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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Acknowledgments
This work has been supported by the National Natural Science Foundation of China (under grant of 61462080) and Ph.D. Scientific Research Startup Project of Xinjiang University.
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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Suleyman, E., Tuerxun, P., Moydin, K., Hamdulla, A. (2019). An Adaptive Threshold Algorithm for Offline Uyghur Handwritten Text Line Segmentation. In: Song, H., Jiang, D. (eds) Simulation Tools and Techniques. SIMUtools 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 295. Springer, Cham. https://doi.org/10.1007/978-3-030-32216-8_29
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DOI: https://doi.org/10.1007/978-3-030-32216-8_29
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