• DocumentCode
    231005
  • Title

    Devanagari handwritten text segmentation for overlapping and conjunct characters- A proficient technique

  • Author

    Thakral, Binny ; Kumar, Manoj

  • Author_Institution
    Comput. Eng., Yadavindra Coll. of Eng., Talwandi Sabo, India
  • fYear
    2014
  • fDate
    8-10 Oct. 2014
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Optical Character Recognition alludes to the methodology of taking images or photos of letters or typewritten content and changing over them into information that a machine can easily interpret, e.g. organizations and libraries taking physical duplicates of books, magazines, or other old printed material and utilizing OCR to put them into computers. Segmentation is the indispensable and most difficult part of OCR process, and it gets to be additionally difficult with handwritten text due to varieties in writing styles and presence of abnormalities. This paper shows a new strategy for the segmentation of conjuncts, and overlapping characters in Devanagari script on Hindi language. The proposed algorithm is focused around Cluster Detection technique and gives 95% correctness for segmenting touching, conjunct characters and 88% effectiveness for overlapping characters.
  • Keywords
    handwritten character recognition; image segmentation; object detection; optical character recognition; Devanagari handwritten text segmentation; Hindi language; OCR process; cluster detection technique; conjunct character; conjuncts segmentation; optical character recognition; overlapping character; writing styles; Accuracy; Algorithm design and analysis; Character recognition; Clustering algorithms; Handwriting recognition; Image segmentation; Text recognition; Conjuncts; Devanagari; Hindi; Isolated; Recognition; Segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Reliability, Infocom Technologies and Optimization (ICRITO) (Trends and Future Directions), 2014 3rd International Conference on
  • Conference_Location
    Noida
  • Print_ISBN
    978-1-4799-6895-4
  • Type

    conf

  • DOI
    10.1109/ICRITO.2014.7014746
  • Filename
    7014746