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Lecturer(s)
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Prokýšek Miloš, PhDr. Ph.D.
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Course content
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Content of lectures " Bitmap graphics o Digitalization of visual data o Image color depth " Image preprocessing o Compression o Noise reduction o Matrix filters " Segmentation o Hough transform o Contour finding o Color separation " Image understanding o Haar's detector o AI
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Learning activities and teaching methods
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Monologic (reading, lecture, briefing), Practical training
- Class attendance
- 28 hours per semester
- Semestral paper
- 20 hours per semester
- Preparation for exam
- 10 hours per semester
- Preparation for classes
- 14 hours per semester
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Learning outcomes
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The aim of this course is to introduce to students methods of computer image processing and basics of machine perception. Students will gain knowledge in area od basics of bitmap graphics and fundamentals of image preprocessing, segmentations and understanding. Course also deals with AI methods of image interpretation.
The student is able to work with computer graphics at the basic level and to develop embedded-systems applications using the well-known technics.
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Prerequisites
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Basic programming skills.
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Assessment methods and criteria
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Oral examination, Analysis of student's work activities (technical works)
Create and defend the semestral project in a form of a complete program for data processing. Oral exam from computer graphics theory
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Recommended literature
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Russ, John C.; Russ, Christian J. Introduction to image processing and analysis. Boca Raton : CRC Press, 2008. ISBN 978-0-8493-7073-1.
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Russ, John C. The image processing handbook. 4th ed. Boca Raton : CRC Press, 2002. ISBN 0-8493-1142-X.
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Žára, Jiří. Moderní počítačová grafika. Vyd. 1., Na obálce uvedeno 2. přeprac. a rozš. vyd. Brno : Computer Press, 2004. ISBN 80-251-0454-0.
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