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文章基本信息

  • 标题:Capital Letter Recognition in Non Cursive Handwritten Documents
  • 本地全文:下载
  • 作者:Samudra Gupt Maurya ; Ritika Chugh ; Rohit Kumar
  • 期刊名称:International Journal of Computer Science and Information Technologies
  • 电子版ISSN:0975-9646
  • 出版年度:2014
  • 卷号:5
  • 期号:3
  • 页码:2824-2827
  • 出版社:TechScience Publications
  • 摘要:In this paper, we here a new text line detection method for handwritten documents. The projected technique is based on a stratagem that consists of three distinct steps. The first step includes image binarization and enhancement, associated component extraction, partitioning of the connected element domain into three spatial sub-domains and typical character height estimation. In the second step, a block-based Hough transform is worn for the detection of potential text lines while a third step is used to correct potential splitting, to detect text lines that the previous step did not reveal and lastly, to separate vertically connected characters and assign them to text lines. The presentation evaluation of the proposed approach is based on a consistent and concrete estimation methodology. This paper models text line detection as an image segmentation predicament by enhancing text line structure using a Gaussian window, and adopting the level set method to progress text line boundaries
  • 关键词:Image segmentation; Histogram based Algorithm;Edge Detection algorithm Preprocessing; Image acquisition
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