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Review of Level Set in Image Segmentation
https://orcid.org/0000-0002-7059-9907
Abstract Level set is one of active contour models, which is good at handling complex topologies and capturing boundary. The level set methods are specially used in image with intensity inhomogeneity, such as medical image, SAR image, etc. There are many methods based on level set, which are classified into region-based and edge-based. This article firstly derives the function of curve evolution and original model of level set based on region and edge, respectively. Level set methods over the past decade are summed up and categorized. Some typical models and their improvement are introduced in detail. Some level set methods are employed for comparison. The disadvantages and future work are also discussed.
Review of Level Set in Image Segmentation
https://orcid.org/0000-0002-7059-9907
Abstract Level set is one of active contour models, which is good at handling complex topologies and capturing boundary. The level set methods are specially used in image with intensity inhomogeneity, such as medical image, SAR image, etc. There are many methods based on level set, which are classified into region-based and edge-based. This article firstly derives the function of curve evolution and original model of level set based on region and edge, respectively. Level set methods over the past decade are summed up and categorized. Some typical models and their improvement are introduced in detail. Some level set methods are employed for comparison. The disadvantages and future work are also discussed.
Review of Level Set in Image Segmentation
https://orcid.org/0000-0002-7059-9907
Abstract Level set is one of active contour models, which is good at handling complex topologies and capturing boundary. The level set methods are specially used in image with intensity inhomogeneity, such as medical image, SAR image, etc. There are many methods based on level set, which are classified into region-based and edge-based. This article firstly derives the function of curve evolution and original model of level set based on region and edge, respectively. Level set methods over the past decade are summed up and categorized. Some typical models and their improvement are introduced in detail. Some level set methods are employed for comparison. The disadvantages and future work are also discussed.
Review of Level Set in Image Segmentation
Wang, Zhaobin (author) / Ma, Baozhen (author) / Zhu, Ying (author)
2020
Article (Journal)
Electronic Resource
English
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