A Segmentation Method under Geometric Constraints after Pre-processing

For a geophysical image with homogeneous grey levels, we propose a method of segmentation that could be subdivided into two parts: the first one concerns a pre-processing of the image which provides an enhancement of some features present on the image. The originality of the method consists in using a scale transformation applied to the pixel values of the image. The second part presents a segmentation method using deformable surfaces. The originality of this segmentation method is that it considers the active contour model as a set of articulated curves, which corresponds to the interfaces between different layers and faults. Moreover, the a priori knowledge of well data allows us to make some geometric constraints on the model. The solution is obtained by minimization of a nonlinear functional under constraints in a suitable convex set. Solving the minimization problem consists in particular in a kappa-order Taylor formula applied to linearize the nonlinear term. Presented at Intl. Conference on Curves and Surfaces (4th), Held in St. Malo, France, 1-7 Jul 1999. Publ. in Proceedings, v2, Curve and Surface Fitting, p9-18. This article is from ADA399401 International Conference on Curves and Surfaces (4th), Saint-Malo, France, 1-7 July 1999. Proceedings, Volume 2. Curve and Surface Fitting.