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License Plate Detection and Recognition Algorithm for Vehicle Black Box

Title
License Plate Detection and Recognition Algorithm for Vehicle Black Box
Author
임준홍
Keywords
License plate; Vehicle Black Box; Support vector machine; k — nearest neighbor; Image Processing
Issue Date
2017-11
Publisher
IEEE
Citation
2017 International Automatic Control Conference (CACS), Page. 1-6
Abstract
Almost every vehicle has currently installed black box since the stored images by black box can be used to investigate the exact cause of the accident. One of the most important aspects in an accident investigation is the license plate detection and recognition as the license plate has information about the driver and car. This paper presents a novel algorithm for license plate detection and recognition using black box image. The proposed license plate recognition system is divided into three stages: license plate detection, individual number and character extraction, and number and character recognition. The Gaussian blur filter is used to remove noise in the image and then we detect the license plate edge using modified Canny algorithm. Second, we determine license plate candidate image using morphology and support vector machine. Finally, we recognize the numbers and characters using k-nearest neighbor classifier. The experimental study results indicate that the license plate detection and recognition algorithm has been successfully implemented.
URI
https://ieeexplore.ieee.org/document/8284273/http://repository.hanyang.ac.kr/handle/20.500.11754/103736
ISBN
978-1-5386-3900-9; 978-1-5386-0341-3
DOI
10.1109/CACS.2017.8284273
Appears in Collections:
COLLEGE OF ENGINEERING SCIENCES[E](공학대학) > ELECTRICAL ENGINEERING(전자공학부) > Articles
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