Entry Chanda:2009:WWT from talip.bib

Last update: Sun Oct 15 02:55:04 MDT 2017                Valid HTML 3.2!

Index sections

Top | Symbols | Numbers | Math | A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z

BibTeX entry

@Article{Chanda:2009:WWT,
  author =       "Sukalpa Chanda and Umapada Pal and Oriol Ramos
                 Terrades",
  title =        "Word-Wise {Thai} and {Roman} Script Identification",
  journal =      j-TALIP,
  volume =       "8",
  number =       "3",
  pages =        "11:1--11:??",
  month =        aug,
  year =         "2009",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1568292.1568294",
  ISSN =         "1530-0226 (print), 1558-3430 (electronic)",
  ISSN-L =       "1530-0226",
  bibdate =      "Mon Mar 29 15:37:08 MDT 2010",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/talip.bib",
  abstract =     "In some Thai documents, a single text line of a
                 printed document page may contain words of both Thai
                 and Roman scripts. For the Optical Character
                 Recognition (OCR) of such a document page it is better
                 to identify, at first, Thai and Roman script portions
                 and then to use individual OCR systems of the
                 respective scripts on these identified portions. In
                 this article, an SVM-based method is proposed for
                 identification of word-wise printed Roman and Thai
                 scripts from a single line of a document page. Here, at
                 first, the document is segmented into lines and then
                 lines are segmented into character groups (words). In
                 the proposed scheme, we identify the script of a
                 character group combining different character features
                 obtained from structural shape, profile behavior,
                 component overlapping information, topological
                 properties, and water reservoir concept, etc. Based on
                 the experiment on 10,000 data (words) we obtained
                 99.62\% script identification accuracy from the
                 proposed scheme.",
  acknowledgement = ack-nhfb,
  articleno =    "11",
  fjournal =     "ACM Transactions on Asian Language Information
                 Processing",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?&idx=J820",
  keywords =     "Multi-script OCR; script identification; SVM; Thai
                 Script",
}

Related entries