Paper Info
Title
Perception-based fuzzy partitions for visual texture modeling.
Abstract
Visual textures in images are usually described by humans using linguistic terms related to their perceptual properties, like “very coarse”, “low directional”, or “high contrasted”. Computational models with the ability of providing a perceptual texture characterization on the basis of these terms can be very useful in tasks like semantic description of images, content-based image retrieval using linguistic queries, or expert systems design based on low level visual features. In this paper, we address the problem of simulating the human perception of texture, obtaining linguistic labels to describe it in natural language. For this modeling, fuzzy partitions defined on the domain of some of the most representative measures of each property are employed. In order to define the fuzzy partitions, the number of linguistic labels and the parameters of the membership functions are calculated taking into account the relationship between the computational values given by the measures and the human perception of the corresponding property. The performance of each fuzzy partition is analyzed and tested using the human assessments, and a ranking of measures is obtained according to their ability to represent the perception of the property, allowing to identify the most suitable measure.
Year
DOI
Venue
2018
10.1016/j.fss.2017.04.015
Fuzzy Sets and Systems
Keywords
Field
DocType
Image analysis,Feature extraction,Texture modeling,Fuzzy partitions,Linguistic labels,Human perception
Ranking,Expert system,Fuzzy logic,Image retrieval,Feature extraction,Natural language,Computational model,Natural language processing,Artificial intelligence,Perception,Mathematics,Machine learning
Journal
Volume
ISSN
Citations 
337
0165-0114
0
PageRank 
References 
Authors
0.34
35
3
Name
Order
Citations
PageRank
Pedro Manuel Martínez-Jiménez1205.73
Jesús Chamorro-Martínez26714.73
José Manuel Soto-Hidalgo3206.04