Abstract
Binary image thinning has wide applications in image processing, machine vision, and pattern recognition. Thinning is a preprocessing step to obtain single-pixel-thin skeleton for document imaging and pattern analysis. Indian languages are complex in character shape than Latin, Chinese, Japanese, and Korean languages. The performance of existing thinning methods cannot reach the state of the art in the field of document image processing for Indian languages. Our objective is to improve the performance of complex-shaped character skeletonization, particularly for Oriya script. This paper presents an iterative parallel thinning method which is well suited to handwritten Oriya characters. Some fundamental requirements of thinning like preservation of stroke connectivity, removal of spurious strokes have been ensured in this method. Experimental results show its efficacy comparing with other existing thinning methods.
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Bag, S., Chawpatnaik, G. (2016). A Modified Parallel Thinning Method for Handwritten Oriya Character Images. In: Das, S., Pal, T., Kar, S., Satapathy, S., Mandal, J. (eds) Proceedings of the 4th International Conference on Frontiers in Intelligent Computing: Theory and Applications (FICTA) 2015. Advances in Intelligent Systems and Computing, vol 404. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2695-6_16
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DOI: https://doi.org/10.1007/978-81-322-2695-6_16
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