This paper presents a method called Robust Edge Aware Descriptor (READ) to compute local gradient information. The proposed method measures the similarity of the underlying structure to an edge using the 1D Fourier transform on a set of points located on a circle around a pixel. It is shown that the magnitude and the phase of READ can well represent the magnitude and orientation of the local gr...

In this paper, we propose a novel local feature descriptor, Local Gaussian Structural Pattern (LGSP), for face recognition that encodes the directional information of the face’s textures (i.e., the texture’s structure), producing a more discriminant code than other state-of-the-art methods. Each micro-pattern’s structure is computed by using a derivative-Gaussian compass mask, which is more rob...

In this work, we present the novel Inter-GIP Distances (IGD) feature and its integration into the Gestalt Interest Points (GIP) image descriptor. With the ongoing growth of visual data, efficient image descriptor methods are becoming more and more important. Several local point-based description methods have been defined in the past decades. Accuracy and descriptor size are important factors wh...

Fourier Coefficients have long been used to achieve invariance to signal transformations. In this paper we propose a Global Rotation Invariant Descriptor (GRID) for matching images based on the Discrete Fourier Transform (DFT). Following the analysis of the sampling criteria for generating such descriptors, it is shown that the descriptor can be made invariant to changes in scale as well under ...