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Eswaran, Paramasivam Muthan
- Recognizing Tamil Palm-Leaf Manuscript Characters Using Hybridized Human Perception Based Features
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1 Department of Department of Electronics and Communication Engineering, Sona College of Technology, IN
1 Department of Department of Electronics and Communication Engineering, Sona College of Technology, IN
Source
ICTACT Journal on Image and Video Processing, Vol 11, No 4 (2021), Pagination: 2432-2440Abstract
In this paper, we present a zoning strategy for recognizing manuscript character images, based on human structural perception of characters. The deficiencies in a uniform zoning approach are filled by drawing significant information using the proposed method. The obtained feature set when applied on a SVM classifier, substantially improves the recognition rate for character images having structural variation at significant regions of characters. As a initiative, we have formulated the Tamil Palm-Leaf Character dataset. Preliminary results show that the incorporation of this hybridized zoning approach has improved the symbol recognition rate to 9.06% (from 81.07% to 90.13%). The average rejection rate has been nullified using this generic non-symmetrical zoning for the proposed dataset.Keywords
Manuscript Character Recognition, Visual perception, Triangular Zoning, Shape Based Zoning, Significant Zone Slicing.
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