Texture classification is mainly used for segmentation of texture regions and content-based access to image databases. Lately these texture classification patterns have been appl...
Abstract. This paper proposes a novel method to deal with the representation issue in texture classification. A learning framework of image descriptor is designed based on the Fish...
This paper proposes a new texture classification approach. There are two main contributions in the proposed method. First, input texture images are transformed to the composite Fo...
Texture classification is a classical yet still active topic in computer vision and pattern recognition. Recently, several new texture classification approaches by modeling textur...
Local Binary Pattern (LBP) has been widely used in texture classification because of its simplicity and computational efficiency. Traditional LBP codes the sign of the local diffe...
In this paper, we propose a new feature extraction method, which is robust against rotation and histogram equalization for texture classification. To this end, we introduce the co...
In this paper, we present a new method for texture classification which we call the regularized simultaneous autoregressive method (RSAR). The regularization technique is introduc...
Abstract. Since texture is scale dependent, multi-scale techniques are quite useful for texture classification. Scale-space theory introduces multi-scale differential operators. In...
Mehrdad J. Gangeh, Bart M. ter Haar Romeny, C. Esw...
Using statistical textons for texture classification has shown great success recently. The maximal response 8 (MR8) method, which extracts an 8-dimensional feature set from 38 filt...
Experimental results of texture features derived from Gabor and other four wavelet transforms classified and clustered based on Support Vector Machine (SVMs) and Self-Organizing M...