@article{2633,
  keywords = {Arabic Documents, Handwritten Character Recognition, Text Mining, Text Line Segmentation, Connected Component Analysis, Projection Profile, Watershed Transform},
  author = {Youssef Boulid and Abdelghani Souhar and Mly. Ouagague and E Ameur},
  title = {Segmentation of Arabic Handwritten Documents into Text Lines using Watershed Transform},
  abstract = {A crucial task in character recognition systems is the segmentation of the document into text lines and especially if it is handwritten. When dealing with non-Latin document such as Arabic, the challenge becomes greater since in addition to the variability of writing, the presence of diacritical points and the high number of ascender and descender characters complicates more the process of the segmentation. To remedy with this complexity and even to make this difficulty an advantage since the focus is on the Arabic language which is semi-cursive in nature, a method based on the Watershed Transform technique is proposed. Tested on «Handwritten Arabic Proximity Datasets» a segmentation rate of 93% for a 95% of matching score is achieved.},
  year = {2017},
  journal = {International Journal of Interactive Multimedia and Artificial Intelligence},
  volume = {4},
  number = {6},
  pages = {96-102},
  month = {12/2017},
  issn = {1989-1660},
  url = {http://www.ijimai.org/journal/sites/default/files/files/2017/08/ijimai20174_6_13_pdf_11239.pdf},
  doi = {10.9781/ijimai.2017.08.002},
}