MACHINE VISION FOR THREE-DIMENSIONAL MODELLING OF GERBERA JAMESONII FOR AUTOMATED ROBOTIC HARVESTING

2005 ◽  
pp. 757-764 ◽  
Author(s):  
M. Kawollek ◽  
T. Rath
Keyword(s):  
Machine Vision ◽  
Three Dimensional ◽  
Gerbera Jamesonii ◽  
Robotic Harvesting

scholarly journals 3-D Point Cloud Registration Algorithm Based on Greedy Projection Triangulation

2018 ◽  
Vol 8 (10) ◽  
pp. 1776 ◽  
Author(s):  
Jian Liu ◽  
Di Bai ◽  
Li Chen
Keyword(s):  
Machine Vision ◽  
Point Cloud ◽  
Three Dimensional ◽  
Target Object ◽  
Initial Alignment ◽  
Registration Accuracy ◽  
Point Cloud Registration ◽  
Registration Algorithm ◽  
Feature Information ◽  
Complex Target

To address the registration problem in current machine vision, a new three-dimensional (3-D) point cloud registration algorithm that combines fast point feature histograms (FPFH) and greedy projection triangulation is proposed. First, the feature information is comprehensively described using FPFH feature description and the local correlation of the feature information is established using greedy projection triangulation. Thereafter, the sample consensus initial alignment method is applied for initial transformation to implement initial registration. By adjusting the initial attitude between the two cloud points, the improved initial registration values can be obtained. Finally, the iterative closest point method is used to obtain a precise conversion relationship; thus, accurate registration is completed. Specific registration experiments on simple target objects and complex target objects have been performed. The registration speed increased by 1.1% and the registration accuracy increased by 27.3% to 50% in the experiment on target object. The experimental results show that the accuracy and speed of registration have been improved and the efficient registration of the target object has successfully been performed using the greedy projection triangulation, which significantly improves the efficiency of matching feature points in machine vision.

scholarly journals Machine Vision Algorithm of Eggplant Recognition for Robotic Harvesting.

2000 ◽  
Vol 12 (1) ◽  
pp. 38-46 ◽  
Author(s):  
Shigehiko HAYASHI ◽  
Katsunobu GANNO ◽  
Yukitsugu ISHII
Keyword(s):  
Machine Vision ◽  
Vision Algorithm ◽  
Robotic Harvesting

Visual interpretation of known objects in constrained scenes

1992 ◽  
Vol 337 (1281) ◽  
pp. 361-370 ◽  
Keyword(s):  
Object Recognition ◽  
Visual Perception ◽  
Machine Vision ◽  
Recent Work ◽  
Three Dimensional ◽  
Neural Mechanisms ◽  
Visual Interpretation ◽  
Natural Vision ◽  
Analogue Models ◽  
Dynamic Filters

Recent work on the visual interpretation of traffic scenes is described which relies heavily on a priori knowledge of the scene and position of the cam era, and expectations about the shapes of vehicles and their likely movements in the scene. Knowledge is represented in the computer as explicit three-dimensional geometrical models, dynamic filters, and descriptions of behaviour. Model-based vision, based on reasoning with analogue models, avoids many of the classical problems in visual perception: recognition is robust against changes in the image of shape, size, colour and illumination. The three-dimensional understanding of the scene which results also deals naturally with occlusion, and allows the behaviour of vehicles to be interpreted. The experiments with machine vision raise questions about the part played by perceptual context for object recognition in natural vision, and the neural mechanisms which might serve such a role.

scholarly journals How to make sense of 3D representations for plant phenotyping: a compendium of processing and analysis techniques

2018 ◽  
Author(s):  
Breght Vandenberghe ◽  
Stephen Depuydt ◽  
Arnout Van Messem
Keyword(s):  
Machine Vision ◽  
Large Scale ◽  
Three Dimensional ◽  
Plant Phenotyping ◽  
Small Scale ◽  
Dimensional Approach ◽  
Crop Monitoring ◽  
Analysis Techniques ◽  
Further Development ◽  
3D Representations

Machine vision technology is moving more and more towards a three-dimensional approach, and plant phenotyping is following this trend. However, despite its potential, the complexity of the analysis of 3D representations has been the main bottleneck hindering the wider deployment of 3D plant phenotyping. In this review we provide an overview of typical steps for the processing and analysis of 3D representations of plants, to offer potential users of 3D phenotyping a first gateway into its application, and to stimulate its further development. We focus on plant phenotyping applications where the goal is to measure characteristics of single plants or crop canopies on a small scale in research settings, as opposed to large scale crop monitoring in the field.

scholarly journals TOWARDS MACHINE VISION BASED RAILWAY ASSETS PREDICTIVE MAINTENANCE

2020 ◽  
Vol 19 (2) ◽  
pp. 125
Author(s):  
Ivan Ćirić ◽  
Milan Banić ◽  
Miloš Simonović ◽  
Aleksandar Miltenović ◽  
Dušan Stamenković ◽  
...  
Keyword(s):  
Machine Vision ◽  
High Speed ◽  
Rolling Contact Fatigue ◽  
Three Dimensional ◽  
Contact Fatigue ◽  
Operational Reliability ◽  
Rolling Contact ◽  
Camera System ◽  
Novel Technologies ◽  
Three Dimensional Coordinate

The main goal of this paper is to present novel technologies that can contribute to safety, competitiveness, efficiency and operational reliability of Railway infrastructure through the development of innovative solutions for measuring and monitoring of railway assets based on machine vision. Measuring the transversal position of the wheels on the rail, as well as identification of the defects of the wheel and the rail (such as deformation of rail head edge, lateral wear, worn wheels, cracks in wheel and rail, rolling contact fatigue, corrugation and other irregularities) can increase reliability and lower maintenance costs. Currently, there is a need on the market for the innovative solution, namely the on-board high-speed stereo camera system augmented with a system that projects custom pattern (fringe scanner system) for measuring the transversal position of the wheels on the rail, robust to environmental conditions and waste along the track that can provide reliable measurements of transversal position of the wheels up to 200 km/h. New trends in Precise Industrial 3D Metrology are showing that stereo vision is an absolute must have in modern specialized optical precision measuring systems for the three-dimensional coordinate measurement.

REAL-TIME MACHINE VISION SYSTEMS

1987 ◽  
Vol 41 (2) ◽  
pp. 173-180
Author(s):  
Kam W. Wong
Keyword(s):  
Solid State ◽  
Machine Vision ◽  
Real Time ◽  
Three Dimensional ◽  
The United States ◽  
Image Correlation ◽  
Software Systems ◽  
Vision Systems ◽  
Camera Systems ◽  
Recent Developments

Recent developments in machine vision systems, solid state cameras, and image processing are reviewed. Both hardware and software systems are currently available for performing real-time recognition and geometric measurements. More than 1000 units of these imaging systems are already being used in manufacturing plants in the United States. Current research efforts are focused on the processing of three-dimensional information and on knowledge-based processing systems. Five potential research topics in the area of photogrammetry are proposed: 1) stereo solid state camera systems, 2) image correlation, 3) self-calibration and self-orientation, 4) general algorithm for multistation and multicamera photography, and 5) artificial photogrammetry.

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