Course Catalog 2009-2010
Postgraduate

Basic Pori International Postgraduate Open University

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Course Catalog 2009-2010

MIT-3216 Measurement Based on Digital Image 1, 5 cr

Person responsible

Heimo Ihalainen, Kalle Marjanen

Implementations

  Lecture times and places Target group recommended to
Implementation 1

Periods 2 2 - 3

 
International Students
Jatko-opiskelijat  


Requirements

Exercises, assignments and exam.

Principles and baselines related to teaching and learning

-

Learning outcomes

This course provides basic understanding of methods for measurements based on digital image, digital image processing and statistical analysis of image information. Exercises and assignments focus on the computational methods for measurements based on digital image.

Content

Content Core content Complementary knowledge Specialist knowledge
1. Various imaging systems and their properties. Representation and compression of digital images.  Basic optics, properties of radiation and noise. Reversible and irreversible packing.   Basic noise statistics. 
2. Image preprocessing methods. Using color images.  Background correction, digital filtering. Color representation.  Bayer-matrix for color images. 
3. Methods developed for machine vision e.g. edge detection, segmentation.  Object location. Edge locations.   
4. Statistical image analysis and texture analysis.  Basic statistics. Analysis based on histograms.  Analysis based on 2D-spectrum. 
5. Computer exercises and assignments cover the above topics in practice.     


Evaluation criteria for the course

Exercises, assignments and exam.

Assessment scale:

Numerical evaluation scale (1-5) will be used on the course

Study material

Type Name Author ISBN URL Edition, availability, ... Examination material Language
Book   Digital Image Processing   Gonzales, Rafael C. & Woods, Richard E.            English  


Prerequisites

Course Mandatory/Advisable Description
SGN-3016 Digital Image Processing I Advisable    

Prerequisite relations (Requires logging in to POP)

Correspondence of content

There is no equivalence with any other courses

More precise information per implementation

  Description Methods of instruction Implementation
Implementation 1   Lectures
Excercises
Practical works
   
Contact teaching: 0 %
Distance learning: 10 %
Self-directed learning: 10 %  


Last modified13.03.2009
ModifierHeikki Jokinen