scholarly journals Efficient 3D stereo vision stabilization for multi-camera viewpoints

2019 ◽  
Vol 8 (3) ◽  
pp. 882-889
Author(s):  
Sharif Shah Newaj Bhuiyan ◽  
Othman O. Khalifa
Keyword(s):  
Stereo Vision ◽  
Linear Order ◽  
Spanning Tree ◽  
Detection Method ◽  
Corner Detection ◽  
Geometric Transformation ◽  
Image Stabilization ◽  
Tree Algorithm ◽  
Stabilization Process ◽  
Key Points

In this paper, an algorithm is developed in 3D Stereo vision to improve image stabilization process for multi-camera viewpoints. Finding accurate unique matching key-points using Harris Laplace corner detection method for different photometric changes and geometric transformation in images. Then improved the connectivity of correct matching pairs by minimizing the global error using spanning tree algorithm. Tree algorithm helps to stabilize randomly positioned camera viewpoints in linear order. The unique matching key-points will be calculated only once with our method. Then calculated planar transformation will be applied for real time video rendering. The proposed algorithm can process more than 200 camera viewpoints within two seconds.

scholarly journals Optimal feeder reconfiguration in distributed generation environment under time-varying loading condition

2021 ◽  
Vol 3 (6) ◽  
Author(s):  
Yanrenthung Odyuo ◽  
Dipu Sarkar ◽  
Lilika Sumi
Keyword(s):  
Graph Theory ◽  
Distributed Generation ◽  
Spanning Tree ◽  
Voltage Stability ◽  
Electrical Network ◽  
List Type ◽  
Network Reconfiguration ◽  
Time Varying ◽  
Electrical Networks ◽  
Tree Algorithm

Abstract The development and planning of optimal network reconfiguration strategies for electrical networks is greatly improved with proper application of graph theory techniques. This paper investigates the application of Kruskal's maximal spanning tree algorithm in finding the optimal radial networks for different loading scenarios from an interconnected meshed electrical network integrated with distributed generation (DG). The work is done with an objective to assess the prowess of Kruskal's algorithm to compute, obtain or derive an optimal radial network (optimal maximal spanning tree) that gives improved voltage stability and highest loss minimization from among all the possible radial networks obtainable from the DG-integrated mesh network for different time-varying loading scenarios. The proposed technique has been demonstrated on a multiple test systems considering time-varying load levels to investigate the performance and effectiveness of the suggested method. For interconnected electrical networks with the presence of distributed generation, it was found that application of Kruskal's algorithm quickly computes optimal radial configurations that gives the least amount of power losses and better voltage stability even under varying load conditions. Article Highlights Investigated network reconfiguration strategies for electrical networks with the presence of Distributed Generation for time-varying loading conditions. Investigated the application of graph theory techniques in electrical networks for developing and planning reconfiguration strategies. Applied Kruskal’s maximal spanning tree algorithm to obtain the optimal radial electrical networks for different loading scenarios from DG-integrated meshed electrical network.

scholarly journals A peduncle detection method of tomato for autonomous harvesting

2021 ◽  
Author(s):  
Jiacheng Rong ◽  
Guanglin Dai ◽  
Pengbo Wang
Keyword(s):  
Pose Estimation ◽  
Pitch Angle ◽  
Detection Method ◽  
Geometric Model ◽  
Average Error ◽  
Long Distance ◽  
End Effector ◽  
Key Points ◽  
Yaw Angle ◽  
Cutting Point

AbstractFor automating the harvesting of bunches of tomatoes in a greenhouse, the end-effector needs to reach the exact cutting point and adaptively adjust the pose of peduncles. In this paper, a method is proposed for peduncle cutting point localization and pose estimation. Images captured in real time at a fixed long-distance are detected using the YOLOv4-Tiny detector with a precision of 92.7% and a detection speed of 0.0091 s per frame, then the YOLACT +  + Network with mAP of 73.1 and a time speed of 0.109 s per frame is used to segment the close-up distance. The segmented peduncle mask is fitted to the curve using least squares and three key points on the curve are found. Finally, a geometric model is established to estimate the pose of the peduncle with an average error of 4.98° in yaw angle and 4.75° in pitch angle over the 30 sets of tests.

scholarly journals STEREO VISION METHOD APPLICATION TO ROAD INSPECTION

2017 ◽  
Vol 12 (1) ◽  
pp. 38-47 ◽  
Author(s):  
Marcin Staniek
Keyword(s):  
Stereo Vision ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Corner Detection ◽  
Stereo Images ◽  
Processing Technologies ◽  
The Road ◽  
Road Pavement ◽  
Road Inspection ◽  
Set Of Points

The paper presents the stereo vision method for the mapping of road pavement. The mapped road is a set of points in three-dimensional space. The proposed method of measurement and its implementation make it possible to generate a precise mapping of a road surface with a resolution of 1 mm in transverse, longitudinal and vertical dimensions. Such accurate mapping of the road is the effect of application of stereo images based on image processing technologies. The use of matching measure CoVar, at the stage of images matching, help eliminate corner detection and filter stereo images, maintaining the effectiveness of the algorithm mapping. The proper analysis of image-based data and application of mathematical transformations enable to determine many types of distresses such as potholes, patches, bleedings, cracks, ruts and roughness. The paper also aims at comparing the results of proposed solution and reference test-bench. The statistical analysis of the differences permits the judgment of error types.

Multi-feature SUSAN corner detection method

2005 ◽  
Author(s):  
Xun Wang ◽  
Jianqiu Jin ◽  
Yun Ling ◽  
Zhaoyi Jiang
Keyword(s):  
Detection Method ◽  
Corner Detection
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