Please use this identifier to cite or link to this item: doi:10.22028/D291-26309
Title: Colour, texture, and motion in level set based segmentation and tracking
Author(s): Brox, Thomas
Rousson, Mikael
Deriche, Rachid
Weickert, Joachim
Language: English
Year of Publication: 2005
Free key words: image segmentatio
level set methods
nonlinear diffusion
DDC notations: 510 Mathematics
Publikation type: Other
Abstract: This paper introduces an approach for the extraction and combination of different cues in a level set based image segmentation framework. Apart from the image grey value or colour, we suggest to add its spatial and temporal variations, which may provide important further characteristics. It often turns out that the combination of colour, texture, and motion permits to distinguish object regions that cannot be separated by one cue alone. We propose a two-step approach. In the first stage, the input features are extracted and enhanced by applying coupled nonlinear diffusion. This ensures coherence between the channels and deals with outliers. We use a nonlinear diffusion technique, closely related to total variation flow, but being strictly edge enhancing. The resulting features are then employed for a vector-valued front propagation based on level sets and statistical region models that approximate the distributions of each feature. The application of this approach to two-phase segmentation is followed by an extension to the tracking of multiple objects in image sequences.
Link to this record: urn:nbn:de:bsz:291-scidok-46151
Series name: Preprint / Fachrichtung Mathematik, Universität des Saarlandes
Series volume: 147
Date of registration: 15-Feb-2012
Faculty: MI - Fakultät für Mathematik und Informatik
Department: MI - Mathematik
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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