Material recognition has several applications, such as image retrieval, object recognition and robotic manipulation. To make the material classification more suitable for real-world applications, it is fundamental to satisfy two characteristics: robustness to scale and to pose variations. In this study, the authors propose a novel discriminant descriptor for texture classification based on a ne...

In this chapter we describe a unifying framework for local binary patterns and variants which we refer to as histograms of equivalent patterns (HEP). In presenting this concept we discuss some basic issues in texture analysis: the problem of defining what texture is; the problem of classifying the many existing texture descriptors; the concept of bag-of-features and the design choices that one ...

Texture description contributes as one of the most important low-level features in content-based image retrieval. In MPEG-7, homogeneous texture descriptor (HTD), texture browsing descriptor (TBD), and edge histogram descriptor (EHD) have been proposed as texture descriptors. However, no comprehensive evaluation and comparison of these three descriptors have been made. In this paper, we propose...

Computer-aided detection systems aim at the automatic detection of diseases using different medical imaging modalities. In this paper, a novel approach to detecting normality/pathology in digital chest radiographs is proposed. The problem tackled is complicated since it is not focused on particular diseases but anything that differs from what is considered as normality. First, the areas of inte...

Optical and Synthetic Aperture Radar (SAR) images are highly complementary, their registrations a fundamental task for other remote sensing applications. Traditional feature-matching algorithms fail to solve the significant nonlinear radiation difference (NRD) caused by different sensors. To address this problem, robust registration algorithm with multi-scale orientated map of phase congruency ...

In this paper, a Fuzzy Dominant Texture Descriptor is proposed for semantically describing an image. This fuzzy descriptor is defined over a set of fuzzy sets modelling the “coarseness” texture property. Concretely, fuzzy partitions on the domain of coarseness measures are proposed, where the number of linguistic labels and the parameters of the membership functions are calculated relating repr...

Texture remains largely underutilized in the analysis of remote sensed datasets compared to descriptors based on the orthogonal spectral dimension. This paper describes our recent efforts towards using texture to automate the annotation of remote sensed imagery Two applications are described that use the homogeneous texture descriptor recently standardized by MPEG-7. In the Jirst, higher-level ...

Since more than 50 years texture in image material is a topic of research. Hereby, color was ignored mostly. This study compares 70 different configurations for texture analysis, using four features. For the configurations we used: (i) a gray value texture descriptor: the co-occurrence matrix and a color texture descriptor: the color correlogram, (ii) six color spaces, and (iii) several quantiz...

This paper describes a visual shape descriptor based on the sectors and shape context of contour lines to represent the image local features used for image matching. The proposed descriptor consists of two-component feature vectors. First, the local region is separated into sectors and their gradient magnitude and orientation values are extracted; a feature vector is then constructed from these...