PECHERSKY , Eugene

Gibbs Fields are widely used in image processing for both segmentation and restoration. Defined on a discrete lattice representing the image they exhibit a non-isotropic behavior. Herein, we study and quantify this non-isotropy by computing the boundary tension as a function of the angle of a line separating the plane in two parts containing a...

We present a new model for extracting tree crowns from aerial images, containing a near infrared channel. We addres s the problem as an image segmentation problem solved by a Markov Random Field (MRF) modeling embedded in a Bayesian framework. The prior model consists of a couple field defined by a three state MRF, associated to vegetation,...

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In this work we propose a 2D discrete stochastic model for the simulation of axonal biogenesis. The model is defined by a third order Markov Chain. The model considers two main processes: the growth process that models the elongation and shape of the neurites and the bifurcation process that models the generation of branches. The growth process...