✦ LIBER ✦

Spatial Models for Fuzzy Clustering

✍ Scribed by Dzung L. Pham

Publisher: Elsevier Science
Year: 2001
Tongue: English
Weight: 450 KB
Volume: 84
Category: Article
ISSN: 1077-3142
DOI: 10.1006/cviu.2001.0951

No coin nor oath required. For personal study only.

✦ Synopsis

A novel approach to fuzzy clustering for image segmentation is described. The fuzzy C-means objective function is generalized to include a spatial penalty on the membership functions. The penalty term leads to an iterative algorithm that is only slightly different from the original fuzzy C-means algorithm and allows the estimation of spatially smooth membership functions. To determine the strength of the penalty function, a criterion based on cross-validation is employed. The new algorithm is applied to simulated and real magnetic resonance images and is shown to be more robust to noise and other artifacts than competing approaches.

📜 SIMILAR VOLUMES

Modeling spatial relationships within a

Modeling spatial relationships within a fuzzy framework

✍ Cobb, Maria A. ;Petry, Frederick E. 📂 Article 📅 1998 🏛 John Wiley and Sons 🌐 English ⚖ 296 KB

In this article, we present a model for defining and repre-tative topological and directional relationships. In this senting binary topological and directional relationships article, ''qualitative topological relationships'' include between 2-dimensional objects that is used to provide both those re

A Java simulation tool for fuzzy cluster

A Java simulation tool for fuzzy clustering

✍ Egan, M. A.; Krishnamoorthy, M.; Rajan, K. 📂 Article 📅 1997 🏛 John Wiley and Sons 🌐 English ⚖ 93 KB 👁 3 views

Emerging technologies on the World Wide Web promise to make program, algorithm and concept simulations universally accessible, and Java appears to be the best technology available. Simulations involving animation and visualization have a tremendous benefit when applied to various algorithms. We pres

A method for fuzzy clustering with ordin

A method for fuzzy clustering with ordinal attributes

✍ Roelof K. Brouwer 📂 Article 📅 2007 🏛 John Wiley and Sons 🌐 English ⚖ 205 KB

A global algorithm for the fuzzy cluster

A global algorithm for the fuzzy clustering problem

✍ Khaled S Al-Sultan; Shokri Z Selim 📂 Article 📅 1993 🏛 Elsevier Science 🌐 English ⚖ 382 KB

Fuzzy model identification based on clus

Fuzzy model identification based on cluster estimation for reservoir inflow forecasting

✍ P. C. Nayak; K. P. Sudheer 📂 Article 📅 2008 🏛 John Wiley and Sons 🌐 English ⚖ 314 KB

## Abstract Fuzzy theory appears to be extremely effective at handling dynamic, non‐linear and noisy data, especially when the underlying physical relationships are not fully understood. Since hydrologists are still uncertain about many of the aspects of the physical processes in the watershed, fuz

FUZZY CLUSTERING FOR AUTOMATED TOOL COND

FUZZY CLUSTERING FOR AUTOMATED TOOL CONDITION MONITORING IN MACHINING

✍ S. Li; M.A. Elbestawi 📂 Article 📅 1996 🏛 Elsevier Science 🌐 English ⚖ 397 KB

A strategy for unsupervised classification for automated tool condition monitoring by using fuzzy neural networks is proposed. This approach is based on a newly developed classification algorithm by the authors, namely the multiple principal component fuzzy neural network for tool condition monitori