Brain tumor is most vital disease which commonly penetrates in the human beings. Studies based on brain tumor confirm that people affected by brain tumors die due to their erroneous detection. In this paper, an enhanced Fuzzy CMeans segmentation (FCM) technique is proposed for detecting brain tumor. To justify the performance of the proposed method, a comparative analysis is being carried out w...

search pointers organize the main part of the application on the internet. however, because of information management hardware, high volume of data and word similarities in different fields the most answers to the user s’ questions aren`t correct. so the web graph clustering and cluster placement in corresponding answers helps user to achieve his or her intended results. community (web communit...

Zoning the pollution of a river may be the first or even the most important step in water quality management. In order to resolve its pollution, fuzzy clustering analysis may be used whenever a composite classification of water quality incorporates mutiple parameters&#10 &#10In such cases, the technique may be used as a complement or an alternative to comprehensive assessment. In fuzzy cluster...

Dermoscopy is one of the major imaging aspects used in the skin lesions. This paper presentsa new tacticfor the segmentation of skin abrasionsin dermoscopic images based on fuzzy Cmeans algorithm learned wavelet network (WN). The WN offeredhere is a member of fixed-grid WNs that is designedwith no requirementof training. Fuzzy C-means techniqueis used to enhancethe network structure. In additio...

A new online clustering method, called E2GK (Evidential Evolving Gustafson-Kessel) is introduced in the theoretical framework of belief functions. The algorithm enables an online partitioning of data streams based on two existing and efficient algorithms: Evidantial cMeans (ECM) and Evolving Gustafson-Kessel (EGK). E2GK uses the concept of credal partition of ECM and adapts EGK, offering a bett...

Zoning the pollution of a river may be the first or even the most important step in water quality management. In order to resolve its pollution, fuzzy clustering analysis may be used whenever a composite classification of water quality incorporates mutiple parameters In such cases, the technique may be used as a complement or an alternative to comprehensive assessment. In fuzzy clustering ...

image segmentation is an essential issue in image description and classification. currently, in many real applications, segmentation is still mainly manual or strongly supervised by a human expert, which makes it irreproducible and deteriorating. moreover, there are many uncertainties and vagueness in images, which crisp clustering and even type-1 fuzzy clustering could not handle. hence, type-...

The classification of the electrocardiogram registration into different pathologies diseases devises is a complex pattern recognition task. The traditional methods of diagnosis and classification present some inconveniences; seen that the precision of credit note one diagnosis exact depends on the cardiologist experience and the rate concentration. Due to the high mortality rate of heart diseas...

In this project the image segmentation using Fuzzy Cmeans algorithm and kernel metric. In FCM algorithm by introducing a trade-off weighted fuzzy factor and kernel metric. This factor depends on the space distance of all neighboring pixels and their gray-level difference simultaneously. So we propose generalised rough set FCM algorithm in order to further enhance its robustness to noise and out...