MEI-56606 Machine Vision, 5 cr
Additional information
This course will focus on industrial applications of Machine Vision, and especially from production automation point-of-view.
Course will include large amounts of independent studies in the form of reading texts (book chapters, articles, etc.), performing tasks on-line in Moodle, writing essays, etc. In addition, course will include hands-on work in laboratory.
Person responsible
Jussi Halme, Minna Lanz
Lessons
| Implementation | Period | Person responsible | Requirements |
| MEI-56606 2016-01 | 3 - 4 |
Jussi Halme Minna Lanz |
Completed and accepted assignments, essays and exercises about topics discussed during the lectures. Course has no exam. |
Learning Outcomes
After completing the course student has know-how about industrial machine vision at the level that he/she can analyse simple applications from machine vision point-of-view, select suitable machine vision hardware components for the application, and program the machine vision equipment. Student can also analyse how reliable the measurement/inspection results are and identify error sources.
Content
| Content | Core content | Complementary knowledge | Specialist knowledge |
| 1. | Machine vision in production automation: Typical applications. Typical system structures. Commonly used 3D imaging methods. | ||
| 2. | Machine vision hardware: * Different system types (PC based system, smart camera based system) * Camera types and selection principles: Specifying camera resolution (field-of-view, spatial resolution) and resulting expected measurement resolution. * Lenses and other optical components: Specifying lens focal length. * Illumination in machine vision: Importance of illumination concerning the resulting image. Illumination methods and light sources. | Typical color camera vs. grey-scale camera. Shutter types. Concepts of depth-of-focus/depth-of-field and optical resolution. Effect of different light colors. | |
| 3. | Machine vision software and image processing: Digital image. Typical functionality and special properties of machine vision software. Common programming concepts and methods in machine vision. | Understanding basic operating principles of the most commonly used machine vision software algorithms. Programming simple machine vision application. | |
| 4. | Typical machine vision applications/tasks in production automation: Checking the presence/counting parts - methods Locating parts for robot pickup - robot and machine vision calibration Dimensional measurements - measurement accuracy and/or uncertainty | Communicating with other equipment. Calibrating machine vision system and combining camera and robot coordinates. Calculating measurement uncertainty. |
Study material
| Type | Name | Author | ISBN | URL | Additional information | Examination material |
| Book | Machine Vision Handbook | Bruce G. Batchelor | ISBN: 978-1-84996-168-4 (Print | TUT has one paper copy at library (only short term loans) and license to eBook, see link. | No | |
| Lecture slides | Lecture materials etc. | Lecturer(s) | Lecture slides, exercise problems, assignment instructions, etc. | No |
Additional information about prerequisites
This course has no formal prerequisites, but since this is a Master's level course, we expect that students have some previous knowledge about production automation. Elementary know-how on programming will help completing course tasks, but is not strictly required.
Correspondence of content
There is no equivalence with any other courses