| Autor: |
Chen D, Zhu J, Zhang X, Shu M, Cohen LD |
| Jazyk: |
angličtina |
| Zdroj: |
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society [IEEE Trans Image Process] 2021; Vol. 30, pp. 5138-5153. Date of Electronic Publication: 2021 May 24. |
| DOI: |
10.1109/TIP.2021.3078106 |
| Abstrakt: |
Minimal paths are regarded as a powerful and efficient tool for boundary detection and image segmentation due to its global optimality and the well-established numerical solutions such as fast marching method. In this paper, we introduce a flexible interactive image segmentation model based on the Eikonal partial differential equation (PDE) framework in conjunction with region-based homogeneity enhancement. A key ingredient in the introduced model is the construction of local geodesic metrics, which are capable of integrating anisotropic and asymmetric edge features, implicit region-based homogeneity features and/or curvature regularization. The incorporation of the region-based homogeneity features into the metrics considered relies on an implicit representation of these features, which is one of the contributions of this work. Moreover, we also introduce a way to build simple closed contours as the concatenation of two disjoint open curves. Experimental results prove that the proposed model indeed outperforms state-of-the-art minimal paths-based image segmentation approaches. |
| Databáze: |
MEDLINE |
| Externí odkaz: |
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