Abstract
This paper presents an unconventional method of segmenting nontext objects directly from a grayscale document image by making use of connected operators, combined with the Otsu thresholding method, where the connected operators are realized as a maxtree. The maxtree structure is used for a simplification of the image and at a later stage, it is used as a structure from which to extract the desired objects. The proposed solution is aimed at segmenting halftone images, tables, line drawings, and graphs. The solution has been evaluated and some of its shortcomings are highlighted. To the best of our knowledge, this is the first attempt at using connected operators for page segmentation.
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Notes
- 1.
Results: https://github.com/MSheshera/TNTClassify.
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Mysore, S., Gupta, M.K., Belhe, S. (2017). Connected Operators for Non-text Object Segmentation in Grayscale Document Images. In: Raman, B., Kumar, S., Roy, P., Sen, D. (eds) Proceedings of International Conference on Computer Vision and Image Processing. Advances in Intelligent Systems and Computing, vol 459. Springer, Singapore. https://doi.org/10.1007/978-981-10-2104-6_36
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DOI: https://doi.org/10.1007/978-981-10-2104-6_36
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