Courses persons responsible
Jani Uusitalo

Lecturers
Timo Prusi
Jani Uusitalo

Implementations

	Period 1	Period 2	Period 3	Period 4	Period 5	Summer
Lecture	-	-	-	4 h/week	-	-
Exercise	-	-	-	1 h/week	-	-
Exercise work	-	-	-	1 h/week	2 h/week	-
Exam

(Timetable for academic year 2006-2007)

Objectives
Basic knowledge and readiness for applying and using machine vision in different discrete parts production applications.

Content

Content	Core content	Complementary knowledge	Specialist knowledge
1.	Properties and selection principles between different camera types. Measurement accuracy and resolution selection, dynamic properties of detectors.
2.	Properties and selection principles between different vision systems. Special properties of vision software.
3.	Light source types, lighting methods. Selection of optics and imaging geometry.
4.	Image analysis basics: digital image, filtering, connection analysis, morphology, convolution, segmentation, (spatial) features, 2D-recognition and position measurement.
5.	Principles and basics of programming vision systems.

Requirements for completing the course
Written examination based on lectures and exercises and accepted laboratory assignments.

Evaluation criteria for the course

Study material

Type	Name	Auhor	ISBN	URL	Edition, availability...	Exam material	Language
Lecture slides		Jani Uusitalo				Yes	English
Summary of lectures	Machine Vision in Production Automation	Jani Uusitalo				No	English

Prerequisites
Prequisite relations (Sign up to TUT Intranet required)

Distance learning

- In information distribution via homepage, newsgroups or mailing lists, e.g. current issues, timetables
- In compiling teaching material, particularly for online use or other electronic media
- In compiling exercise, group or laboratory work
- In distributing and/or returning exercise work, material etc
- In the visualization of objects and phenomena, e.g. animations, demonstrations, simulations, video clips
- In interaction and discussion, such as online discussions, chat
- The course utilizes a learning platform, which? Moodle

- Contact teaching: 80 %
- Distance learning: 0 %
- Proportion of a student's independent study: 20 %

Scaling

Methods of instruction	Hours
Lectures	72
Exercises	12
Laboratory assignments	32
Information and communication technology	2
Other contact teaching	1
Learning diary, portfolio and other written work	4

Other scaled	Hours
Preparation for exam	8
Exam/midterm exam	3
Total sum	134

Correspondence of content
2702800 Machine Vision in Production Engineering

Course homepage

Last modified	21.12.2006
Modified by	Jani Uusitalo