NDLI: The Markov random fields in functional neighbors as a texture model: applications in texture classification

Content Provider	IEEE Xplore Digital Library
Author	Mosquera, A. Cabello, D.
Copyright Year	1996
Description	Author affiliation: Dept. of Electron. & Comput., Santiago de Compostela Univ., Spain (Mosquera, A.)
Abstract	The main objective of this work is to design an approach for the study of textures that is capable of handling textures of different sizes in the same resolution scale. In addition, we want this approach to be independent from the images it analyzes in order to make it valid for the largest possible number of application fields. These considerations have led us to using a Markov random field model in which we have modified its probabilistic dependence so that it is capable of analyzing microtextures and macrotextures simultaneously. These modifications are carried out by means of the introduction of a new non-standard system of neighbors, called functional neighbors. Finally, we show how Markov's random field with a system of functional neighbors provides better results in texture classification tasks than with a system of physical neighbors.
Starting Page	815
Ending Page	819
File Size	630244
Page Count	5
File Format	PDF
ISBN	081867282X
ISSN	10514651
DOI	10.1109/ICPR.1996.547189
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1996-08-25
Publisher Place	Austria
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Markov random fields Image analysis Image recognition Stochastic processes Image texture analysis Character recognition Probability distribution Mathematical model Noise level
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition

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