Abstract
We introduce a texture-based modification of the GrabCut algorithm that significantly improves its performance for high-resolution images but with a slight decrease in accuracy. This consists of five steps: expansion, convolution, shrinkage, GrabCut of the shrunk image, and enlargement. The results showed that modified algorithm is three times faster than the original one. At the same time, there is no significant difference between the average F1-measures obtained for both algorithms in case of high-resolution images. Therefore, it can be successfully used in semi-automatic segmentation of such images.
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Babiuch, M., Zieliński, B., Skomorowski, M. (2016). RoughCut–New Approach to Segment High-Resolution Images. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2016. Lecture Notes in Computer Science(), vol 9693. Springer, Cham. https://doi.org/10.1007/978-3-319-39384-1_52
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DOI: https://doi.org/10.1007/978-3-319-39384-1_52
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