Publication Type:

Book Chapter

Source:

Integrating Writing Direction and Handwriting Letter Recognition in Touch-Enabled Devices, Springer India, Volume 380, Number Advances in Intelligent Systems and Computing, New Delhi, p.393–400 (2016)

ISBN:

9788132225232

URL:

http://dx.doi.org/10.1007/978-81-322-2523-2_38

Abstract:

Optical character recognition (OCR) transforms printed text to editable format and digital writing on smart devices. Learning to write programs has made learners trace an alphabet to learn the flow of writing and OCR by itself is less effective as it ignores the directional flow of writing and only focuses on the final image. Our research designed a unique android-based multilingual game-like writing app that enhances the writing experience. A key focus of the research was to compare and identify character recognition algorithms that are effective on low-cost android tablets with limited processing capabilities. We integrate a quadrant-based direction checking system with artificial neural networks and compare it to the existing systems. Our solution has the dual advantage of evaluating the writing direction and significantly increasing the accuracy compared to the existing systems. This program is used as the literacy tool in many villages in rural India.

Cite this Research Publication

A. Jayakumar, Babu, G. S., Raghu Raman, and Prof. Nedungadi, P., “Integrating Writing Direction and Handwriting Letter Recognition in Touch-Enabled Devices”, in Integrating Writing Direction and Handwriting Letter Recognition in Touch-Enabled Devices, vol. 380, New Delhi: Springer India, 2016, pp. 393–400.

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