Abstract
In this paper, the problem of image segmentation for detecting defects is considered. It is proposed to use the method of persistent homology for image segmentation using topological features. The influence of various image preprocessing methods on the result of segmentation by persistent homology is investigated. A mathematical model of segmentation is demonstrated. Examples of the algorithm for detecting defects in wood images are shown. The results of segmentation and comparison tables of characteristics depending on preprocessing methods are presented. The advantage of using the persistent homology method with Gauss filtering for detecting wood defects is demonstrated.
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Eremeev, S., Romanov, S. (2021). Influence of Image Pre-processing Algorithms on Segmentation Results by Method of Persistence Homology. In: Hu, Z., Petoukhov, S., He, M. (eds) Advances in Artificial Systems for Medicine and Education IV. AIMEE 2020. Advances in Intelligent Systems and Computing, vol 1315. Springer, Cham. https://doi.org/10.1007/978-3-030-67133-4_11
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DOI: https://doi.org/10.1007/978-3-030-67133-4_11
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