Course: Image recording and processing

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Course title Image recording and processing
Course code NTI/SZO
Organizational form of instruction Lecture + Lesson
Level of course Bachelor
Year of study not specified
Semester Winter
Number of ECTS credits 5
Language of instruction Czech
Status of course Compulsory
Form of instruction Face-to-face
Work placements Course does not contain work placement
Recommended optional programme components None
Lecturer(s)
  • Lédl Vít, Ing. Ph.D.
  • Psota Pavel, Ing. Ph.D.
Course content
Lectures: 1. Introduction, image acquisition and processing, basic optics for imaging, aperture, depth of field, F - number, basic calculations. 2. Abberations, objective lens, selection of lens, macro lens extension tube. 3. Hypercentric and telecentric lenses, suitability, special imaging systems, filters, illumination. 4. Microscopes 5. CCD and CMOS sensors, photons convergence to electrical signal, special types of sensors, exposure time, formats of sensors, noise, dynamic range, resolution, the limits of applicability. 6. The conditions for acquiring high-quality image, look-up table, geometric transformations, histogram equalization, contrast enhancement, thresholding, noise reduction, transformation of intensities. 7. Fourier transform in 2D and its properties and applications in image processing, filtering, wavelet transform, convolution, correlation. 8. Image preprocessing, noise removal, sharpening, edge detection, etc.. 9. Binary and grayscale mathematical morphology. 10. Special methods for dimensions measurement, subpixel interpolation, Hough transform, Radon transform. 11. Ultrahigh resolution recording - limiting factors, image compression, interface. 12. Hyperspectral imaging, IR thermography. 13. Compact industrial systems for construction of computer vision applications. 14. Practical examples. Tutorials: 1 - radiometry - photometry - basic calculations. 2-5 - Optics and Imaging - calculations, samples 6-10 Working with cameras, imaging and capturing, design of laboratory imaging setup - controlled by Matlab 11-14 Image Processing in MATLAB

Learning activities and teaching methods
Monological explanation (lecture, presentation,briefing), Dialogue metods(conversation,discussion,brainstorming), Self-study (text study, reading, problematic tasks, practical tasks, experiments, research, written assignments)
  • Class attendance - 56 hours per semester
  • Home preparation for classes - 20 hours per semester
  • Preparation for exam - 38 hours per semester
  • Preparation for credit - 22 hours per semester
  • Preparation for comprehensive test - 14 hours per semester
Learning outcomes
Students will be acquainted with the basics of image recording and processing. The course will introduce hardware tools for digital recording and digital image processing. After completing the course, students will gain a comprehensive overview of the structure and function of the capturing system from illumination device, optical system (lens), to the selection of the appropriate camera. Furthermore, students gain basic information about the advanced sensing systems such as thermography, or hyperspectral imager. Software tools and mathematical methods are an essential part of understanding the problems of processing of the captured image, there will be a popular form of introduction to basic mathematical methods such as 2D FT and its applications, binary mathematical morphology and more. Students will become familiar with the application of instruments and systems for capturing and processing images in science and industry.
Students will gain basic knowledge about techniques for image acquisition and processing.
Prerequisites
Unspecified

Assessment methods and criteria
Combined examination

Unspecified
Recommended literature
  • Malý, Petr. Optika. Praha: Karolinum, 2013. ISBN 978-80-246-2246-0.
  • SVOBODA, Tomáš, Jan KYBIC a Václav HLAVÁČ. Image Processing, Analysis, and Machine Vision: A MATLAB Companion. Toronto: Thomson, 2008. ISBN 978-0-495-29595-2.
  • ŠONKA, Milan, Václav HLAVÁČ a Roger BOYLE. Image processing, analysis, and machine vision. 3rd ed.. Toronto: Thomson, 2008. ISBN 978-0-495-08252-1.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester
Faculty: Faculty of Mechatronics, Informatics and Interdisciplinary Studies Study plan (Version): Applied Sciences in Engineering (2019) Category: Special and interdisciplinary fields 1 Recommended year of study:1, Recommended semester: Winter