DocumentCode
3515605
Title
Multifractal texture analysis and classification
Author
Anh, V.V. ; Maeda, Jukai ; Tieng, Q.M. ; Tsui, H.T.
Author_Institution
Centre in Stat. Sci. & Ind. Math., Queensland Univ. of Technol., Brisbane, Qld., Australia
Volume
4
fYear
1999
fDate
1999
Firstpage
445
Abstract
Existing fractal methods of texture analysis rely on the fractal dimension of textures as a function of scale for their discrimination and classification. We propose a method which is based on the possible multiscaling/multifractality of textures. A stochastic model is suggested to represent this multiscaling behaviour. We demonstrate the value of the method on a number of similar data sets (hence quite difficult for their discrimination) from the high-resolution Brodatz album
Keywords
data structures; image classification; stochastic processes; data sets; fractal methods; high-resolution Brodatz album; multifractal texture analysis; multifractality; multiscaling behaviour; stochastic model; texture classification; Computer industry; Computer science; Electronics industry; Fractals; Industrial electronics; Mathematics; Rough surfaces; Stochastic processes; Surface roughness; Systems engineering and theory;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing, 1999. ICIP 99. Proceedings. 1999 International Conference on
Conference_Location
Kobe
Print_ISBN
0-7803-5467-2
Type
conf
DOI
10.1109/ICIP.1999.819633
Filename
819633
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