research-article

Allograph modeling for online handwritten characters in devanagari using constrained stroke clustering

Authors:

Sriganesh MadhvanathAuthors Info & Claims

ACM Transactions on Asian Language Information Processing (TALIP), Volume 13, Issue 3

Article No.: 12, Pages 1 - 21

https://doi.org/10.1145/2629622

Published: 03 October 2014 Publication History

Abstract

Writer-specific character writing variations such as those of stroke order and stroke number are an important source of variability in the input when handwriting is captured “online” via a stylus and a challenge for robust online recognition of handwritten characters and words. It has been shown by several studies that explicit modeling of character allographs is important for achieving high recognition accuracies in a writer-independent recognition system. While previous approaches have relied on unsupervised clustering at the character or stroke level to find the allographs of a character, in this article we propose the use of constrained clustering using automatically derived domain constraints to find a minimal set of stroke clusters. The allographs identified have been applied to Devanagari character recognition using Hidden Markov Models and Nearest Neighbor classifiers, and the results indicate substantial improvement in recognition accuracy and/or reduction in memory and computation time when compared to alternate modeling techniques.

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Cited By

Bhattacharya SMaitra DBhattacharya UParui S(2016)An End-to-End System for Bangla Online Handwriting Recognition2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR)10.1109/ICFHR.2016.0076(373-378)Online publication date: Oct-2016
https://doi.org/10.1109/ICFHR.2016.0076
Ahmed MFasy BHickmann KWenk C(2015)A Path-Based Distance for Street Map ComparisonACM Transactions on Spatial Algorithms and Systems10.1145/27299771:1(1-28)Online publication date: 29-Jul-2015
https://dl.acm.org/doi/10.1145/2729977

Index Terms

Allograph modeling for online handwritten characters in devanagari using constrained stroke clustering
1. Computing methodologies
  1. Machine learning

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Published In

cover image ACM Transactions on Asian Language Information Processing

ACM Transactions on Asian Language Information Processing Volume 13, Issue 3

September 2014

83 pages

ISSN:1530-0226

EISSN:1558-3430

DOI:10.1145/2676410

Editor:
Richard Sproat
Google, Inc., USA

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Copyright © 2014 ACM.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 03 October 2014

Accepted: 01 April 2014

Revised: 01 April 2014

Received: 01 August 2013

Published in TALIP Volume 13, Issue 3

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Cited By

Bhattacharya SMaitra DBhattacharya UParui S(2016)An End-to-End System for Bangla Online Handwriting Recognition2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR)10.1109/ICFHR.2016.0076(373-378)Online publication date: Oct-2016
https://doi.org/10.1109/ICFHR.2016.0076
Ahmed MFasy BHickmann KWenk C(2015)A Path-Based Distance for Street Map ComparisonACM Transactions on Spatial Algorithms and Systems10.1145/27299771:1(1-28)Online publication date: 29-Jul-2015
https://dl.acm.org/doi/10.1145/2729977

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