NDLI: Unconstrained licence plate and text localization and recognition

Content Provider	IEEE Xplore Digital Library
Author	Matas, J. Zimmermann, K.
Copyright Year	2005
Description	Author affiliation: Center for Machine Perception, Czech Tech. Univ., Prague, Czech Republic (Matas, J.; Zimmermann, K.)
Abstract	Licence plates and traffic signs detection and recognition have a number of different applications relevant for transportation systems, such as traffic monitoring, detection of stolen vehicles, driver navigation support or any statistical research. A number of methods have been proposed, but only for particular cases and working under constraints (e.g. known text direction or high resolution). Therefore a new class of locally threshold separable detectors based on extremal regions, which can be adapted by machine learning techniques to arbitrary shapes, is proposed. In the test set of licence plate images taken from different viewpoints (-45/spl deg/,45/spl deg/), scales (from seven to hundreds of pixels height) even in bad illumination conditions and partial occlusions, the high detection accuracy is achieved (95%). Finally we present the detector generic abilities by traffic signs detection. The standard classifier (neural network) within the detector selects a relevant subset of extremal regions, i.e. regions that are connected components of a thresholded image. Properties of extremal regions render the detector very robust to illumination change and partial occlusions. Robustness to a viewpoint change is achieved by using invariant descriptors and/or by modelling shape variations by the classifier. The time-complexity of the detection is approximately linear in the number of pixel and a non-optimized implementation runs at about 1 frame per second for a 640 /spl times/ 480 image on a high-end PC.
Starting Page	225
Ending Page	230
File Size	621325
Page Count	6
File Format	PDF
ISBN	0780392159
DOI	10.1109/ITSC.2005.1520111
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-09-16
Publisher Place	Austria
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Licenses Text recognition Detectors Vehicle detection Shape Pixel Lighting Robustness Transportation Monitoring
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
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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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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