Edge detection has traditionally been associated with detecting physical space jump discontinuities in one dimension, e.g. seismic signals, and two dimensions, e.g. digital images. Hence most of the research on edge detection algorithms is restricted to these contexts. High dimension edge detection can be of significant importance, however. For instance, stochastic variants of classical differe...

In this paper we present a fast marker detection front end for Augmented Reality (AR) applications. The proposed algorithm is inspired by the ARTag system and designed to be robust against changing illumination conditions and occlusion of markers. In order to achieve this robustness we use an edge based approach. Edge pixels found by an edge detector are linked into lines by a RANSAC-grouper. T...

‎let $g$ be a graph and $chi^{prime}_{aa}(g)$ denotes the minimum number of colors required for an‎ ‎acyclic edge coloring of $g$ in which no two adjacent vertices are incident to edges colored with the same set of colors‎. ‎we prove a general bound for $chi^{prime}_{aa}(gsquare h)$ for any two graphs $g$ and $h$‎. ‎we also determine‎ ‎exact value of this parameter for the cartesian product of ...

The standard approach to image reconstruction is to stabilize the problem by including an edge-preserving roughness penalty in addition to faithfulness to the data. However, this methodology produces noisy object boundaries and creates a staircase effect. The existing attempts to favor the formation of smooth contour lines take the edge field explicitly into account; they either are computation...

When driving on lower-category Dutch rural roads without any delineation, drivers are likely to drift off the road with their right-side wheels, thus incurring damage to the pavement edge or even leading to accidents. In two experiments, two types of road-edge delineation, with continuous or dashed edge lines, were compared with two control roads without lines or with only a dashed line on the ...

This paper presents a closed edge detection method based on a level lines selection approach. The proposed method is based on an unsupervised probabilistic scheme using an a contrario method. A level line is considered meaningful if its contrast and length is unlikely to be due to chance. Besides being unsupervised, this method exploits a tree structure. The first step of the proposed approach ...

‎‎let $g=(v,e)$ be a simple graph‎. ‎an edge labeling $f:eto {0,1}$ induces a vertex labeling $f^+:vtoz_2$ defined by $f^+(v)equiv sumlimits_{uvin e} f(uv)pmod{2}$ for each $v in v$‎, ‎where $z_2={0,1}$ is the additive group of order 2‎. ‎for $iin{0,1}$‎, ‎let‎ ‎$e_f(i)=|f^{-1}(i)|$ and $v_f(i)=|(f^+)^{-1}(i)|$‎. ‎a labeling $f$ is called edge-friendly if‎ ‎$|e_f(1)-e_f(0)|le 1$‎. ‎$i_f(g)=v_f(...

This paper proposed a novel technique of edge detection in which ACO Edge detection is performed on fusion of Hue and PCA component. Edge detection is the vital step in numerous critical vision applications. Edge detection produces a black and white binary image where each object is distinguished by lines. Edges are the region in the image where sharp variations exist. Matlab tool is used for i...

Line or linear structure detection is a very basic, yet important problem in image processing and computer vision. Many line detection algorithms are based on edge detection and consider lines as extended or contiguous edges. Most techniques require that a binary edge map be first extracted from the image before line detection is performed. In this paper, we propose a new line detection techniq...