Model-based character recognition in low resolution Kuhl, Annika, Tan, Tele and Venkatesh, Svetha 2008, Model-based character recognition in low resolution, in ICIP 2008 : Proceedings of the International Conference on Image Processing, IEEE, Piscataway, N. J., pp. 1001-1004. Attached Files Name Description MIMEType Size Downloads venkatesh-modelbased-2008.pdf Published version application/pdf 213.38KB 121 Title Model-based character recognition in low resolution Author(s) Kuhl, Annika Tan, Tele Venkatesh, Svetha orcid.org/0000-0001-8675-6631 Conference name International Conference on Image Processing (2008 : San Diego, Calif.) Conference location San Diego, Calif. Conference dates 12-15 Oct. 2008 Title of proceedings ICIP 2008 : Proceedings of the International Conference on Image Processing Editor(s) [Unknown] Publication date 2008 Conference series International Conference on Image Processing Start page 1001 End page 1004 Total pages 4 Publisher IEEE Place of publication Piscataway, N. J. Keyword(s) number plate recognition optical character recognition text processing Summary We propose a combined character separation and recognition approach for low-resolution images of alphanumeric text. By synthesising the image formation process a set of low-resolution templates is created for each character. Cluster algorithms and normalised cross-correlation are then applied to match these templates and thereby allowing both character separation and recognition to be achieved at the same time. Thus characters are recognised using their low-resolution appearance only without applying image enhancement methods. Experiments showed that this approach is able to recognise low-resolution alphanumeric text of down to 5 pixels in size. Notes This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. ISBN 1424417651 9781424417650 ISSN 1522-4880 Language eng Field of Research 089999 Information and Computing Sciences not elsewhere classified Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences HERDC Research category E1.1 Full written paper - refereed Copyright notice ©2008, IEEE Free to Read? Yes Persistent URL http://hdl.handle.net/10536/DRO/DU:30044570 Document type: Conference Paper Collections: School of Information Technology Open Access Collection Related Links Link Description Connect to published version (restricted access) Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au. Versions Version Filter Type Fri, 20 Apr 2012, 11:32:55 EST Thu, 26 Apr 2012, 15:47:07 EST Thu, 26 Apr 2012, 15:50:22 EST Tue, 01 May 2012, 15:47:57 EST Tue, 24 Jun 2014, 08:36:11 EST Tue, 06 Sep 2016, 18:43:26 EST Sat, 21 Oct 2017, 02:02:45 EST Tue, 05 Dec 2017, 12:31:21 EST Fri, 07 Sep 2018, 15:51:54 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 0 times in Scopus Search Google Scholar Access Statistics: 356 Abstract Views, 121 File Downloads  -  Detailed Statistics Created: Fri, 20 Apr 2012, 11:32:54 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.