Machine Vision (TSAR0520)

Machine Vision, 5 cr - TSAR0520

Machine Vision (TSAR0520-3003), 09.01.2023 – 30.04.2023,
5 cr (TSA20SA, ...) — Face-to-face + -
Language of instruction

Finnish

Timing

09.01.2023 - 30.04.2023

Lecturer(s)

Samppa Alanen, Juho Riekkinen

Campus

Main Campus

Enrollment

01.11.2022 - 05.01.2023
Groups
- TSA20SA
- TSA20SB
Degree Programme

Bachelor's Degree Programme in Electrical and Automation Engineering

Mode of delivery

Face-to-face

Unit

School of Technology
Machine Vision (TSAR0520-3004), 07.03.2023 – 29.02.2024,
5 cr (ZJAJ23KLIKEROK) — Online learning + -
Language of instruction

Finnish

Timing

07.03.2023 - 29.02.2024

Lecturer(s)

Juho Riekkinen

Campus

Main Campus
Groups
- ZJAJ23KLIKEROK
Degree Programme

Bachelor's Degree Programme in Electrical and Automation Engineering

Mode of delivery

Online learning

Share of virtual studies

5 cr

Unit

School of Technology

Main objectives for this course are acquiring knowledge and getting familiar with different types of machine vision systems and solutions (including robotics applications). Studying in this course require fundamentals in field of technology and programming skills. This course enables further studies of the subject in other courses.

EUR-ACE ENGINEERING PRACTICE
Student is familiar and able to use image acquisition, image pre-processing and image analysis functions in machine vision systems with grayscale and color cameras. Student is familiar with hardware component properties (cameras, image processing components, light sources, optics, connections) in machine vision. Student understands functionalities, limits and opportunities in machine vision systems. Student is able to design machine vision system and program machine vision application and algorithms according to end-user requirements. Student is able to design the installation of the machine vision system according to end-user needs (designing optical geometry, choosing camera and lightning options, implementing interface to automation system, designing environmental protection).

Camera and lightning technologies
Optics
Image acquisition
Image analysis
Designing machine vision system
Programming machine vision application and applying machine vision algorithms
Interfaces for external systems

Fundamentals in field of technology, programming skills

0-5

Sufficient (1): Students is partly able to design machine vision system and take into account the requirements of the application. Students is able to design and implement hardware, software and installations for machine vision applications but the design and implementation is significantly incomplete.

Satisfactory (2): Student is mainly able to design machine vision system and take into account the requirements of the application. Students is able to design and implement hardware, software and installations for machine vision applications but the design and/or implementation is incomplete.

Good (3): Student is able to solve machine vision system design and installation issues according to the requirements of the application. Students is able to design and implement machine vision applications in a functional way including component selection, software and installations. Despite functional implementation, selections and/or implementation are not optimal.

Very good (4): Student is able to manage the design and installation challenges of a machine vision system according to the requirements of the application. Students is able to design and implement machine vision applications in a very good way including component selection, software and installations but there are small selection or implementation differences in the solutions compared to the optimal.

Excellent (5): Student is able to master the design and installation of a machine vision system according to the requirements of the application. Student is able to design and implement challenging machine vision applications in an optimal way including component selection, software and installations.

Machine Vision, 5 cr - TSAR0520

Upcoming implementations