DocumentCode :
703060
Title :
An identification method for texture AR-2D modelling based on auto- and partial correlation measures
Author :
Claude, Isabelle ; Smolarz, Andre
Author_Institution :
Lab. de Modelisation et Surete des Syst., Univ. de Technol. de Troyes, Troyes, France
fYear :
1998
fDate :
8-11 Sept. 1998
Firstpage :
1
Lastpage :
4
Abstract :
This paper deals with the identification of the model order for a bidimensional autoregressive (AR-2D) texture model. It means the automatic choice of the number of neighbours in the prediction set of the model and their spatial position. The method, called mixed correlation method is based on partial and autocorrelation measures and fastly and efficiently allows to find an adapted model for all microtextures. In a textured samples classification procedure, these adapted models improve the percentage of good classification in comparison with a classical approach consisting in taking the same prediction set for all the textures.
Keywords :
autoregressive processes; correlation methods; image classification; image texture; set theory; auto correlation measure; bidimensional autoregressive texture model; mixed correlation method; model order identification method; model prediction set; partial correlation measure; sample classification procedure; texture AR-2D modelling; Adaptation models; Correlation; Layout; Mathematical model; Predictive models; Silicon carbide; Wool;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing Conference (EUSIPCO 1998), 9th European
Conference_Location :
Rhodes
Print_ISBN :
978-960-7620-06-4
Type :
conf
Filename :
7089530
Link To Document :
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