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A Generalized Asymmetric Dual-front Model for Active Contours and Image Segmentation

Chen, Da; Spencer, Jack; Mirebeau, Jean-Marie; Chen, Ke; Shu, Minglei; Cohen, Laurent D. (2021), A Generalized Asymmetric Dual-front Model for Active Contours and Image Segmentation, IEEE Transactions on Image Processing, 30, p. 5056 - 5071. 10.1109/TIP.2021.3078102

Type
Article accepté pour publication ou publié
External document link
https://arxiv.org/pdf/2006.07839.pdf
Date
2021
Journal name
IEEE Transactions on Image Processing
Volume
30
Publisher
IEEE - Institute of Electrical and Electronics Engineers
Pages
5056 - 5071
Publication identifier
10.1109/TIP.2021.3078102
Metadata
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Author(s)
Chen, Da
Shandong Artificial Intelligence Institute, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250014, China
Spencer, Jack
University of Exeter
Mirebeau, Jean-Marie
Laboratoire de Mathématiques d'Orsay [LMO]
Chen, Ke
Department of Mathematical Sciences [Liverpool]
Shu, Minglei
Shandong Artificial Intelligence Institute, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250014, China
Cohen, Laurent D.
CEntre de REcherches en MAthématiques de la DEcision [CEREMADE]
Abstract (EN)
The Voronoi diagram-based dual-front scheme is known as a powerful and efficient technique for addressing the image segmentation and domain partitioning problems. In the basic formulation of existing dual-front approaches, the evolving contour can be considered as the interfaces of adjacent Voronoi regions. Among these dual-front models, a crucial ingredient is regarded as the geodesic metrics by which the geodesic distances and the corresponding Voronoi diagram can be estimated. In this paper, we introduce a new dual-front model based on asymmetric quadratic metrics. These metrics considered are built by the integration of the image features and a vector field derived from the evolving contour. The use of the asymmetry enhancement can reduce the risk for the segmentation contours being stuck at false positions, especially when the initial curves are far away from the target boundaries or the images have complicated intensity distributions. Moreover, the proposed dual-front model can be applied for image segmentation in conjunction with various region-based homogeneity terms. The numerical experiments on both synthetic and real images show that the proposed dual-front model indeed achieves encouraging results.
Subjects / Keywords
Eikonal equation; asymmetric quadratic metric; Voronoi diagram; active contours; image segmentation; fast marching method

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