DocumentCode :
2202996
Title :
Analysis of texture images using robust fractal description
Author :
Avadhanam, Niranjan ; Mitra, Sunanda
Author_Institution :
Dept. of Electr. & Comput. Eng., California Univ., Davis, CA, USA
fYear :
1994
fDate :
21-24 Apr 1994
Firstpage :
1
Lastpage :
6
Abstract :
A maximum likelihood estimation (MLE) method is used to estimate the fractal dimension of a number of natural texture images with and without the presence of noise. An additional texture measure which can be linked to the lacunarity measure is used to characterize natural textures since fractal dimension alone cannot totally characterize texture images. Segmentation of natural textures is successfully achieved by a k-means clustering algorithm using fractal dimension and the additional measure as representative features
Keywords :
fractals; image segmentation; image texture; maximum likelihood estimation; fractal description; fractal dimension estimation; k-means clustering algorithm; lacunarity measure; noise; texture image analysis; texture measure; texture segmentation; Clustering algorithms; Computer vision; Fractals; Image analysis; Image motion analysis; Image segmentation; Image texture analysis; Maximum likelihood estimation; Polymers; Robustness;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Analysis and Interpretation, 1994., Proceedings of the IEEE Southwest Symposium on
Conference_Location :
Dallas, TX
Print_ISBN :
0-8186-6250-6
Type :
conf
DOI :
10.1109/IAI.1994.336692
Filename :
336692
Link To Document :
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