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  Texture Classification Based on Extraction of Skeleton Primitives Using Wavelets
 
 
Titel: Texture Classification Based on Extraction of Skeleton Primitives Using Wavelets
Auteur: U.S.N. Raju
B. Eswara Reddy
V. Vijaya Kumar
B. Sujatha
Verschenen in: Information technology journal
Paginering: Jaargang 7 (2008) nr. 6 pagina's 883-889
Jaar: 2008
Inhoud: A novel method for dominant skeleton extraction of textures using different wavelet transforms, is proposed in this study. The skeleton varies depending on the shape of structuring element. If the structuring element is homothetic to the object, the object is covered with only one magnification of the structuring element. By this, the skeleton is reduced to one point. The present study considers the skeleton from a binary texture. The proposed method derives from the above that a total number of pixels within the skeleton is the minimum when structuring element is homothetic to the primitive. This provides the scope that the texture is composed of one primitive, which minimizes the total number of pixels. For evaluating such skeleton primitive the present study utilized a 3x3 structuring element, as the skeleton primitives. All possible skeleton primitives combinations of 3x3 mask are evaluated on all textures. The skeleton primitive that is making the least number of skeleton points is considered as dominant skeleton primitive. Based on the extraction of skeleton primitives a classification is made on textures using Haar, Daubechies, Coiflet and Symlet wavelets. Experimental results indicate a good classification and also a comparison is made among these four wavelet results. Present method is experimented on Brodatz textures using these four wavelets.
Uitgever: Asian Network for Scientific Information (provided by DOAJ)
Bronbestand: Elektronische Wetenschappelijke Tijdschriften
 
 

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