Segmentation by nonlinear diffusion
- 10 December 2002
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 202-207
- https://doi.org/10.1109/cvpr.1991.139688
Abstract
A global model which integrates three sequential steps for segmenting an image, namely, noise-filtering, local edge-detection, and integration of local edges into object boundaries, is described. The model overcomes some of the difficulties inherent in earlier global models, particularly their tendency to oversegment, and the lack of practical numerical algorithms for implementing them. The model consists of two coupled elliptic functionals, one for smoothing out the noise, and the other for boundary detection. The latter is obtained by regularizing the usual pointwise thresholding employed for boundary detection. The first variation of these functionals leads to coupled system of diffusion equations which are implemented by a simple finite difference scheme. The scheme may easily be converted into a parallel algorithm.Keywords
This publication has 7 references indexed in Scilit:
- Parameter estimation, multiscale representation and algorithms for energy-minimizing segmentationsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Properties of Energy-Minimizing SegmentationsSIAM Journal on Control and Optimization, 1992
- Approximation of functional depending on jumps by elliptic functional via t‐convergenceCommunications on Pure and Applied Mathematics, 1990
- Existence theorem for a minimum problem with free discontinuity setArchive for Rational Mechanics and Analysis, 1989
- Optimal approximations by piecewise smooth functions and associated variational problemsCommunications on Pure and Applied Mathematics, 1989
- Snakes: Active contour modelsInternational Journal of Computer Vision, 1988
- Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of ImagesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1984