Abstract
In this paper, we present a character-level ground-truth for an Arabic dataset of 8,640 character-shapes along with an evaluation metric that is adapted from image segmentation. These tools together constitute a benchmark for character-segmentation. We demonstrate the use of this benchmark on some segmentation algorithms and report their quantitative results in bits. Our approach can be extended to other scripts.
Original language | English |
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Title of host publication | Proceedings - 14th International Conference on Frontiers in Handwriting Recognition, ICFHR 2014 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 766-770 |
Number of pages | 5 |
ISBN (Electronic) | 9781479943340 |
DOIs | |
State | Published - 9 Dec 2014 |
Publication series
Name | Proceedings of International Conference on Frontiers in Handwriting Recognition, ICFHR |
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Volume | 2014-December |
ISSN (Print) | 2167-6445 |
ISSN (Electronic) | 2167-6453 |
Bibliographical note
Publisher Copyright:© 2014 IEEE.
Keywords
- Arabic handwriting
- entropy-based metric
- ground-truth
- segmentation
ASJC Scopus subject areas
- Computer Science Applications
- Computer Vision and Pattern Recognition