TY - GEN

T1 - From Inpainting to Active Contours

AU - Lauze, Francois Bernard

AU - Nielsen, Mads

N1 - Conference code: 3

PY - 2005

Y1 - 2005

N2 - We introduce a novel type of region based active contour using image inpainting. Usual region based active contours assume that the image is divided into several semantically meaningful regions and attempt to differentiate them through recovering dynamically statistical optimal parameters for each region. In case when perceptually distinct regions have similar intensity distributions, the methods mentioned above fail. In this work, we formulate the problem as optimizing a ”background disocclusion” criterion, a disocclusion that can be performed by inpainting. We look especially at a family of inpainting formulations that includes the Chan and Shen Total Variation Inpainting (more precisely a regularization of it). In this case, the optimization leads formally to a coupled contour evolution equation, an inpainting equation, as well as a linear PDE depending on the inpainting. The contour evolution is implemented in the framework of level sets. Finally, the proposed method is validated on various examples.

AB - We introduce a novel type of region based active contour using image inpainting. Usual region based active contours assume that the image is divided into several semantically meaningful regions and attempt to differentiate them through recovering dynamically statistical optimal parameters for each region. In case when perceptually distinct regions have similar intensity distributions, the methods mentioned above fail. In this work, we formulate the problem as optimizing a ”background disocclusion” criterion, a disocclusion that can be performed by inpainting. We look especially at a family of inpainting formulations that includes the Chan and Shen Total Variation Inpainting (more precisely a regularization of it). In this case, the optimization leads formally to a coupled contour evolution equation, an inpainting equation, as well as a linear PDE depending on the inpainting. The contour evolution is implemented in the framework of level sets. Finally, the proposed method is validated on various examples.

U2 - 10.1007/11567646_9

DO - 10.1007/11567646_9

M3 - Article in proceedings

SN - 978-3-540-29348-4

T3 - Lecture notes in computer science

SP - 97

EP - 108

BT - Variational, Geometric, and Level Set Methods in Computer Vision

PB - <Forlag uden navn>

Y2 - 29 November 2010

ER -