Course detail

Processing of multidimensional signals

FEKT-CZVSAcad. year: 2011/2012

See "Curriculum".

Language of instruction

English

Number of ECTS credits

6

Mode of study

Not applicable.

Guarantor

Ing. Karel Horák, Ph.D.

Department

Department of Control and Instrumentation (UAMT)

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. Fundamentals of signal processing.
2. Analogue and discrete signals.
3. Reconstruction and discrete filters.
4. Integral transform of one-dimensional signals.
5. One-dimensional and two-dimensional signals.
6. Analogue and discrete image.
7. Geometric transformations.
8. Brightness transformations.
9. Integral transform of two-dimensional signals.
10. Gradient operators.
11. Mathematical morphology.
12. Segmentation and classification.

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

Sonka M., Hlavac V., Boyle R.: Image Processing, Analysis and Machine Vision. Thomson 2008. ISBN 978-0-495-08252-1. (EN)
Russ J.C.: The Image Processing Handbook. CRC Press 1995. ISBN 0-8493-2516-1. (EN)

Classification of course in study plans

  • Programme EEKR-BC Bachelor's

    branch BC-AMT , 3. year of study, winter semester, optional specialized

Type of course unit

 

Lecture

26 hours, optionally

Teacher / Lecturer

Ing. Karel Horák, Ph.D.

Exercise in computer lab

39 hours, compulsory

Teacher / Lecturer

Ing. Karel Horák, Ph.D.