Fuzzy Rough Set Approach for Selecting the Most Significant Texture Features in Mammogram Images

2013 ◽  
Author(s):  
B. O. Alijla ◽  
A. T. Khader ◽  
Lim Chee Peng ◽  
M. A. Al-Betar ◽  
Wong Li Pei
Keyword(s):  
Rough Set ◽  
Texture Features ◽  
Fuzzy Rough Set ◽  
Mammogram Images

Research on Facial Expression Recognition Based on Variable Precision Fuzzy Rough Set

2013 ◽  
Vol 411-414 ◽  
pp. 1228-1232
Author(s):  
Xi Wen Qin ◽  
Han Lin ◽  
Xiao Gang Dong ◽  
Hong Yu Zhang
Keyword(s):  
Facial Expression ◽  
Rough Set ◽  
Facial Expression Recognition ◽  
Texture Features ◽  
Expression Recognition ◽  
Fuzzy Rough Set ◽  
Recognition Process ◽  
Variable Precision ◽  
Starting Point ◽  
Mixing Characteristics

In this paper, facial expression recognition as the starting point, it is extracted the mixing characteristics of the facial expression, including geometric and texture features. It can solve the problem of the collection contains the degree based on Variable Precision Fuzzy Rough Set, It could improved the accuracy of facial expression recognition using the method, thus making the facial expression recognition process more accurate and efficient.

Bipolar fuzzy rough set model on two different universes and its application

2012 ◽  
Vol 35 ◽  
pp. 94-101 ◽  
Author(s):  
Hai-Long Yang ◽  
Sheng-Gang Li ◽  
Shouyang Wang ◽  
Jue Wang
Keyword(s):  
Rough Set ◽  
Fuzzy Rough Set

GENERALIZED FUZZY ROUGH SETS BY CONDITIONAL PROBABILITY RELATIONS

2002 ◽  
Vol 16 (07) ◽  
pp. 865-881 ◽  
Author(s):  
ROLLY INTAN ◽  
MASAO MUKAIDONO
Keyword(s):  
Conditional Probability ◽  
Rough Set ◽  
Real World ◽  
Rough Sets ◽  
Similarity Relation ◽  
Fuzzy Rough Set ◽  
Fuzzy Similarity ◽  
Fuzzy Similarity Relation ◽  
Real World Applications ◽  
The Universe

In 1982, Pawlak proposed the concept of rough sets with a practical purpose of representing indiscernibility of elements or objects in the presence of information systems. Even if it is easy to analyze, the rough set theory built on a partition induced by equivalence relation may not provide a realistic view of relationships between elements in real-world applications. Here, coverings of, or nonequivalence relations on, the universe can be considered to represent a more realistic model instead of a partition in which a generalized model of rough sets was proposed. In this paper, first a weak fuzzy similarity relation is introduced as a more realistic relation in representing the relationship between two elements of data in real-world applications. Fuzzy conditional probability relation is considered as a concrete example of the weak fuzzy similarity relation. Coverings of the universe is provided by fuzzy conditional probability relations. Generalized concepts of rough approximations and rough membership functions are proposed and defined based on coverings of the universe. Such generalization is considered as a kind of fuzzy rough set. A more generalized fuzzy rough set approximation of a given fuzzy set is proposed and discussed as an alternative to provide interval-value fuzzy sets. Their properties are examined.

Unsupervised fuzzy-rough set-based dimensionality reduction

2013 ◽  
Vol 229 ◽  
pp. 106-121 ◽  
Author(s):  
Neil Mac Parthaláin ◽  
Richard Jensen
Keyword(s):  
Dimensionality Reduction ◽  
Rough Set ◽  
Fuzzy Rough Set
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