Geometrical Coding Research Articles

Impact of Power Spectrum in Geometrical Coding on the Scattering of Random Electromagnetic Coding Metasurface

Impact of Power Spectrum in Geometrical Coding on the Scattering of Random Electromagnetic Coding Metasurface

Territorial blueprint in the hippocampal system.

As we skillfully navigate through familiar places, neural computations of distances and coordinates escape our attention. However, we perceive clearly the division of space into socially meaningful territories. 'My space' versus 'your space' is a distinction familiar to all of us. Spatial frontiers are social in nature since they regulate individuals' access to utilities in space depending on hierarchy and affiliation. How does the brain integrate spatial geometry with social territory? We propose that the action of oxytocin (OT) in the entorhinal-hippocampal regions supports this process. Grounded on the functional role of the hypothalamic neuropeptide in the hippocampal system, we show how OT-induced plasticity may bias the geometrical coding of place and grid cells to represent social territories.

Implementation of the Fast Algorithm for Geometrical Coding of Digital Images with the Use of CUDA Architecture

In this paper we compare the speed and quality of CUDA implementation for a new edge detection algorithm based on geometrical coding with the CUDA implementation of Canny algorithm commonly used in OpenCV library. The comparison shows that the new approach can really compete with the Canny operator and in some cases even overcomes it in speed and quality. Examples of geometrical coding edge detection in different situations are presented.

Fast algorithm for geometrical coding of digital images

A fast algorithm for geometrical coding is presented in the paper. It allows one to perform the image analysis by methods of differential geometry rather than widespread methods based on gradient and Hessian calculations. Nowadays, one of the most important aspects in image analysis is the speed of computations. The algorithm for geometrical coding is comparable or faster than traditional algorithms of image analysis and in many cases it gives better results. Several examples of algorithm working results for contour detection are presented.

Normalized Scale Coding for Geometrical Coding in Image Retrieval System

Pattern recognition has emerged as an effective measure for automated system. I n such an approach the coding is carried out over a set of images and result are retrieved based on the best match approach. Where image features are taken as the representative feature for image coding, the introduced artifacts are the major effects at the coding level. In this work a shape oriented coding based on curvature coding and its representation based on Normalized information is proposed. The coding reveals the lower spectral information of the image contour and considers it as feature information which improves the recognition approach.