Abstract
Segmentation plays a crucial role in the recognition of offline handwritten characters from the digitized document images. In this paper, the authors propose the glyph segmentation method for offline handwritten Telugu characters. This method efficiently segments the top vowel ligature glyph, main glyph, bottom vowel ligature glyph and consonant conjunct glyph from the offline handwritten Telugu character images. It efficiently identifies the small glyphs that are related to the unconnected main glyphs or consonant conjuncts and also efficiently segments the connected top vowel ligature from the main glyph. This approach of segmentation efficiently reduces the train data size for the purpose of offline handwritten Telugu characters recognition system. The result shows the efficiency of proposed method.
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Naga Manisha, C., Sundara Krishna, Y.K., Sreenivasa Reddy, E. (2018). Glyph Segmentation for Offline Handwritten Telugu Characters. In: Satapathy, S., Bhateja, V., Raju, K., Janakiramaiah, B. (eds) Data Engineering and Intelligent Computing. Advances in Intelligent Systems and Computing, vol 542 . Springer, Singapore. https://doi.org/10.1007/978-981-10-3223-3_21
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DOI: https://doi.org/10.1007/978-981-10-3223-3_21
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