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In view of the over- and under-segmentation problems existed in the conventional image segmentation based on rough-set theory, an novel color image segmentation approach based on Rough-Set theory is presented in this paper. Firstly, the new distance has been defined by using the vector angle and Euclidean distance. And then according to the new distance, the space binary matrixes that represent the...
One limitation of the fuzzy rough sets is its sensitivity to the perturbation of original numerical data. In this paper we construct a model of fuzzy variable precision rough sets (FVPRS) by combining the fuzzy rough sets and variable precision rough sets, which is non-sensitive to the perturbation of the original numerical data. First, the fuzzy lower and upper approximations of FVPRS model are defined,...
Recently, many methods based on fuzzy rough sets are proposed to reduce fuzzy attributes. The common characteristic of these methods is that all of them are based on fuzzy equivalence relation. In other words, the underlying concept of rough sets, indispensability relation, is generalized to fuzzy equivalence relation. Here fuzzy equivalence relation is the binary relation, which is reflexive, symmetric...
To induce rules from numerical data by rough sets, there are two kinds of methods. One is to discretize the original data and then apply the crisp rough sets models. Here the rough sets models which can only deal with the nominal data are called crisp rough sets models. The other is to fuzzify the original data and then apply fuzzy rough sets models. There are some problems on both of these methods...
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