A Coarse-to-Fine Deformable Contour Optimization Framework
IEEE Transactions on Pattern Analysis and Machine Intelligence
A bin picking system based on depth from defocus
Machine Vision and Applications
Comparison of Multiscale Representations for a Linking-Based Image Segmentation Model
MMBIA '96 Proceedings of the 1996 Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA '96)
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Multiscale approaches are an invaluable tool for image segmentation. A vast amount of research has been devoted to the construction of different multiscale representations of an image. In this paper we use the `hyperstack'--a multiscale linking model for image segmentation--for an in-depth comparison of four different scale space generators with respect to segmentation results. We consider the linear (Gaussian) scale space both in the spatial and the Fourier domain, the variable conductance diffusion according to the Perona & Malik equation, and the Euclidean shortening flow. We have done experiments on MR images of the brain, for which a gold standard is available. The hyperstack proofs to be rather insensitive to the underlying scale space generator.