|
Lecturer(s)
|
-
Paleček Karel, Ing. Ph.D.
-
Chaloupka Josef, doc. Ing. Ph.D.
|
|
Course content
|
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 chips 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 recognitio
|
|
Learning activities and teaching methods
|
|
Monological explanation (lecture, presentation,briefing)
|
|
Learning outcomes
|
The subject Machine Vision is focused on student's ability to understand basic principles of computer image processing and recognition
|
|
Prerequisites
|
unspecified
|
|
Assessment methods and criteria
|
unspecified
|
|
Recommended literature
|
-
DAVIES, E., R. Computer and Machine Vision, Fourth Edition: Theory, Algorithms, Practicalities. UK, 2012. ISBN 978-0123869081.
-
HLAVÁČ, Václav a Miloš SEDLÁČEK. Zpracování signálů a obrazů. 2. přeprac. vyd.. Praha: ČVUT, 2007. ISBN 978-80-01-03110-0.
-
Chaloupka, J. Přednášky, cvičení - RZO. Liberec, TUL.
-
ŠONKA, Milan, Václav HLAVÁČ a Roger BOYLE. Image processing, analysis, and machine vision. 3rd ed.. Toronto: Thomson, 2008. ISBN 978-0-495-08252-1.
|