Course: Digital Image Processing

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Course title Digital Image Processing
Course code KKY/ZDO-E
Organizational form of instruction Lecture + Tutorial
Level of course Master
Year of study not specified
Semester Winter and summer
Number of ECTS credits 6
Language of instruction English
Status of course Compulsory-optional
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Course availability The course is available to visiting students
Lecturer(s)
  • Železný Miloš, Doc. Ing. Ph.D.
Course content
Definition of the digital image processing task, digitization of image information, representation of colour information. Pre-processign methods - point brightness transformations, geometric transformations, noise filtration, greadient operators, frequency analysis. Morphologic tranformations. Methods of segmentation. Methods of description of objects - description based on region boundaries, description based on shape of regions. Classification. Motion analysis. 3D imaging. Applications in photography, industry, human-computer communication, and medicine.

Learning activities and teaching methods
  • Contact hours - 39 hours per semester
  • Practical training (number of hours) - 26 hours per semester
  • Team project (50/number of students) - 25 hours per semester
  • Preparation for laboratory testing; outcome analysis (1-8) - 8 hours per semester
  • Preparation for an examination (30-60) - 58 hours per semester
prerequisite
Knowledge
have basic knowledge of linear algebra and matrix calculation
have basic knowledge of mathematical analysis
have basic knowledge of a theory of probability and mathematical statistics
Skills
analyse and interpret information
develop an algorithm and implement a task
evaluate obtained results
Competences
N/A
N/A
learning outcomes
Knowledge
have a knowledge of digital image processing
be able to explain basic principles of image pre-processing
be able to explain the methods of the object description and classification
Skills
be able to solve the image processing tasks
be able to apply methods of computer processing of image information
choose correct method for the image processing task
Competences
N/A
N/A
teaching methods
Knowledge
Lecture
Self-study of literature
Individual study
Skills
Practicum
Lecture with visual aids
Project-based instruction
Competences
Project-based instruction
Practicum
assessment methods
Knowledge
Seminar work
Continuous assessment
Oral exam
Skills
Seminar work
Continuous assessment
Skills demonstration during practicum
Competences
Seminar work
Continuous assessment
Recommended literature
  • Shapiro, Linda G.; Stockman, George C. Computer vision. Upper Saddle River : Prentice Hall, 2001. ISBN 0-13-030796-3.
  • Sonka, Milan; Hlavac, Vaclav; Boyle, Roger. Image processing, analysis, and machine vision. Toronto : Thomson, 2008. ISBN 978-0-495-08252-1.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester