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Lecturer(s)
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Chaloupka Josef, doc. Ing. Ph.D.
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Course content
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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
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Learning activities and teaching methods
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Monological explanation (lecture, presentation,briefing), Practicum
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Learning outcomes
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The main aim of this course is to introduce students to principle of digital image processing and recognition.
Theoretic piece of knowledge and practical skills from requered areas
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Prerequisites
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Unspecified
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Assessment methods and criteria
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Written exam
Requirements for getting a credit are activity at the seminars. Examination is of the written forms.
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Recommended literature
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Davies, E., R.:. Computer and Machine Vision, Fourth Edition: Theory, Algorithms, Practicalities. UK, 2012. ISBN 978-0123869081.
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Hlaváč, V., Sedláček, M. Zpracování signálu a obrazu. Praha, ČVUT, 2009. ISBN 978-80-01-04442-1.
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Chaloupka, J. elearning - kurz Úvod do zpracování obrazů.
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Šonka, M., Hlaváč, V., Boyle, R.:. Image processing, analysis, and machine vision. 3rd ed.. Toronto: Thomson Learning, 2008. ISBN 978-0-495-08252-1.
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