique, connected component analysis etc. The efficiency of the systems using any of these approaches generally varies between 80 to 97 %. It is noteworthy that no single technique is sufficient in itself to segment the number plate in all types of images. Due to the additional issues faced in Indian number plates ie. varying formats and multiple scripts, two techniques have been combined together in the approach presented in this paper for efficient detection of the plate in the image. In India we have two forms of the license plates. Black characters on white background for private vehicles and yellow background for commercial vehicles like taxis, buses, trucks etc.[5] An example of an Indian license plate is HR26 AC 4343 where the first two characters “HR” represent the state, 26 represents the district and the remaining number, AC 4343 is the unique identification number of the vehicle. The license plate recognition system works on the principles derived from Image Processing and Pattern Recognition. ISO 9001:2008 Certified Journal
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