Research Article
An Adaptive Threshold Algorithm for Offline Uyghur Handwritten Text Line Segmentation
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@INPROCEEDINGS{10.1007/978-3-030-32216-8_29, author={Eliyas Suleyman and Palidan Tuerxun and Kamil Moydin and Askar Hamdulla}, title={An Adaptive Threshold Algorithm for Offline Uyghur Handwritten Text Line Segmentation}, proceedings={Simulation Tools and Techniques. 11th International Conference, SIMUtools 2019, Chengdu, China, July 8--10, 2019, Proceedings}, proceedings_a={SIMUTOOLS}, year={2019}, month={10}, keywords={Text line segmentation Adaptive thresholding Offline Uyghur handwritten documents}, doi={10.1007/978-3-030-32216-8_29} }- Eliyas Suleyman
Palidan Tuerxun
Kamil Moydin
Askar Hamdulla
Year: 2019
An Adaptive Threshold Algorithm for Offline Uyghur Handwritten Text Line Segmentation
SIMUTOOLS
Springer
DOI: 10.1007/978-3-030-32216-8_29
Abstract
This paper presents an effective text-line segmentation algorithm and evaluates its performance on Uyghur handwritten text document images. Projection based adaptive threshold selection mechanism is implemented to detect and segment the text lines with different valued thresholds. The robustness of the proposed algorithm is admirable that experiments on 210 Uyghur handwritten document image including 2570 text lines got correct segmentation by 97.70% precision and 99.01% recall rate and outperformed the compared classic text-line segmentation algorithm on same evaluation set.
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