FI:PB130 Intro Digital Image Processing - Course Information
PB130 Introduction to Digital Image ProcessingFaculty of Informatics
- 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).
- doc. RNDr. Petr Matula, Ph.D. (lecturer)
RNDr. Martin Maška, Ph.D. (seminar tutor)
Dmitry Sorokin, Ph.D. (seminar tutor)
- Guaranteed by
- doc. RNDr. Petr Matula, Ph.D.
Department of Visual Computing - Faculty of Informatics
Supplier department: Department of Visual Computing - Faculty of Informatics
- Mon 8:00–9:50 D1
- Timetable of Seminar Groups:
PB130/02: Fri 8:00–8:50 B311, M. Maška
PB130/03: Fri 9:00–9:50 B311, M. Maška
PB130/04: Wed 10:00–10:50 B311, M. Maška
- ! PV131 Digital Image Processing
Knowledge of high-school mathematics and understanding 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 37 fields of study the course is directly associated with, display
- Course objectives
- 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.
- 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.
- 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
- Follow-Up Courses
- Further comments (probably available only in Czech)
- Study Materials
The course is taught annually.
- Listed among pre-requisites of other courses