Year: 2021
Type: article
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.
Authors: Da Chen, Jian Zhu, Xinxin Zhang, Minglei Shu, Laurent D. Cohen
Institutions: Qilu University of Technology, Shandong Academy of Sciences, Shandong Tumor Hospital, Shandong First Medical University, Shandong University, Centre National de la Recherche Scientifique, Centre de Recherche en Mathématiques de la Décision, Université Paris Sciences et Lettres, Université Paris Dauphine-PSL
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3049259308