Course Catalog 2006-2007

TTE-5216 MACHINE VISION IN PRODUCTION AUTOMATION, 5 cr
Machine Vision in Production Automation

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

  • Used assessment scale is numeric (1-5)

  • 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

  • ITC utilized during the course

  • - 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

  • Estimate as a percentage of the implementation of the course
  • - Contact teaching: 80 %
    - Distance learning: 0 %
    - Proportion of a student's independent study: 20 %

    Scaling
    Methods of instructionHours
    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 scaledHours
    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 byJani Uusitalo