@INCOLLECTION { Rsds4817,
author = {Malyszko, Dariusz and Stepaniuk, Jaroslaw}, 
title = {Fuzzy Rough Entropy Clustering Algorithm Parametrization}, 
booktitle = {Man-Machine Interactions}, 
series =  = {Advances in Soft Computing}, 
volume = 59, 
pages = {239--246}, 
publisher = {Springer-Verlag}, 
address = {Heidelberg - Berlin, Germany}, 
year = 2009, 
url = {http://www.springerlink.com/content/ug20472t6465/?p=fd8a7f09865b491dbbc1e1c4c154629f&pi=8}, 
isbn = {978-3-642-00562-6}, 
abstract = {Image processing represents active research area that requires advanced and sophisticated methods capable of handling novel emerging imagery technologies. Adequate and precise capture and image interpretation is primarily based on proper image segmentation. Advances in correct image partitioning are still embracing new research areas such as fuzzy sets, rough sets and rough fuzzy sets. Present research concentrates on new rough entropy clustering algorithm Fuzzy RECA Rough Entropy Clustering Algorithm and extension relative to distance threshold and fuzzy threshold, namely its parameters having impact on rough entropy calculation. Different rough entropy measures are calculated and incorporated into Fuzzy RECA based clustering algorithm on satellite image data set. Presented results suggest that proposed fuzzy thresholds capture properly image properties and it is possible to take advantage of these characteristics in real image processing applications.}, 
keywords = {granular computing, standard and fuzzy rough entropy clustering algorithm, image clustering, rough sets, fuzzy sets, rough fuzzy sets, }, 
}