Handwritten Devanagari Script Segmentation: A non-linear Fuzzy Approach
Abstract
The paper concentrates on improvement of segmentation accuracy by addressing some of the key challenges of handwritten Devanagari word image segmentation technique. In the present work, we have developed a new feature based approach for identification of Matra pixels from a word image, design of a non-linear fuzzy membership functions for headline estimation and finally design of a non-linear fuzzy functions for identifying segmentation points on the Matra. The segmentation accuracy achieved by the current technique is 94.8%. This shows an improvement of performance by 1.8% over the previous technique [1] on a 300-word dataset, used for the current experiment.
Cite
@article{arxiv.1501.05472,
title = {Handwritten Devanagari Script Segmentation: A non-linear Fuzzy Approach},
author = {Ram Sarkar and Bibhash Sen and Nibaran Das and Subhadip Basu},
journal= {arXiv preprint arXiv:1501.05472},
year = {2015}
}
Comments
In Proceedings of IEEE Conference on AI Tools and Engineering (ICAITE-08), March 6-8, 2008, Pune