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Lecturer(s)
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Course content
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Lectures: 1. Introduction, digital image processing, basics of technical optics, iris, depth of focus, apreture, basic computations 2. Lenses, mounting of lenses, lenses choice, extension tubes, CCD sizes, telecentric lenses, filters: color and polarizing, illumination 3. Sensors' resolution, limits of usability, resolution increasing with dimensions measurement, small objects measurement 4. CCD and CMOS sensors, photons transferring to electrical signal, special types of sensors, exposure time, electronic shutter, AES and AGC functions 5. TV standards, analog video signal and it's transfer, aspect ratio 6. Video signal digitizing, digital interfaces, FireWire, GigE, Camera-Link, trigerring 7. Acquisition of quality image. Histogram. Image enhancement using histogram equalization and look-up table. Noise reduction. 8. Image preprocessing, edges enhancement, edge detection, filters, mathematical morphology, convolution 9. Special methods for dimensions measurement, subpixel accurancy. Hough transform 10. Frame grabbers for PC-systems, types and usability 11. Standards PCI, PCI-e, PC104, PXI, USB, Fire-Wire 12. Compact vision systems for easy digital image processing application building 13. Cameras and vision systems in safeguarding systems 14. Excursion in vision system integrator company APPLIC Practice: 1. Technical optics - basic computations 2. Technical optics - basic computations 3. Introduction to Siemes Spectation software 4. Automatization with Siemens vision systems 5. Setting of individual task 6. Solving of individual task 7. Solving and preview results of individual task with compact vision camera VS722 8. Industrial digital cameras with NI environments 9. Special modes of digital cameras - trigerring, ES and GC parametres 10. Digital image processing libraries 11. Library IMAQ Vision and possibilities demonstration 12. Presentation of some advanced tasks solved as a research activities 13. Credits awards
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Learning activities and teaching methods
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Monological explanation (lecture, presentation,briefing), Demonstration, Laboratory work
- Semestral paper
- 34 hours per semester
- Preparation for credit
- 15 hours per semester
- Preparation for exam
- 45 hours per semester
- Class attendance
- 56 hours per semester
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Learning outcomes
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Courses are focused on digital image acquisition, processing and hardware devices for machine vision system integration. Theoretical lectures will bring principles of machine vision system design, including illumination, lenses, cameras and proper evaluating hardvare selection. Students will work with machine vision systems, which are commonly used in industrial production. The aim of the course is students' ability to develop machine vision systems according the requested features.
Students will get knowledge about basis of digital image acquiring, digital image processing and evaluation hardware overview for vision systems development. During the practical education will students learn how to use all necessary components (illumination, optics, filters, lenses, cameras and software as well) and will find practical effects and advantages.
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Prerequisites
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Physics knowledge at level of high school
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Assessment methods and criteria
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Combined examination, Written exam
Requirements for getting a credit are activity at the practicals /seminars and successful passing the tests. Examination is of the written and oral forms.
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Recommended literature
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FISCHER, J.:. Optoelektronické senzory a videometrie. ČVUT, 2000.
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Hlaváč,V., Sedláček, M.:. Zpracování signálů a obrazů.. ČVUT FEL, Praha, 2001.
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Sonka, M, etc.:. Processing and Machine Vision.. PWS Publishing, USA, 2000.
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