Rohini A. Bhusnurmath

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Texture is a rich source of visual information about the surface characteristics of an object in the digital image. So texture characteristics play an important role in texture image classification. In this paper, we propose a novel approach of texture image classification based on nonsubsampled contourlet transform (NSCT) and local directional binary(More)
Texture classification plays an important role in computer vision and image processing applications, which has received considerable attention over the last several decades. In this paper, diffusion approach for texture analysis based on anisotropic diffusion and local directional binary patterns (LDBP) is presented. The proposed approach uses partial(More)
In the present paper, a novel method of partial differential equation (PDE) based features for texture analysis using wavelet transform is proposed. The aim of the proposed method is to investigate texture descriptors that perform better with low computational cost. Wavelet transform is applied to obtain directional information from the image. Anisotropic(More)
Textures and patterns are the distinguishing characteristics of objects. Texture classification plays fundamental role in computer vision and image processing applications. In this paper, texture classification using PDE (partial differential equation) approach and wavelet transform is presented. The proposed method uses wavelet transform to obtain the(More)
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