Base Knowledge
NA
Teaching Methodologies
1 – Expository method: a telling method were facts, concepts, principles and generalizations are defined andpresented by the teacher and discussed with the class, followed by demonstrative examples;
2 – Experimental method: an active method were the student develops the knowledge through the use of problemsolving and project development approaches, in group dynamics and individual reflective work. Regarding the evaluation the following methods are used:
Learning Results
To project, use and apply computer vision systems to industry to assess more or less complex properties without mechanical contact between the perception system and the measurement object.
Generally speaking, students are expected to acquire skills in the design and implementation of solutions in industrial nature and eventually of an applied scientific nature.
Program
1. Introduction
2-Vision
Bases, concepts and definitions
Formation and image acquisition: geometric transformations
Low-level image processing: filters and basic operations
Morphology and morphological operations
Region and contour descriptors
Color image: the color spaces
Image recognition: models and patterns
Lighting issues and techniques
Industrial artificial vision systems
3-Other systems of perception
Laser perception systems: 1D and 2D principles and systems
The 3D “cameras”
Other forms of perception.
Grading Methods
- - one individual assignment (50%) - 50.0%
- - one written exam (50%) - 50.0%
- - individual assignments (75%) - 75.0%
- - one written exam (25%) - 25.0%
Internship(s)
NAO
Bibliography
Digital Image Processing/W. Burger, M. Burge /2007
W. Burger, M. Burge – Digital Image Processing. Springer, Nov 2007
E. R. Davies – Machine Vision: Theory, Algorithms, Practicalities. Morgan Kaufmann, 2005
M. Sonka, V. Hlavac, R. Boyle – Image Processing: Analysis and Machine Vision. Thomson Learning Vocational, 1998/2007
Rafael C. Gonzalez, Richard E. Woods – Digital Image Processing. Prentice Hall, 2007
Rafael C. Gonzalez, Richard E. Woods, Steven L. Eddins – Digital Image Processing Using Matlab. Prentice Hall, 2004
D. Ballard, C. Brown – Computer Vision, Prentice-hall, 1982 (on-line em http://homepages.inf.ed.ac.uk/rbf/BOOKS /BANDB/bandb.html