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Machine vision (4 cr)

Code: KL25KONÄKÖ4-3010

General information


Enrollment
16.04.2022 - 28.10.2022
Registration for the implementation has ended.
Timing
24.10.2022 - 18.12.2022
Implementation has ended.
Number of ECTS credits allocated
4 cr
Local portion
4 cr
Mode of delivery
Contact learning
Unit
SeAMK Automation Engineering and Information Technology
Campus
SeAMK Seinäjoki, Frami
Teaching languages
Finnish
Seats
0 - 30
Degree programmes
Bachelor of Engineering, Automation Engineering
Teachers
Toni Luomanmäki
Course
KL25KONÄKÖ4

Evaluation scale

1-5

Content scheduling

- Fundamental principles of the machine vision
- Applications of the machine vision
- Typical components of the machine vision system
- Basic functions of the Cognex InSight EasyBuilder machine vision software.
- Laboratory exercises

Objective

After completing the course the student will;
- Know the different machine vision technologies and knows where they are usually applied in industry
- Know the key components and their functions in the machine vision system
- Be able to use a machine vision software to create basic level image analysis and extract features from the image

Content

The basic principles of the machine vision, applications of the machine vision, typical components of the machine vision system, machine vision software, defining a machine vision system. The basic functions of the Cognex In-Sight EasyBuilder machine vision software. Basics of the machine vision laboratory equipment.

Materials

Lecture handouts, machine vision related manuals, articles, videos

Teaching methods

Lectures, interactive assignments, software exercices, laboratory assignments

Student workload

Total work load of the course: 100 h (scheduled lectures 40 h, independent work 60 h)

Assessment criteria, satisfactory (1)

The student knows the basics of the course contents.The student knows the principle of machine vision and knows where it can be applied.

Assessment criteria, good (3)

The student knows well the course contents.The student knows the principle of machine vision and knows where it can be applied. The student is able to use programs related to machine vision.

Assessment criteria, excellent (5)

The student knows excellent the course contents.The student knows the principle of machine vision and knows where it can be applied. The student is able to use programs related to machine vision. The student is able to design and implement vision-based applications that implement separation of parts and materials or quality control.

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