DocumentCode :
3204164
Title :
Analyzing oriented textures through phase portraits
Author :
Rao, A.R. ; Jain, R.
Author_Institution :
IBM Thomas J. Watson Res. Center, Yorktown Heights, NY, USA
Volume :
i
fYear :
1990
fDate :
16-21 Jun 1990
Firstpage :
336
Abstract :
An attempt is made to develop a solution for signal-to-symbol transformation in the domain of flowlike or oriented texture. The geometric theory of differential equations is used to derive a symbol set based on the visual appearance of phase portraits. This theory provides a technique for describing textures both qualitatively and quantitatively. An attractive feature of this symbol set is that it is domain independent and makes no assumptions about the kind of texture that may be present. The computational framework for starting with a given oriented texture is provided, and its symbolic representation is derived. This is based on computing the orientation field for the texture and then using a nonlinear least-squares technique over successive windows to determine the changing spatial behavior of the texture. Results of the application of this technique to real texture images are presented
Keywords :
computer vision; differential equations; least squares approximations; surface texture; computer vision; differential equations; flowlike texture; geometric theory; nonlinear least-squares technique; orientation field; oriented textures; phase portraits; signal-to-symbol transformation; spatial behavior; symbol set; symbolic representation; Anisotropic magnetoresistance; Artificial intelligence; Computer vision; Differential equations; Electronic mail; Image segmentation; Image texture analysis; Least squares methods; Machinery; Signal analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 1990. Proceedings., 10th International Conference on
Conference_Location :
Atlantic City, NJ
Print_ISBN :
0-8186-2062-5
Type :
conf
DOI :
10.1109/ICPR.1990.118126
Filename :
118126
Link To Document :
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