Course: Image Processing

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Course title Image Processing
Course code ITE/IMA
Organizational form of instruction Lecture + Lesson
Level of course Master
Year of study not specified
Semester Winter and summer
Number of ECTS credits 5
Language of instruction English
Status of course Compulsory
Form of instruction Face-to-face
Work placements Course does not contain work placement
Recommended optional programme components None
Lecturer(s)
  • Paleček Karel, Ing. Ph.D.
  • Chaloupka Josef, doc. Ing. Ph.D.
Course content
Topics of the lectures 1. Digital image processing, computer graphic versus machine vision, image digitization, digital image properties, color and gray-scale image 2. Introduction to radiometry, 2D image, digital cameras, optic, CCD and CMOS chip 3. Color spaces, geometric transformation, pixel co-ordinate transformation, brightness interpolation 4. Pixel brightness transformations, linear discrete image transforms, 2D FFT and DCT, Hadamard transform, Wavelets 5. Image smoothing, edge detectors I. 6. Edge detectors II., image restoration 7. Segmentation, thresholding, edge-based and region-based segmentation, matching 8. Binary mathematical morphology 9. Gray-scale mathematical morphology 10. Skeletons and object marking, granulometry, morphological segmentation and watersheds 11. Region identification 12. Utilization of 2D convolution and correlation, region detection 13. Features for image recognition 14. Image objects recognition Laboratories and seminars 1. Matlab and image processing toolbox - introduction 2. Operation with BMP object, image histogram 3. Color spaces, geometric transformations 4. Image histogram equalization, 2D image spectrum 5. Filters for image smoothing 6. Edge detectors 7. Applications of image segmentation 8. Algorithms of binary mathematical morphology 9. Algorithms of gray-scale mathematical morphology 10. Using of top-hat transformation 11. Image recognition with chain codes 12. Application of region identification algorithm 13. Selection of image features for image recognition 14. Image recognition project

Learning activities and teaching methods
Monological explanation (lecture, presentation,briefing)
  • Class attendance - 56 hours per semester
Learning outcomes
The subject Image Analysis is focused on student's ability to understand basic principles of computer image processing and recognition.
Graduates from this course will obtain good knowledge from the field of image analysis.
Prerequisites
No specify

Assessment methods and criteria
Written exam

Recommended literature
  • Gonzales, R., C., Woods, R., E. Digital Image Processing, In: Pearson Education. USA, 2008. ISBN 978-0-13-168728-8.
  • Šonka M., Hlaváč V., Boyle R. Image Processing, Analysis, and Machine Vision. PWS Publishing, 1998. ISBN 0-534-953-93.


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