scholarly journals Fractal Dimension Based Texture Analysis of Digital Images

2012 ◽  
Vol 38 ◽  
pp. 2981-2986 ◽  
Author(s):  
P. Shanmugavadivu ◽  
V. Sivakumar
Keyword(s):  
Fractal Dimension ◽  
Texture Analysis ◽  
Digital Images

scholarly journals Estimation of fractal dimension and fractal curvatures from digital images

2015 ◽  
Vol 75 ◽  
pp. 134-152 ◽  
Author(s):  
Evgeny Spodarev ◽  
Peter Straka ◽  
Steffen Winter
Keyword(s):  
Fractal Dimension ◽  
Digital Images

Estimation of qth-Order Fractal Dimensions

Fractals ◽  
1997 ◽  
Vol 05 (supp01) ◽  
pp. 257-269 ◽  
Author(s):  
Stefano Fioravanti ◽  
Daniele D. Giusto
Keyword(s):  
Image Processing ◽  
Fractal Dimension ◽  
Texture Analysis ◽  
Digital Image Processing ◽  
Digital Image ◽  
State Of The Art ◽  
Fractal Dimensions ◽  
Sar Image ◽  
Spectrum Function ◽  
Novel Algorithm

The paper deals with the theory of qth-order fractal dimensions and its application to texture analysis. In particular, the state-of-the-art regarding the fractal dimension estimation for characterizing textures is presented. After, the insufficiency of the single fractal dimension is proven and the qth order fractal dimensions are introduced to overcome such drawback. The multifractality spectrum function D(q) is described, a novel algorithm for estimating such dimensions is then proposed, and its use in digital-image processing is addressed. Results on real SAR image textures are reported and discussed.

ON TEXTURE CLASSIFICATION USING FRACTAL DIMENSION

1999 ◽  
Vol 13 (06) ◽  
pp. 929-943 ◽  
Author(s):  
YAN QIU CHEN ◽  
GUOAN BI
Keyword(s):  
Fractal Dimension ◽  
Texture Analysis ◽  
Texture Classification ◽  
Texture Feature ◽  
Experimental Results ◽  
Image Texture ◽  
Feature Sets ◽  
Mathematical Properties ◽  
Underlying Causes

The fractal dimension has been studied as a feature for texture analysis. It has been found that the fractal dimension is not an effective image texture measure but little is known about the reasons for the fractal dimension failing to be effective for texture analysis. This paper investigates into the underlying causes why the fractal dimension is not an effective image texture feature. Four mathematical properties have been identified which are responsible for the fractal dimension's ineffectiveness. The experimental results show that while the fractal dimension itself is hardly an effective feature for texture classification, it can considerably enhance other feature sets.

Multiscale Fractal Texture Analysis Using Morphological Techniques

Fractals ◽  
1997 ◽  
Vol 05 (supp01) ◽  
pp. 125-131 ◽  
Author(s):  
Antony T. Popov
Keyword(s):  
Fractal Dimension ◽  
Texture Analysis ◽  
Mathematical Morphology ◽  
Parallel Implementation ◽  
Linear Transformations ◽  
Extrinsic Factors

Fractal dimension is used to analyse texture images. Since the fractal dimension remains unchanged under linear transformations, presented method is robust for dismissing effects caused by lighting and other extrinsic factors. The methods of mathematical morphology are used to calculate the fractal (Bouligand) dimension. A parallel implementation of morphological blanket covering is proposed.

Fractal dimension of maximum response filters applied to texture analysis

2015 ◽  
Vol 65 ◽  
pp. 116-123 ◽  
Author(s):  
Lucas Correia Ribas ◽  
Diogo Nunes Gonçalves ◽  
Jonatan Patrick Margarido Oruê ◽  
Wesley Nunes Gonçalves
Keyword(s):  
Fractal Dimension ◽  
Texture Analysis ◽  
Maximum Response

Natural texture analysis in a multiscale context using fractal dimension

1991 ◽  
Author(s):  
Kidiyo Kpalma ◽  
Alain Bruno ◽  
Veronique Haese-Coat
Keyword(s):  
Fractal Dimension ◽  
Texture Analysis
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