Abstract:
Sinhala is the official and national language of
Sri Lanka. Seventeen million people of Sri Lanka use Sinhala
language to their day to day works. Most of the researches
have been done to Sinhala printed character recognition with
high accuracy. Nowadays, Sinhala handwritten character
recognition is popular research in Sri Lanka. It is not like
printed character segmentation; shape of the same type of
handwritten character can be changed in different times.
Therefore, characters will be overlapped or touched with each
other. Handwritten character segmentation is more important
to increase the accuracy of the character recognition.
Currently there is lack of high accuracy finding to segment
overlapping and touching Sinhala handwritten characters.
This paper introduced a connected pixel labeling method to
segmentation of overlapping characters and peak and valley
point identification method to segmentation of touching
characters. According to tested result, connected pixel labelling
method has 97% accuracy and peak and valley identification
method has 72% accuracy.
Citation:
K. S. A. Walawage and L. Ranathunga, "Segmentation of Overlapping and Touching Sinhala Handwritten Characters," 2018 3rd International Conference on Information Technology Research (ICITR), 2018, pp. 1-6, doi: 10.1109/ICITR.2018.8736129.