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Research report on Bangla optical character recognition using Kohonen network

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dc.contributor.author Shatil, Adnan Md. Shoeb
dc.date.accessioned 2010-10-28T04:08:49Z
dc.date.available 2010-10-28T04:08:49Z
dc.date.issued 2007
dc.identifier.uri http://hdl.handle.net/10361/658
dc.description.abstract This report discusses the theory and implementation of an Optical Character Recognition (OCR) for Bangla. The principal idea is to convert images of text documents such as those obtained from scanning a document into editable texts. This report does not address the pre-processing steps such as skew correction and noise reduction (which is handled in a previous report), so the documents are assumed to pre-processed by another tool in the pipeline. For training and recognition, the input is then first converted to a binary image, and then into to a 25x25 pixel2 image; the only feature extracted from the images is a 625-bit long vector, which is then trained or classified using a Kohonen neural network. The OCR shows excellent performance for documents with single typeface. The work in progress is extending it to handle multiple typefaces. en_US
dc.language.iso en en_US
dc.publisher Center for research on Bangla language processing (CRBLP), BRAC University en_US
dc.title Research report on Bangla optical character recognition using Kohonen network en_US
dc.type Technical Report en_US


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