The article is a step forward towards improving image segmentation using a popular method called Graph-Cut. We focus on optimizing the algorithm for processing data, in which the target object occupies only a small portion of the total volume. We propose a two-step procedure. At the first step, the location of the object is determined roughly. At the second step, Graph-Cut segmentation is performed with a special multi-scale chart structure. Two different graph construction methods are suggested. The calculation time of both variants is compared with the original Graph-Cut method. The msgc_lo2hi method has been shown to provide a statistically significant time reduction of the computational costs.
CITATION STYLE
Jirik, M., Lukes, V., Zelezny, M., & Liska, V. (2018). Multiscale Graph-Cut for 3D Segmentation of Compact Objects. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11255 LNCS, pp. 227–236). Springer Verlag. https://doi.org/10.1007/978-3-030-05288-1_18
Mendeley helps you to discover research relevant for your work.