In this paper a combined statistical and structural approach has been employed for texture representation. A set of Texture Primitives has been suggested. These primitives are basically tested for the presence of texture by conducting a suitable statistical test called Nair’s test. The set of universal primitives are labeled as local descriptor and the frequency of occurrences of these primitiv...

This paper presents a texture descriptor for color texture classification specially designed to be robust against changes in the illumination conditions. The descriptor combines a histogram of local binary patterns (LBPs) with a novel feature measuring the distribution of local color contrast. The proposed descriptor is invariant with respect to rotations and translations of the image plane and...

a r t i c l e i n f o Extracting local keypoints and keypoint descriptions from images is a primary step for many computer vision and image retrieval applications. In the literature, many researchers have proposed methods for representing local texture around keypoints with varying levels of robustness to photometric and geometric transformations. Gradient-based descriptors such as the Scale In...

We describe and demonstrate a texture region descriptor which is invariant to affine geometric and photometric transformations, and insensitive to the shape of the texture region. It is applicable to texture patches which are locally planar and have stationary statistics. The novelty of the descriptor is that it is based on statistics aggregated over the region, resulting in richer and more sta...

Making recognition more reliable under uncontrolled lighting conditions is one of the most important challenges for practical face recognition systems. Other recognition systems don’t nullify most of the lighting variations. We tackle this by combining the strengths of robust illumination normalization, local texture-based face representations, distance transform based matching and kernel based...

in this paper, we used a shape matching algorithm to recognize farsi digits. for each sampled point on the contour of a shape, we obtain a descriptor showing the distribution of the other points of the contour, with respect to this point. based on these descriptors, we find the corresponding points of the two contours and take the sum of their distances as a dissimilarity measure between two sh...

In this paper, we present a tracking technique utilizing a simple saliency visual descriptor. Initially, we define a visual descriptor named local similarity pattern that mimics the famous texture operator local binary patterns. The key difference is that it assigns each pixel a code based on the similarity to the neighbouring pixels. Later, we simplify this descriptor to ...

This paper proposes a novel approach to encode cross-channel texture correlation for color texture classification task. Firstly, we quantitatively study the correlation between different color channels using Local Binary Pattern (LBP) as the texture descriptor and using Shannon’s information theory to measure the correlation. We find that (R, G) channel pair exhibits stronger correlation than (...