Machine Vision
Machine vision (MV) is the process of applying a range of technologies to provide imaging-based automatic inspection, process control and robot guidance in industrial applications.
Machine Vision Research and Development Projects
Below you find some information about some of my ongoung Machine Vision Research and Development Projects.
Real-Time Monitoring of Microplastic in the Water
Microplastic refers to any type of tiny, solid plastic particle or fiber found as litter in oceans and other waterways. Microplastic most often starts as larger pieces of plastic, such as plastic packaging, cigarette filters, car tires, or synthetic fabric that breaks down into tiny pieces over time. These particles and fibers measure 5 millimeters in diameter or less and do not dissolve in water.
The aim is to create a prototype for Real-Time Monitoring of Microplastic in the water. This includes monitoring using a camera, analyzing and storing data in the cloud. Machine Vision and Machine Learning for detection of Microplastic in the images from the camera.
Include system for logging and monitoring of Microplastic in the water.
Below we see the prototype for the Image Analyzer Application used in the Microplastic project.
Machine Vision Platform for Pool Games
In this research and development project we will implement a prototype of a Cloud-based pool table computer vision competition system with focus on IoT, Web Technology, Machine Learning (ML), Cyber Security, Smart Sensors and Vision Technology.
Publications
Below you find some of my publication within the field Machine Vision Systems and Robotics.
Scientific Articles
- Sandboxing for Cross-Platform Applications of Robots - Hans-Petter Halvorsen, Alexander Jonsaas, Saba Mylvaganam - 2019 IEEE International Symposium on RObotic and Sensors Environments (ROSE), June 17-18, 2019, Ontario, Canada. ISBN 978-1-7281-1964-9. Available from IEEE Xplore.
- Fusion of Body Sensors’ Data and Video Images in Assistive Technology - Hans-Petter Halvorsen, Karina Kaspersen, Alexander Jonsaas, Saba Mylvaganam - IEEE Sensors Applications Symposium (SAS), March 11-13, 2019, Sophia Antipolis, France. ISBN 978-1-5386-7713-1. Available from IEEE Xplore.
- Remote control of a robotic arm - A cross-platform study using LabVIEW and DeltaV - Hans-Petter Halvorsen, Alexander Jonsaas, Lilly Eikehaug, Sondre Mogård, Håkon Viumdal, Rune Andersen, Saba Mylvaganam. ITEN2015 Conference, Łódź, Poland, September 2015.