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Geodesic Active Regions for Texture Segmentation

Nikolaos Paragios 1 Rachid Deriche
1 ROBOTVIS - Computer Vision and Robotics
CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : This paper proposes a framework for segmenting different textured areas over synthetic or real textured frames by curves propagation. We assume that the system has the ability to be taught over different texture prototypes. For each prototype a global statistical model is generated, as a set of probability density functions attributes from a multi-valued frame analysis, where different filter responses are used to create this multi-valued frame. Then, each prototype is represented by a reliable statistical model. Given an input frame composed of different texture types, the same bank of filters is applied. Over the generated multi-valued frame, we define an energy as a special form of a geodesic active contour model, a Geodesic Active Regi on Model, where we integrate boundary finding and region based segmentation approaches. This energy is minimized using a steepest gradient descend method, where smoothing, edge-based, and region statistics forces, move the curve toward the minimum of the designed objective function. Using the level set formulation scheme, complex curves can be detected, while topological changes for the evolving curves are naturally managed. In order to deal with the problem of noise influence, as well as to reduce the required computational cost, a multi-grid approach has also been considered. Finally, two different methods are used for the level set implementation, the Narrow Band and the Hermes Algorithm. Very promising experimental results are provided using synthetic and real textured frames.
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Submitted on : Wednesday, May 24, 2006 - 12:21:02 PM
Last modification on : Friday, February 4, 2022 - 3:18:46 AM
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  • HAL Id : inria-00073250, version 1



Nikolaos Paragios, Rachid Deriche. Geodesic Active Regions for Texture Segmentation. RR-3440, INRIA. 1998. ⟨inria-00073250⟩



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