Combining Turning Point Detection with Grid Transformation for Road Intersection Detection

2021 ◽  
pp. 335-347
Author(s):  
Rutian Qing ◽  
Yizhi Liu ◽  
Yijiang Zhao ◽  
Zhihou Guo ◽  
Zhuhua Liao ◽  
...  
Keyword(s):  
Turning Point ◽  
Intersection Detection ◽  
Point Detection

scholarly journals Combining turning point detection and Dijkstra’s algorithm to search the shortest path

2017 ◽  
Vol 9 (2) ◽  
pp. 168781401668335 ◽  
Author(s):  
Ter-Feng Wu ◽  
Pu-Sheng Tsai ◽  
Nien-Tsu Hu ◽  
Jen-Yang Chen
Keyword(s):  
Image Processing ◽  
Path Planning ◽  
Obstacle Avoidance ◽  
Shortest Path ◽  
Turning Point ◽  
Dijkstra’S Algorithm ◽  
Edge Point ◽  
Dijkstra's Algorithm ◽  
Before And After ◽  
Point Detection

In this study, image processing was combined with path-planning object-avoidance technology to determine the shortest path to the destination. The content of this article comprises two parts: in the first part, image processing was used to establish a model of obstacle distribution in the environment, and boundary sequence permutation method was used to conduct orderly arrangement of edge point coordinates of all objects, to determine linking relationship between each edge point, and to individually classify objects in the image. Then, turning point detection method was used to compare the angle size between vectors before and after each edge point and to determine vertex coordinates of polygonal obstacles. In the second part, a modified Dijkstra’s algorithm was used to turn vertices of convex-shaped obstacles into network nodes, to determine the shortest path by a cost function, and to find an obstacle avoidance path connecting the start and end points. In order to verify the feasibility of the proposed architecture, an obstacle avoidance path simulation was made by the graphical user interface of the programming language MATLAB. The results show that the proposed method in path planning not only is feasible but can also obtain good results.

scholarly journals RETINA FUNDUS IMAGE MASK GENERATION USING PSEUDO PARAMETRIC MODELING TECHNIQUE

2010 ◽  
Vol 11 (2) ◽  
pp. 163-177 ◽  
Author(s):  
Abiodun Musa Aibinu ◽  
M.J.E. SALAMI ◽  
A.A. SHAFIE
Keyword(s):  
Diabetic Retinopathy ◽  
Hybrid Approach ◽  
Parametric Modeling ◽  
Good Tool ◽  
Cross Point ◽  
Intersection Detection ◽  
Artificial Neural Network Ann ◽  
Point Detection ◽  
Very High ◽  
Image Mask

The use of vascular intersection as one of the symptomsfor monitoring and diagnosis of diabetic retinopathy fromfundus images have been widely reported in literatures. Inthis work, a new hybrid approach that makes use of threedifferent methods of vascular intersection detection namelyModified cross-point number (MCN), Combine Cross Points(CNN) and Artificial Neural Network (ANN) is hereby proposed.Result obtained from the application of this techniqueto both simulated and experimental shows a very high accuracyand precision value in detecting both bifurcation andcross over points. Thus an improvement in bifurcation andvascular point detection and a good tool in the monitoringand diagnosis of diabetic retinopathy.

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