Hausdorff accurate estimation of density level sets is relevant in applications where a spatially uniform mode of convergence is desired to ensure that the estimated set is close to the target set at all points. The minimax optimal rate of error convergence for the Hausdorff metric is known to be (n/ logn) for level sets with Lipschitz boundaries, where the parameter α characterizes the regular...

System-level design requires some sort of speciica-tion for a system at the level of abstraction of the system. When the system (or subsystem) is a processor, the appropriate level of abstraction is the instruction set. However, there are no good approaches for describing processors at this level. Nevertheless, this type of speciication has a number of beneets: it is more concise (and thus less...

Segmentation is a vital aspect of medical imaging. It aids in the visualization of medical data and diagnostics of various dieses. This report presents an implementation of a level set approach for active contour image segmentation. This method is originally developed by Osher and Sethian and then applied to image segmentation by Malladi. No requirements about objects’ shape and allowance for v...

Segmentation of motion in an image sequence is one of the most challenging problems in image processing, while at the same time one that finds numerous applications. To date, a wealth of approaches to motion segmentation have been proposed. Many of them suffer from the local nature of the models used. Global models, such as those based on Markov random fields, perform, in general, better. In th...

This paper presents a new general framework for image segmentation. A level set formulation is used to model the boundaries of the image regions and a new Multi-Label Fast Marching is introduced for the evolution of the region contours towards the segmentation result. Statistical tests are performed to yield an initial estimate of high-con dence subsets of the image regions. Furthermore, the ve...

We suggest a variational method for the joint estimation of optic flow and the segmentation of the image into regions of similar motion. It makes use of the level set framework following the idea of motion competition, which is extended to non-parametric motion. Moreover, we automatically determine an appropriate initialization and the number of regions by means of recursive two-phase splits wi...

We present a new approach for non-rigid surface-registration of 3D objects. By representing the surfaces as the zero-level of a signed distance function in 3D space, our algorithm becomes independent of topology. We propose an extension of Thirion’s Demons algorithm to register the distance images. Our extension includes the use of a curvature term to guide the registration in the direction tan...

The Bernoulli convolution associated to the real β > 1 and the integer d ≥ β is a probablilty measure ηβ,d on R, solution of the self-similarity relation η = d−1 ∑ k=0 pk ·η◦Sk where (p0, . . . , pd−1) is a probabililty vector and Sk(x) = x+k β . If β is an integer or a Pisot algebraic number, the study of this measure is close to the study of the order of growth of the number of representation...

in this work, we define a fuzzy soft set theory and its related properties. we then define fuzzy soft aggregation operator that allows constructing more efficient decision making method. finally, we give an example which shows that the method can be successfully applied to many problems that contain uncertainties.

We consider a multiple-rule, generalized modus ponens inference scheme, with an interpretation based on compositional rule of inference (CRI) and a residuated implication. We show that such a system is equivalent, as far as CRI is concerned, to a system that satis5es the “basic requirement for fuzzy reasoning”, proposed by Turksen and Tian (Fuzzy Sets and Systems 58 (1993) 3–40). We establish a...