This paper proposes a framework for segmenting di erent textured areas over synthetic or real textured frames by curves propagation. We assume that the system has the ability to be taught over di erent texture prototypes. For each prototype a global statistical model is generated, as a set of probability density functions attributes from a multi-valued frame analysis, where di erent lter respon...

We present a methodology for the active control of time-harmonic wave fields, e.g., acoustic disturbances, in composite regions. This methodology extends our previous approach developed for the case of arcwise connected regions. The overall objective is to eliminate the effect of all outside field sources on a given domain of interest, i.e., to shield this domain. In this context, active shield...

This paper presents a novel variational method for image segmentation which is obtained by unifying boundary and region-based information sources under the Geodesic Active Region framework. A statistical analysis over the observed density function (image histogram) using a mixture of Gaussian elements, indicates the number of the di erent regions and their intensity properties. Then, the bounda...

An unsupervised approach to image segmentation which fuses region and boundary information is presented. The proposed approach takes advantage of the combined use of 3 different strategies: the guidance of seed placement, the control of decision criterion, and the boundary refinement. The new algorithm uses the boundary information to initialize a set of active regions which compete for the pix...

This paper presents a novel variational method for supervised texture segmentation. The textured feature space is generated by filtering the given textured images using isotropic and anisotropic filters, and analyzing their responses as multi-component conditional probability density functions. The texture segmentation is obtained by unifying region and boundary-based information as an improved...