FI:PV131 Digital Image Processing - Course Information
PV131 Digital Image ProcessingFaculty of Informatics
- Extent and Intensity
- 2/2. 4 credit(s) (plus extra credits for completion). Recommended Type of Completion: zk (examination). Other types of completion: z (credit).
- prof. RNDr. Michal Kozubek, Ph.D. (lecturer)
RNDr. Martin Maška, Ph.D. (seminar tutor)
doc. RNDr. David Svoboda, 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
- Wed 16:00–17:50 G101
- Timetable of Seminar Groups:
PV131/02: Tue 8:00–9:50 B311, M. Maška
PV131/03: Fri 10:00–11:50 B311, M. Maška
- Required knowledge: English, foundations of mathematics, linear algebra and calculus.
- 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
- The aim of this course is to introduce to the students the basics of digital image processing. The students will gain overview about the available techniques and possibilities of this field. They will learn basic image transforms, segmentation algorithms and problems of object measurements. They will be able to perform the basic techniques and apply them in practice. The lecture serves as the base for all those who want to attend to the topic in more details.
- Acquisition of 2D and 3D image data, process of signal digitization.
- Properties of the digital image, types of noise.
- Fourier transform and Nyquist sampling theorem.
- Convolution, PSF, OTF.
- Image preprocessing, linear and non-linear filters.
- Edge detection.
- Global and local thresholding, binary image and its modification.
- Mathematical morphology.
- Image segmentation.
- Object description.
- Object classification.
- Digital image processing in practice, biomedical applications.
- GONZALEZ, Rafael C. and Richard E. WOODS. Digital image processing. 3rd ed. Upper Saddle River, N.J.: Pearson Prentice Hall, 2008. xxii, 954. ISBN 9780135052679. info
- PRATT, William K. Digital image processing : PIKS scientific inside. 4th ed. Hoboken, N.J.: Wiley-interscience, 2007. xix, 782. ISBN 9780471767770. 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
- Teacher's information