Paper Info
Title
Retrieving Texture Images Using Coarseness Fuzzy Partitions
Abstract
In this paper, a Fuzzy Dominant Texture Descriptor is proposed for semantically describing an image. This fuzzy descriptor is defined over a set of fuzzy sets modelling the "coarseness" texture property. Concretely, fuzzy partitions on the domain of coarseness measures are proposed, where the number of linguistic labels and the parameters of the membership functions are calculated relating representative coarseness measures (our reference set) with the human perception of this texture property. Given a "texture fuzzy set", its dominance in an image is analyzed and the dominance degree is used to obtain the image texture descriptor. Fuzzy operators over these descriptors are proposed to define conditions in image retrieval queries. The proposed framework makes database systems able to answer queries using texture-based linguistic labels in natural language.
Year
DOI
Venue
2010
10.1007/978-3-642-14058-7_56
IPMU (2)
Keywords
Field
DocType
fuzzy set,image texture,database system,human perception,image retrieval,membership function,natural language
Data mining,Texture Descriptor,Pattern recognition,Image texture,Fuzzy logic,Image retrieval,Fuzzy set,Natural language,Fuzzy operators,Artificial intelligence,Membership function,Mathematics
Conference
Volume
ISSN
Citations 
81
1865-0929
0
PageRank 
References 
Authors
0.34
16
3
Name
Order
Citations
PageRank
Jesús Chamorro-Martínez16714.73
Pedro Manuel Martínez-Jiménez2205.73
José Manuel Soto-Hidalgo3206.04