This paper presents a novel fully automated unsupervised framework for the brain tissue segmentation in magnetic resonance (MR) images. The framework is a combination of Bayesian-based adaptive mean shift, a priori spatial tissue probability maps and fuzzy c-means. Mean shift is employed to cluster the tissues in the joint spatial-intensity feature space and then a fuzzy c-means is applied with...

This paper presents the results of a new approach for binarization of text images. The new technique uses the fuzzy C-means clustering algorithm to simulate the clustering performed by the human visual system. The clustering process was applied to eleven text images. All of them have black text but the background change in color. As a mean of comparison, binarization using the image histogram w...

In the paper, we proposed a model called Adaptive Threshold Level Set Without Edge that is applied on the segmentation of GM in brain MR images. Threshold to find the boundary of GM is automatically obtained by fuzzy c mean algorithm. A similarity index (SI) is used for quantitative evaluation of the segmentation results. By testing 134 planar MR brain images and comparing to the gold standard ...

The aim of this paper is to extend the classical problem of confidence interval estimation for the mean of a random variable to the case of a fuzzy random variable. The key idea consists in considering a confidence region defined as a ball w.r.t. a given metric, which is centered in the sample mean and whose radius is determined via bootstrapping. The developed approach is illustrated both by m...

We present in this paper a method of image segmentation (T-CAAR) based on a fuzzy logic tree. The construction of the classes corresponding to regions of interest has been made by an upset of membership function and a fusion operator into a tree structure. The comparison of this method with fuzzy c-mean, mean shift and watershed allows using an appropriate technique for biotechnological bioproc...

The paper proposed the adaptive noise suppression technique for suppression of noise in voice communication. There are different techniques earlier used for adaptive filteration like least mean square, kalman’s filter etc.In the paper we used “fuzzy logic” technique for adaptive filteration. We know about the theory of adptive filteration of noise and application of fuzzy logic. We are using th...

barrett's mucosa is one of the most important diseases in upper gastrointestinal system that caused by gastroesophagus reflux. if left untreated, the disease will cause distal esophagus and gastric cardiaadenocarcinoma. the malignancy risk is very high in short segment barrett’s mucosa. therefore,lesion area segmentation can improve specialist decision for treatment. in this paper, we proposeda...