In this paper wk have used two fuzzy clustering algorithms, namely Fuzzy C-Means (FCM) and Gustafson Kessel Clustering (GKC) for unsupervised change detection in multitemporal remote sensing images. In conventional FCM & GKC no spatio-contextual information is taken into account and thus the result is not so much robust to noise/outliers. By incorporation of local neighborhood informationthe pe...

With advances technologies of Internet and new digital image, the volume of digital images produced by scientific, educational, medical, industrial, and other applications has increased dramatically. The paper was inspired by symmetrical study about an image and also we tried to apply edge detection using Phase Congruency method that proposed by Kovesi. We tried making comparative study on edge...

We explore an approach to possibilistic fuzzy clustering that avoids a severe drawback of the conventional approach, namely that the objective function is truly minimized only if all cluster centers are identical. Our approach is based on the idea that this undesired property can be avoided if we introduce a mutual repulsion of the clusters, so that they are forced away from each other. We deve...

A Fick’s model that includes a Takagi-Sugeno fuzzy model to estimate the effective diffusivity was analyzed. The modelling of drying kinetics on mango trough this diffusional-fuzzy model was compared with the theoretical Fick’s model and the empirical Peleg and Weibull models. The identification and validation was performed from experimental drying curves of ripe mango slices (Mangifera indica ...

Two extensions to the objective function-based fuzzy clustering are proposed. First, the (point) prototypes are extended to hypervolumes, whose size can be fixed or can be determined automatically from the data being clustered. It is shown that clustering with hypervolume prototypes can be formulated as the minimization of an objective function. Second, a heuristic cluster merging step is intro...

This paper describes a method for designing a lter bank for segmenting modulation features in line textures. A new version of the S-Gabor lter of Heitger et al 1] is developed in which the range of frequencies covered by the lter can be easily controlled. A method of tuning S-Gabor lters to modulation features in line textures is also presented. The candidate frequency set is obtained by select...

Image segmentation is a process by which an image is partitioned into regions with similar features. Many approaches have been proposed for color image segmentation, but Fuzzy C-Means has been widely used, because it has a good performance in a large class of images. However, it is not adequate for noisy images and it also takes more time for execution as compared to other method as K-means. Fo...

A fuzzy classifier using multiple ellipsoids approximating decision regions for classification is to be designed in this paper. An algorithm called Gustafson-Kessel algorithm (GKA) with an adaptive distance norm based on covariance matrices of prototype data points is adopted to learn the ellipsoids. GKA is able to adapt the distance norm to the underlying distribution of the prototype data poi...

Some of the well-known fuzzy clustering algorithms are based on Euclidean distance function, which can only be used to detect spherical structural clusters. Gustafson-Kessel clustering algorithm and Gath-Geva clustering algorithm were developed to detect non-spherical structural clusters. However, the former needs added constraint of fuzzy covariance matrix, the later can only be used for the d...

mechanisms other than those implied by these three “Preformation is represented by DNA, not by . . . a tiny models can at least refine anteroposterior pattern. For adult in every sperm . . .” example, the prechordal mesendoderm emits signals —Antonio Garcı́a-Bellido (1998) that can anteriorize the hindbrain (Dale et al., 1997; Foley “The key to understanding how genomic regulatory et al., 1997; ...