Our Laplacian energy-based segmentation method (H-DIBCO2018-HBUT) achieved the Best performance in ICFHR 2018 competition on handwritten document image binarization (H-DIBCO 2018)[1], and the 2nd Best performance in Challenge A of ICFHR 2018 competition on document image analysis tasks for Southeast Asian palm leaf manuscripts[2].
H-DIBCO2018-HBUT: Wei XIONG, Zijie XIONG, Xiuhong JIA, Min LI
We first perform the morphological bottom-hat transform to compensate the document background with a disk-shaped structuring element, the size of which is determined by the stroke width transform (SWT)[3]. We then apply the Howe’s binarization method[4] on the compensated document images to further segment the foreground and background pixels. Finally, we carry out the image post-processing to produce better results.
If the code is helpful to your research, please cite the following papers:
- W. Xiong, X. Jia, J. Xu, Z. Xiong, M. Liu, J. Wang, "Historical document image binarization using background estimation and energy minimization," in Proceedings of the 24th International Conference on Pattern Recognition (ICPR 2018), Beijing, CHINA, 2018, pp. 3716-3721. doi: 10.1109/icpr.2018.8546099
- W. Xiong, L. Zhou, L. Yue, L. Li, S. Wang, "An enhanced binarization framework for degraded historical document images," EURASIP Journal on Image and Video Processing, vol. 2021, no. 1, 2021. doi: 10.1186/s13640-021-00556-4
References
[1] I. Pratikakis, K. Zagoris, P. Kaddas, B. Gatos, "ICFHR 2018 competition on handwritten document image binarization (H-DIBCO 2018)," in Proceedings of the 16th International Conference on Frontiers in Handwriting Recognition (ICFHR 2018), Niagara Falls, USA, 2018, pp. 489-493. doi: 10.1109/icfhr-2018.2018.00091
[2] M. W. A. Kesiman, D. Valy, J.-C. Burie, E. Paulus, M. Suryani, S. Hadi, M. Verleysen, S. Chhun, J.-M. Ogier, "ICFHR 2018 competition on document image analysis tasks for Southeast Asian palm leaf manuscripts," in Proceedings of the 16th International Conference on Frontiers in Handwriting Recognition (ICFHR 2018), Niagara Falls, USA, 2018, pp. 483-488. doi: 10.1109/icfhr-2018.2018.00090
[3] B. Epshtein, E. Ofek, Y. Wexler, "Detecting text in natural scenes with stroke width transform," in Proceedings of the 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2010), San Francisco, CA, 2010, pp. 2963-2970. doi: 10.1109/cvpr.2010.5540041
[4] N. R. Howe, "Document binarization with automatic parameter tuning," International Journal on Document Analysis and Recognition, vol. 16, no. 3, pp. 247-258, 2013. doi: 10.1007/s10032-012-0192-x