International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 10 Issue: 06 | Jun 2023
p-ISSN: 2395-0072
www.irjet.net
Automatic Fetching of Vehicle details using ANPR Camera Ankit Kumar1, Sayon Samadar2, Rupam Saha3 , Sukanya Roy, Swagata Bhatarcharya Department of Electronics and Communication Engineering, Guru Nanak Institute of Technology, Sodepur, West Bengal ---------------------------------------------------------------------***--------------------------------------------------------------------iv. Character segmentation. Abstract - Traffic Management of the vehicle nowadays becomes necessary due to the large number of vehicles. Besides this when something wrong happens with the vehicle many times it becomes difficult to recognize the number of vehicles because many times its noisy and of low illusion. This must be done carefully otherwise the reorganization of numbers present on the vehicle becomes wrong. Many authors provide different methodology for the recognition of the number plates. All the authors try to identify the numbers by implementing systems in different languages and provide the result. In this paper, we introduce the single camera-based number recognition system used for this system that recognizes vehicle number plates on one lane by using a single camera. Due to the increased cost of the installation and maintenance thereof, there is a growing need for a multi-lane-based number recognition system. When the single camerabased number recognition system is used for multi-lane recognition, the recognition rate is lowered due to a difference in vehicle image size among lanes and a lowresolution problem.
v. Character recognition. The initial step of ANPR system is location of the vehicle and capturing the image of vehicle, the second step is the localization of Number Plate and then the extraction of vehicle Number Plate is done. The final step uses image segmentation strategy. Segmentation is done for individual character recognition. This sums up the purpose of the ANPR camera in this system. Next, the number is searched through the database available at the traffic control room. This database includes all the information regarding the owner. This process is followed for multiple vehicles in the traffic at a given time simultaneously. Finally, the vehicles disobeying the traffic rules are marked and the numbers are sent to the official on-duty to check. This part is done by the use of text to speech converters used in the system. 1.1 Methodology
Therefore, in this study, we applied a character extraction algorithm using connected vertical and horizontal edge segments-based labeling to improve multi-lane vehicle number recognition rate and thereby to allow application of the single camera-based system to multi-lane roads. Key Words: Automatic Number Plate Recognition, Character recognition, Multi-lane Detection, Vehicle Image Processing, Real-Time Traffic Information, Template Matching, Edge Detection.
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The process of ANPR starts with identifying a registration plate of the vehicle.
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It involves the algorithms used which are able to identify the rectangular area of the registration plate from an original picture.
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This is achieved through video cameras capturing images that are analyzed using Optical Character Recognition (OCR), which scans each group of pixels within the images and estimates whether or not it could be a letter and replaces the pixels with the ASCII* code for the letter. (*)
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ANPR cameras need to be of a special type and set up within certain designated parameters.
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The identification and recognition process takes place in four phases mainly.
1.INTRODUCTION ANPR system is an image-processing innovation which is used to recognise vehicles by their license plates. This Recognition System also takes out the abnormal state information from the digital image captured. The useless homogeny includes the dimension and the outline of the License Plate. The ANPR system consists of following steps: -
(1) Preprocessing of Image
i. Vehicle image capture.
(2)Localizing Registration Plate
ii. Pre-processing.
(3) Segmentation of Characters
iii. Number plate extraction.
(4) Recognition of Actual number plate.
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