Course detail
Processing of multidimensional signals
FEKT-BZVSAcad. year: 2012/2013
See "Curriculum".
Language of instruction
Czech, English
Number of ECTS credits
6
Mode of study
Not applicable.
Guarantor
Learning outcomes of the course unit
Knowledge in processing of multidimensional signals, especially in image processing.
Prerequisites
The subject knowledge on the secondary school level is required.
Co-requisites
Not applicable.
Planned learning activities and teaching methods
Teaching methods depend on the type of course unit as specified in the article 7 of BUT Rules for Studies and Examinations.
Assesment methods and criteria linked to learning outcomes
Requirements for completion of the course are specified by a regulation issued by the lecturer responsible for the course and updated for every academic year.
Course curriculum
1. Introduction to Signal Processing.
2. Discrete Image.
3. Image Acquisition.
4. Brightness Transformation.
5. Geometric Transformation.
6. Integral Transformation.
7. Edge and Corner Detection.
8. Noise Filtering.
9. Image Segmentation.
10. Description.
11. Classification.
12. Mathematical Morphology.
2. Discrete Image.
3. Image Acquisition.
4. Brightness Transformation.
5. Geometric Transformation.
6. Integral Transformation.
7. Edge and Corner Detection.
8. Noise Filtering.
9. Image Segmentation.
10. Description.
11. Classification.
12. Mathematical Morphology.
Work placements
Not applicable.
Aims
The course is divided into two parts: discrete signals and discrete images. First of all, fundamentals of signal processing, sampling theory, signal reconstruction and discrete filters are introduced with a view to further image processing. Second part of the course contains theory of discrete image processing as geometric and brightness transformations, integral transformations, gradient operators, mathematical morphology and fundamentals of segmentation and classification.
Specification of controlled education, way of implementation and compensation for absences
The content and forms of instruction in the evaluated course are specified by a regulation issued by the lecturer responsible for the course and updated for every academic year.
Recommended optional programme components
Not applicable.
Prerequisites and corequisites
Not applicable.
Basic literature
Not applicable.
Recommended reading
Russ J.C.: The Image Processing Handbook. CRC Press 1995. ISBN 0-8493-2516-1. (EN)
Sonka M., Hlavac V., Boyle R.: Image Processing, Analysis and Machine Vision. Thomson 2008. ISBN 978-0-495-08252-1. (EN)
Sonka M., Hlavac V., Boyle R.: Image Processing, Analysis and Machine Vision. Thomson 2008. ISBN 978-0-495-08252-1. (EN)
Classification of course in study plans
Type of course unit
Exercise in computer lab
39 hod., compulsory
Teacher / Lecturer