NDLI: Locating multiple license plates using scale, rotation, and colour-independent clustering and filtering techniques

Content Provider	IET Digital Library
Author	Bhargav, Rohit Deshpande, Parag
Abstract	A license plate (LP) can help identify a motor vehicle. However, no common standard for LP exists across countries, and even within a country, significant LP variations are observed. In addition, environmental factors cause uncontrolled plate and character variations. It is, therefore, a challenge to design a robust and universal license plate recognition (LPR) system which works for multiple countries, for different types of vehicles, and for different styles of LPs. This study presents a novel approach for locating LP based on the use of multiple clustering and filtering techniques applied to the geometrical properties of LP characters. The proposed approach is independent of the size, rotation, and colour of the LP and can be used to locate single or multiple LP of different styles of different vehicles and of different countries. The approach has been validated using the standard Media-lab and application-oriented license plate (AOLP) datasets as well as on datasets of vehicles from other countries. The approach achieved an average success ratio of 93.42% for locating LPs from both the Media-lab and the AOLP dataset and is higher than the results of previously published methods which evaluated their performance over the same datasets.
Starting Page	2335
Ending Page	2345
Page Count	11
ISSN	17519659
Volume Number	13
e-ISSN	17519667
Issue Number	Issue 12, Oct (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/13/12
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2018.6237
Journal	IET Image Processing
Publisher Date	2019-08-07
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Application-oriented License Plate Datasets Character Recognition Character Variations Colour-independent Clustering Common Standard Computer Vision And Image Processing Technique Edge Detection Environmental Factors Feature Extraction Filtering Technique Image Recognition Locating LPs LP Characters Motor Vehicle Multiple Clustering Multiple Countries Multiple License Plate Object Detection Road Vehicle Significant LP Variations Standard Media-lab Traffic Engineering Computing Uncontrolled Plate
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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