Descriptor systems which are also referred to as singular systems are described by differential equations and algebraic equations [1]. It has been widely applied in the areas of power systems, economic systems, biological systems, constrained robots, electronic networking, aerospace, chemical process and astronomy (solar activity)[1-4]. Stability of descriptor systems is a basic and important p...

Object recognition has become one of the most active research topics in computer vision in recent years. The set of features extracted from the training image is critical for good object recognition performance. The Scale Invariant Feature Transform (SIFT) was proposed by David Lowe in 1999; the SIFT features are local and effective for object recognition. In this paper we conducted a survey of...

Tensor scale is a morphometric parameter that unifies the representation of local structure thickness, orientation, and anisotropy, which can be used in several computer vision and image processing tasks. In this article, we exploit this concept for binary images and propose a shape salience detector and a shape descriptor – Tensor Scale Descriptor with Influence Zones. It also introduces a rob...

In this paper, we propose a novel 3D free form surface matching method based on a novel key-point detector and a novel feature descriptor. The proposed detector is based on algebraic surface fitting. By global smooth fitting, our detector achieved high computational efficiency and robustness against non-rigid deformations. For the feature descriptor, we provide algorithms to compute 3D critical...

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...

In this paper, we propose a novel local image descriptor DoP which is termed as the difference of images represented by polynomials in different degrees. Once an interest point/region is extracted by a common image detector such as Harris corner, our DoP descriptor is able to characterize the interest point/region with high distinctiveness, compactness, and robustness to viewpoint change, image...

In this article, we develop a novel method for the detection of vineyard parcels in agricultural landscapes based on very high resolution (VHR) optical remote sensing images. Our objective is to perform texture-based image retrieval and supervised classification algorithms. To do that, the local textural and structural features inside each image are taken into account to measure its similarity ...

In this paper we apply the Local Binary Pattern on Three Orthogonal Planes (LBP-TOP) descriptor to the field of human action recognition. A video sequence is described as a collection of spatial-temporal words after the detection of space-time interest points and the description of the area around them. Our contribution has been in the description part, showing LBP-TOP to be a promising descrip...

Histogram of orientated gradient (HOG) is widely used as a local feature descriptor in bag of features (BOF) method, whereas, few studies are conducted to discover the relationship between them. In this paper, we exploit this relationship and reveal that the construction method of descriptor in blocks in HOG can be treated as a variant of BOF method. Based on this interpretation, we propose a n...

In this paper, we propose Local Binary Pattern Histogram Fourier features (LBP-HF), a novel rotation invariant image descriptor computed from discrete Fourier transforms of local binary pattern (LBP) histograms. Unlike most other histogram based invariant texture descriptors which normalize rotation locally, the proposed invariants are constructed globally for the whole region to be described. ...