Course Catalog 2009-2010 International Basic Pori International Postgraduate Open University |Degrees|     |Study blocks|     |Courses|

Person responsible

Heimo Ihalainen, Kalle Marjanen

Implementations

	Lecture times and places	Target group recommended to
Implementation 1	Periods 2 2 - 3

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

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 modified	13.03.2009
Modifier	Heikki Jokinen