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
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