In shadow detection area, deep learning-based methods have achieved outstanding performance. However, the potential ambiguity in images is still main reason for poor performance of algorithms. By analysing relationships among edges, false-positive information, and areas, an edge-guided disambiguation module better proposed. The consists two parts: 1) edge feature used to guide comprehensive are...

The iterative back-projection (IBP) algorithm for single image super-resolution (SR) can not guarantee the edge smoothness because the reconstruction error is back-projected isotropically. Furthermore, in the case that there is only one low-resolution input, the estimation of the reconstruction error is easily affected by noise. Thus, this algorithm is highly sensitive to noise. The focus of th...

in this paper, shortest path design problem (spdp) in which the path is incident to all cells is considered. the bi-directional path is one of the known types of configuration of networks for automated guided vehi-cles (agv).to solve this problem, two algorithms are developed. for each algorithm an integer linear pro-gramming (ilp) is determined. the objective functions of both algorithms are t...

Correlation trackers are in use for the past four decades. Edge based correlation tracking algorithms have proved their strength for long term tracking, but these algorithms suffer from two major problems: clutter and slow occlusion. Thus, there is a requirement to improve the confidence measure regarding target and non-target object. In order to solve these problems, we present an “Edge Enhanc...

In the paper, we present an approach of multi-resolution analysis to extract road information from high resolution imagery. Firstly, high resolution imagery is divided into a series of different resolution images. According to the representation characteristics of roads at different resolution, we analyze roads’ geometrical, radiometric, and topological attributes and carry out a variety of pro...

In this paper, we employ the new geometric active contour models formulated in [20, 21] for edge detection and segmentation of MRI and ultrasound medical imagery. Our method is based on de ning feature-based metrics on a given image which in turn leads to a novel snake paradigm in which the feature of interest may be considered to lie at the bottom of a potential well. Thus the snake is attract...

In earlier work [9, 10], we developed an approach to edge labelling and depth reconstruction based on fusion of registered depth and intensity images. This paper presents a new method and extensions to the first stage of that approach, that is the detection and semantic labelling of the edge data. Reflectance edges are extracted from an intensity image, and quadratic curves are fitted to range ...