Halcon Archives - Robotics Academy

Precise measurement using machine vision

The Robotics Academy was commissioned to investigate further the potential of machine vision for Neorem Magnets’ needs. Atte Ali-Hokka and Juha Aalto were involved in the project in the Robotics Academy team. The project was directed by Joonas Kortelainen. The task of the team was to investigate the possibility to measure the object delivered by the company with a machine vision camera in the Satakunta University of Applied Sciences’ RoboAI collaborative laboratory.

The customer wanted to study the technical dimensions and quality of the object as accurately and reliably as possible. The project used an IDS camera that captures the subject in very high resolution. The team implemented the program in Halcon development environment that meets the customer’s requirements. The group had no previous experience with machine vision, but the Academy students were happy to take up the challenge.

The client was particularly interested in exploring the possibilities of measuring and examining the area of the object and its formal correctness compared to the technical drawings provided by the company. The students had no previous experience in creating such a program so students went on to study the measurement of the object by creating a program that can measure the length, angles of sides and perimeter of the object.

As the team learned about the new object an image was created in the real world coordinate system allowing the size of the object to be measured in millimeters. This development step opened the doors for the working group to a whole new way of measuring, as it was now possible to compare the image to the technical drawings provided by the customer to the working group.

Summary:

The customer seemed satisfied with the results achieved by the working group. The students and the client felt that both parties had benefited from the project. For students, this benefit is reflected in the amount of learning that students gained from working on the project with a great deal of machine vision, as well as camera, lighting, and programming techniques. The Robotics Academy would like to thank Neorem Magnets for taking the opportunity to explore their expertise and provide an interesting project.

Machine vision as an industrial tool

Our client, Boliden Harjavalta’s main products are copper, nickel, gold and silver. Boliden’s nickel smelter is the only one in Western Europe. Boliden produces high quality nickel matte using the latest technology in the industry.

The Robotics Academy students were commissioned to explore the possibilities of using machine vision in the Boliden process. Boliden was interested in the concentration of various components of the slag after the smelting process and hoped to use machine vision to simplify and speed up the process.

A machine vision system is one where computer imaging is used for industrial purposes. The system consists of a light source, an object to be photographed, a camera, a computer, and an image processing program that interprets the image automatically. Machine vision systems perform precisely pre-programmed tasks and are primarily used when optical inspection should be fast, accurate, round the clock and consistently repeatable. Machine vision can be used to perform tasks that are impossible for human vision by using wavelengths that cannot be detected by the human eye. In this assignment, a conveyor belt cared slag under the system to identify the customer-defined concentrations.

When using a smart camera, all image processing and counting is done in the camera itself. We chose to use Cognex’s In-Sight application, but the slowness of this camera was a disadvantage because the items had to be pictured on a fast conveyor belt. Due to scheduling concerns, Robotics Academy students were not able to continue their research further, however, it is possible to continue the project with another software and a different camera solution in the future. We recommend considering Halco software, which could handle all intellectual observation and computing, as well as speed up image processing.

Summary

In our project, we learned how to take advantage of different camera and light options. The overall benefits were mutual. The students’ gained knowledge and were able to give the customer the information they sought. With the help of additional instruction, we can better utilize machine vision in future projects.