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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 Content of practicals: Labs are following topics of lectures
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Learning activities and teaching methods
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Monologic (reading, lecture, briefing), Project-based learning
- Class attendance
- 28 hours per semester
- Preparation for classes
- 28 hours per semester
- Semestral paper
- 10 hours per semester
- Preparation for exam
- 10 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)
Defense of semestral work with an oral exam in computer graphics theory.
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Recommended literature
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Russ, John C. Introduction to image processing and analysis, CRC Press, 2008.
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Russ, John C. The image processing handbook, CRC Press, 2002.
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ŽÁRA, Jiří, Bedřich BENEŠ a Jiří SOCHR. Moderní počítačová grafika. 2., přeprac. a rozš. vyd. Praha: Computer Press, 2004, 609 s. ISBN 80-251-0454-0.
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