DocumentCode
379855
Title
Texture segmentation using Shanon wavelet
Author
El Taweel, Salah ; Darwish, Ahmed M.
Author_Institution
Nat. Telecommun. Inst., Cairo, Egypt
fYear
1998
fDate
4-7 Oct 1998
Firstpage
343
Abstract
In this paper, we present an approach to texture segmentation that utilizes the Hurst coefficient or the fractal dimension computed along the 1-D cross sections of 2-D texture data. These coefficients are computed utilizing the Shanon wavelet fractal estimation algorithm using a maximum likelihood estimate. These coefficients are considered the feature vector which is used to achieve segmentation using supervised or unsupervised techniques. The major advantage of the Shanon fractal estimator is its simplicity due to the pyramid structure used. The approach has been tested on real brodatz textures and outdoor scenes and yielded the appropriate segmentation
Keywords
feature extraction; fractals; image segmentation; image texture; maximum likelihood estimation; wavelet transforms; 1D cross sections; 2D texture data; Hurst coefficient; Shanon wavelet fractal estimation algorithm; feature vector; fractal dimension; image segmentation; maximum likelihood estimation; outdoor scenes; pyramid structure; real brodatz textures; supervised techniques; texture segmentation; unsupervised techniques; Brownian motion; Feature extraction; Fractals; Image segmentation; Maximum likelihood detection; Maximum likelihood estimation; Rough surfaces; Surface roughness; Surface waves; Telecommunication computing;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing, 1998. ICIP 98. Proceedings. 1998 International Conference on
Conference_Location
Chicago, IL
Print_ISBN
0-8186-8821-1
Type
conf
DOI
10.1109/ICIP.1998.999024
Filename
999024
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