Ensemble of active contour based image segmentation
Wei Xu, Xiaodong Yue, Yufei Chen, Marek Reformat · 2017
Most image segmentation methods based on active contour model are sensitive to the contour initialization. For the images of complex contents, it is difficult to initialize the contour properly and the biased initialization may lead to low-quality segmentation results. Aiming to tackle this problem, we propose an ensemble strategy to improve the contour-based segmentation. The optimal segmentation ensemble is obtained through maximizing the weighted mutual information between the probability distributions of multiple segmentation results. Experimental results validate that the ensemble of contour-based segmentation is robust to the biased initialization and produces stable and precise results for the images of complex contents.