An Efficient Character Segmentation Algorithm for Offline Handwritten Uighur Scripts Based on Grapheme Analysis

DOI

10.2991/aiie-16.2016.31How to use a DOI?

Keywords

computer application; uighur language; handwriting recognition; character segmentation; grapheme

Abstract

Cursive offline handwritten Uighur scripts contain a lot of small and random writing strokes, which makes the character segmentation is more complicated. In view of this, a new efficient character segmentation algorithm based on grapheme (part of a character) analysis is proposed in this paper. Firstly, by dot strokes detection and Component analysis, a handwritten Uighur word is over-segmented into three types of strokes: dot, affix and main strokes. Secondly, the main strokes are over-segmented but the dot strokes are clustered, so that a main graphemes queue and an additional graphemes queue are constructed respectively. Finally, the best hypothesis of characters sequence is selected by analyses of the graphemes' shapes and recognition results. Experiment results with 93.09% character segmentation accuracy rate and 97.67% recall rate have verified the validity of the proposed algorithm.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yamei Xu
AU  - Panpan Du
PY  - 2016/11
DA  - 2016/11
TI  - An Efficient Character Segmentation Algorithm for Offline Handwritten Uighur Scripts Based on Grapheme Analysis
BT  - Proceedings of the 2016 2nd International Conference on Artificial Intelligence and Industrial Engineering (AIIE 2016)
PB  - Atlantis Press
SP  - 129
EP  - 133
SN  - 1951-6851
UR  - https://doi.org/10.2991/aiie-16.2016.31
DO  - 10.2991/aiie-16.2016.31
ID  - Xu2016/11
ER  -