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
Link To Document :
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