Segmentation of handwritten character identification from an image using digital image processing based on threshold level compared with edge based segmentation

Author:

Sasikumar C.,Suresh G. R.

Publisher

AIP Publishing

Reference45 articles.

1. D. V. Sharma and G. S. Lehal, “An Iterative Algorithm for Segmentation of Isolated Handwritten Words in Gurmukhi Script,” in 18th International Conference on Pattern Recognition (ICPR’06), Aug. 2006, vol. 2, pp. 1022–1025.

2. S. Puri and S. P. Singh, “An efficient Devanagari character classification in printed and handwritten documents using SVM,” ProcediaComput. Sci., vol. 152, pp. 111–121, Jan. 2019.

3. G. H. Kumar and T. Jipeng, “Different Edge Detection Algorithms Comparison and Analysis on Handwritten Chinese Character Recognition,” Int. J. Comput. Appl. Technol., vol. 47, no. 17, 2012, [Online]. Available: https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.258.5760&rep=rep1&type=pdf

4. H.-G. Zhang, G. Liu, W.-R. Xu, and J. Guo, “An algorithm of handwritten digits segmentation based on multi-mould,” in Proceedings. International Conference on Machine Learning and Cybernetics, Nov. 2002, vol. 2, pp. 1081–1084 vol.2.

5. B. Shaw, S. K. Parui, and M. Shridhar, “Offline Handwritten Devanagari Word Recognition: A Holistic Approach Based on Directional Chain Code Feature and HMM,” in 2008 International Conference on Information Technology, Dec. 2008, pp. 203–208.

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