Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/1910
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dc.contributor.authorKodwani, L-
dc.contributor.authorMeher, S-
dc.date.accessioned2013-04-12T05:02:37Z-
dc.date.available2013-04-12T05:02:37Z-
dc.date.issued2013-04-
dc.identifier.citationInternational Joint Conference on Advance Engineering & Technology (ICAET), April 9, 2013, Raipuren
dc.identifier.urihttp://hdl.handle.net/2080/1910-
dc.descriptionCopyright belongs to the Proceedings Publisher.en
dc.description.abstractIn this paper we present full-featured vehicle detection, tracking and licence plate recognition system. It consists of vehicle detection, licence plate extraction and a character recognition module. Here first foreground estimation is done by Gaussian mixture model then proposing a real time and robust method of license plate extraction based on block variance technique. License plate extraction is an important stage in license plate recognition for automated transport system. The Extracted license plates are segmented into individual characters by using a region-based approach. The recognition scheme combines adaptive iterative thresholding with a template matching algorithm. The method is invariant to illumination and is robust to character size and thickness, skew and small character breaks. The major advantages of our system are its real-time capability and that it does not require any additional sensor input (e.g. from infrared sensors) except a video stream. We evaluate our system on a large number of vehicle images. Experimental results demonstrate the great robustness and efficiency of our method.en
dc.format.extent1002166 bytes-
dc.format.mimetypeapplication/pdf-
dc.language.isoen_US-
dc.subjectBackground estimationen
dc.subjectLicense plate recognitionen
dc.subjectSurveillance Systemen
dc.subjectTrackingen
dc.subjectVehicle detectionen
dc.subjectVideo indexingen
dc.titleAutomatic License Plate Recognition in Real Time Videos using Visual Surveillance Techniquesen
dc.typeArticleen
Appears in Collections:Conference Papers

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