Integrating Writing Direction and Handwriting Letter Recognition in Touch-Enabled Devices

  • Akshay Jayakumar
  • Ganga S. Babu
  • Raghu Raman
  • Prema Nedungadi
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 380)

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.

Keywords

Character recognition Online recognition Offline recognition Neural networks Quadrant-based direction checking Alphabet rules Self-organizing map ANN OCR 

Notes

Acknowledgments

This work derives its inspiration and direction from the Chancellor of Amrita University, Sri Mata Amritanandamayi Devi. We are grateful for the support of our colleagues at Amrita CREATE and the staff at Amrita University.

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Copyright information

© Springer India 2016

Authors and Affiliations

  • Akshay Jayakumar
    • 1
  • Ganga S. Babu
    • 1
  • Raghu Raman
    • 1
  • Prema Nedungadi
    • 1
  1. 1.Amrita CREATEAmrita UniversityKollamIndia

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