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Publication Detail
Multiscale histogram of oriented gradient descriptors for robust character recognition
  • Publication Type:
    Conference
  • Authors:
    Newell AJ, Griffin LD
  • Publication date:
    02/12/2011
  • Pagination:
    1085, 1089
  • Published proceedings:
    Proceedings of the International Conference on Document Analysis and Recognition, ICDAR
  • ISBN-13:
    9780769545202
  • Status:
    Published
  • Print ISSN:
    1520-5363
Abstract
Characters extracted from images or graphics pose a challenge for traditional character recognition techniques. The high degree of intraclass variation along with the presence of clutter makes accurate recognition difficult, yet the semantic information conveyed by sections of text within images or graphics makes their recognition an important problem. Previous work has shown that, on the two most commonly used datasets of such characters, Histogram of Oriented Gradient (HOG) descriptors have outperformed other methods. In this work we consider two extensions of the HOG descriptor to include features at multiple scales, and evaluate their performance using characters taken from images and graphics. We demonstrate that, by combining pairs of oriented gradients at different scales, it's possible to achieve an increase in performance of 12.4% and 5.6% on the two datasets. © 2011 IEEE.
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