【摘要】 基于最小生成树的图像分割方法虽然具有较快的分割速度,然而这类方法的结果较为粗糙、冗杂.结合Mumford-Shah理论,提出了一种优化的方法.通过考虑图像中区域间的结合程度以及各区域的几何性质,计算区域间基于结合度的权值并将之加入到最小生成树图像分割方法的区域合并判断公式中,使相互结合较好的区域更易于合并.该方法能够在保留目标区域间较弱边缘的同时,很好地合并目标区域内部结合较好的区域,并得到简洁平滑的轮廓.更多还原

【Abstract】 The main advantage of image segmentation methods based on MST(minimum spanning tree) is its fast speed,but the segmentation results are often coarse and lack of clear structures.Inspired by Mumford-Shah theory,an improved MST-based segmentation method is proposed in this work.In our method,a good consideration is taken into account about the connectivity of neighboring regions as well as the geometric properties of each region.More specifically,weights between regions are computed and added into the region merging criteria to make the regions with higher connectivity easier to merge.Experiments showed that our method could preserve weak edges between objects and merge regions effectively within the same object,and the contours of resultant segmented regions are simple and smooth.更多还原