期刊
IEEE TRANSACTIONS ON IMAGE PROCESSING
卷 29, 期 -, 页码 7032-7044出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIP.2020.2997331
关键词
Level set; Image segmentation; Computational modeling; Image edge detection; Nonhomogeneous media; Optimization; Active contours; Image segmentation; active contour model; level set; hybrid; energy weight constraint
资金
- National Key Research and Development Program of China [2018YFB2003200, 2018YFB2003500]
Hybrid active contour models with the combination of region and edge information have attracted great interests in image segmentation. To the best of our knowledge, however, the theoretical foundation of these hybrid models with level set evolution is insufficient and limited. More specifically, the weighting factors of their energy terms are difficult to select and are often empirically determined without definite theoretical basis. This problem is particularly prominent in the case of multi-object segmentation when more level set functions must be computed simultaneously. To cope with these challenges, this paper proposes a new level set approach for constructing hybrid active contour models with reliable energy weights, where the weights of region and edge terms can be constrained by the optimization condition deduced from the proposed method. It can be regarded as a general approach since many existing region-based models can be easily used to construct new hybrid models using their equivalent two-phase formulations. Some representative as well as state-of-the-art models are taken as examples to demonstrate the generality of our method. The respective comparative studies validate that under the guidance of the optimization condition, segmentation accuracy, robustness, and computational efficiency can be improved compared with the original models which are used to construct the new hybrid ones.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据