Lexicon-Free, Novel Segmentation of Online Handwritten Indic Words

Author

Sundaram, Suresh ; Ramakrishan, A.G.

Author_Institution

Dept. of Electr. Eng., Indian Inst. of Sci., Bangalore, India

fYear

2011

fDate

18-21 Sept. 2011

Firstpage

1175

Lastpage

1179

Abstract

Research in the field of recognizing unlimited vocabulary, online handwritten Indic words is still in its infancy. Most of the focus so far has been in the area of isolated character recognition. In the context of lexicon-free recognition of words, one of the primary issues to be addressed is that of segmentation. As a preliminary attempt, this paper proposes a novel script-independent, lexicon-free method for segmenting online handwritten words to their constituent symbols. Feedback strategies, inspired from neuroscience studies, are proposed for improving the segmentation. The segmentation strategy has been tested on an exhaustive set of 10000 Tamil words collected from a large number of writers. The results show that better segmentation improves the overall recognition performance of the handwriting system.

Keywords

handwritten character recognition; image segmentation; vocabulary; word processing; Tamil words; feedback strategies; isolated character recognition; lexicon-free segmentation; lexicon-free word recognition; neuroscience studies; online handwritten Indic word segmentation; unlimited vocabulary recognition; Character recognition; Databases; Feature extraction; Handwriting recognition; Knowledge based systems; Neuroscience; Support vector machines; Dominant overlap Segmentation (DOS); Feedback segmentation (FS); Online Tamil symbol recognition; Stroke Group; Support Vector Machine (SVM);

fLanguage

English

Publisher

ieee

Conference_Titel

Document Analysis and Recognition (ICDAR), 2011 International Conference on

Conference_Location

Beijing

ISSN

1520-5363

Print_ISBN

978-1-4577-1350-7

Electronic_ISBN

1520-5363

Type

conf

DOI

10.1109/ICDAR.2011.237

Filename

6065495