Abstract
Discrimination of handwritten and machine printed text in a scanned document image is an important process as the Optical Character Recognizers (OCRs) available are domain specific. In this paper, a novel approach has been proposed to discriminate handwritten and machine printed word components based on the structure. In the binarized form of the word component, due to the informative foreground overlay on the null background, transitions from 0-1 and 1-0 occur at the contour of the component structure. The count and occurrence of these transitions are used to discriminate handwritten and machine printed word components. The proposed method is robust and simple. Extensive experimentation has been conducted over a wide range of data samples (English words).
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Acknowledgments
This work has been supported by Visveswaraya Technological University (VTU) under the Research Grant Scheme 2010-11 (Ref. No VTU/Aca./2011-12/A-9/13097). The authors acknowledge the support provided by VTU.
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Narayan, S., Gowda, S.D. (2013). Discrimination of Handwritten and Machine Printed Text in Scanned Document Images. In: Chakravarthi, V., Shirur, Y., Prasad, R. (eds) Proceedings of International Conference on VLSI, Communication, Advanced Devices, Signals & Systems and Networking (VCASAN-2013). Lecture Notes in Electrical Engineering, vol 258. Springer, India. https://doi.org/10.1007/978-81-322-1524-0_46
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DOI: https://doi.org/10.1007/978-81-322-1524-0_46
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