PB130 Introduction to Digital Image Processing

Faculty of Informatics
Spring 2018
Extent and Intensity
2/1. 3 credit(s) (plus extra credits for completion). Recommended Type of Completion: zk (examination). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Petr Matula, Ph.D. (lecturer)
doc. RNDr. Martin Maška, Ph.D. (seminar tutor)
doc. RNDr. David Svoboda, Ph.D. (seminar tutor)
Dmitry Sorokin, Ph.D. (assistant)
Guaranteed by
doc. RNDr. Petr Matula, Ph.D.
Department of Visual Computing – Faculty of Informatics
Supplier department: Department of Visual Computing – Faculty of Informatics
Timetable
Tue 10:00–11:50 D2
  • Timetable of Seminar Groups:
PB130/01: Wed 11:00–11:50 B311, M. Maška, P. Matula, D. Svoboda
PB130/02: Fri 9:00–9:50 B311, M. Maška, P. Matula, D. Svoboda
Prerequisites
! PV131 Digital Image Processing
Knowledge of high-school mathematics and understanding and design of simple algorithms is supposed.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 38 fields of study the course is directly associated with, display
Course objectives
The objective of the course is to introduce students to the area of digital image processing in order to get necessary background for studying other courses from the area.
Learning outcomes
At the end of the course a student should: know the basic terminology related to digital image processing; know about the typical problems from digital image processing; understand the principle of simple algorithms for image processing and know how to use them. The course is intended as an introduction to digital image processing.
Syllabus
  • Human vision, image acquisition and basic image computer representations.
  • Color images.
  • Point transforms. Histogram.
  • Linear image filtering. Convolution.
  • Non-linear filters.
  • Mathematical morphology.
  • Edge detection. Gradient.
  • Regions in binary images and their description.
  • Image segmentation.
  • Applications of digital image processing.
Literature
    recommended literature
  • BURGER, Wilhelm and Mark James BURGE. Digital image processing : an algorithmic introduction using Java. 1st ed. New York: Springer, 2008, xx, 564. ISBN 9781846283796. info
    not specified
  • GONZALEZ, Rafael C. and Richard E. WOODS. Digital image processing. 2nd ed. Upper Saddle River: Prentice Hall, 2002, xx, 793. ISBN 0130946508. info
  • SONKA, Milan, Václav HLAVÁČ and Roger BOYLE. Image processing analysis and machine vision [2nd ed.]. 2nd ed. Pacific Grove: PWS Publishing, 1999, xxiv, 770. ISBN 0-534-95393-X. info
Teaching methods
Lectures followed by class exercises in a computer room to gain hands-on experience.
Assessment methods
Lectures in Czech, study materials in English. Mandatory practicals (labs) on computers with mandatory homeworks. Written final exam, no materials allowed.
Language of instruction
Czech
Follow-Up Courses
Further comments (probably available only in Czech)
Study Materials
The course is taught annually.
Listed among pre-requisites of other courses
The course is also listed under the following terms Spring 2014, Spring 2015, Spring 2016, Spring 2017, Autumn 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.
  • Enrolment Statistics (Spring 2018, recent)
  • Permalink: https://is.muni.cz/course/fi/spring2018/PB130