1. Geodesic Paths for Image Segmentation With Implicit Region-Based Homogeneity Enhancement.
- Author
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Chen, Da, Zhu, Jian, Zhang, Xinxin, Shu, Minglei, and Cohen, Laurent D.
- Subjects
IMAGE segmentation ,HOMOGENEITY ,GEODESICS ,PARTIAL differential equations ,FUZZY algorithms - Abstract
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. [ABSTRACT FROM AUTHOR]
- Published
- 2021
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