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Lecturer(s)
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Dobrovolný Martin, Ing. Ph.D.
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Pidanič Jan, doc. Ing. Ph.D.
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Course content
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1. Introduction, signal classification in continuous and discrete time, description and meaning (deterministic, random, causal, finite, periodic), special signals (unit jump, rectangular pulse, Dirac pulse, unit pulse, sampling signal). 2. Characteristics of time domain signals (mean, energy, power, mutual energy and power, mutual correlation and autocorrelation). 3. Signal quantization, Signal sampling. 4. Types of AD converters and their basic properties. 5. Signal spectrum, Fourier transform, basic properties, visualization. 6. Use of DFT and FFT in signal analysis. 7. Principles of sensing image and sound information, principles of sensing elements. 8. Analog sensing systems, Analog TV signal transmission. 9. Digital sensing systems, CMOS and CCD sensing elements. 10. Available integrated circuits for signal processing and their basic properties. 11. C# - Convolution and its use in image filtering. 12. C# - Digital signal simulation and modeling. 13. C# - Image and 1D signal preprocessing techniques, edge detection in image matrix.
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Learning activities and teaching methods
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Methods of individual activities
- Home preparation for classes
- 4 hours per semester
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Learning outcomes
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The course acquaints with the basic methods of digital signal analysis and image processing. The aim is to acquaint students with techniques used in the transmission and processing of signal and image data, signal digitization and modern image sensing elements. The student will get an overview of the signal processing and signal analysis in time and frequency domain.
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Prerequisites
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None
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Assessment methods and criteria
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Oral examination
The student attendance on all practice courses is necessitated. On the credit test the students have to present the courses knowledges. The exam is based on theoretical knowledges presented on the lectures. A condition for credit and examination is: 1. Submission and analysis of the term paper + theoretical discussion of the assigned problem. During the exam, understanding and approach to the problem is assessed. Comprehensiveness of the solution and independence. Authorship of the thesis is verified during the examination. 2. Presentation of a short video with descriptions/comments in EN. 3. Return of borrowed items. Semester work At the end of the semester, the student, in agreement with the teacher, chooses a suitable topic for the term paper. It is possible to use the remaining time and consult in the scheduled classes. The student may use the laboratory facilities by arrangement. Topics from previous years may be accepted only if the student demonstrates substantial completion of the topic (more than 50%) and justifies why the topic was not completed. The term paper is created in the Microsoft Visual Studio - C# environment. Students can use their UPCE student licenses at home. During the course we create a project together - a "little Photoshop" - at the end of the semester each student chooses a suitable topic to incorporate into the project. With a few exceptions, the use of code taken from the course is not allowed in the term paper. Students must create the code using their own algorithms. The course of the exam The course ends with an exam, in which the student defends the term paper (presenting the procedures and describing the source code in detail) and demonstrates the knowledge gained through discussion. In case it is proved that the student is not the author of the thesis, the exam cannot be recognized and a new topic must be assigned. Furthermore, the student will create a presentation in English, which the teacher will then upload to YouTube. The presentation must include: - Name of the author of the project, Year of defence, Title of the course. - Development diagram with description of algorithms. - A sample of the function. - The presentation should not exceed 5 min. It is preferable to use subtitles instead of comments. - In the first class, students will be introduced to examples of previous presentations.
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Recommended literature
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CASTLEMAN, Kenneth R. Digital image processing. Englewood Cliffs. ISBN 978-0132114677.
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KLÍMA, Miloš. Zpracování obrazové informace. ISBN 80-010-1436-2.
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PRCHAL, Josef a Boris ŠIMÁK. Digitální zpracování signálů v telekomunikacích. ISBN 80-010-2149-1.
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