Title
Convex non-convex segmentation of scalar fields over arbitrary triangulated surfaces.
Abstract
An extension of the Mumford–Shah model for image segmentation is introduced to segment real-valued functions having values on a complete, connected, 2-manifold embedded in R3. The proposed approach consists of three stages: first, a multi-phase piecewise smooth partition function is computed, then its values are clustered and, finally, the curve tracking is computed on the segmented boundaries. The first stage, which constitutes the key novelty behind our proposal, relies on a Convex Non-Convex variational model where an ad-hoc non-convex regularization term coupled with a space-variant regularization parameter allows to effectively deal with both the boundaries and the inner parts of the segments. The cost functional is minimized by means of an efficient numerical scheme based on the Alternating Directions Methods of Multipliers. Experimental results are presented which demonstrate the effectiveness of the proposed three-stage segmentation approach.
Year
DOI
Venue
2019
10.1016/j.cam.2018.06.048
Journal of Computational and Applied Mathematics
Keywords
Field
DocType
Mesh segmentation,Non-convex regularization,Convex non-convex optimization,Mumford–Shah variational model
Applied mathematics,Mathematical analysis,Segmentation,Partition function (statistical mechanics),Scalar (physics),Regular polygon,Image segmentation,Triangulation,Regularization (mathematics),Mathematics,Piecewise
Journal
Volume
ISSN
Citations 
349
0377-0427
1
PageRank 
References 
Authors
0.35
10
4
Name
Order
Citations
PageRank
Martin Huska111.36
Alessandro Lanza2557.16
Serena Morigi314220.57
Fiorella Sgallari421722.22