| Course Unit Code | 450-4101/02 |
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| Number of ECTS Credits Allocated | 4 ECTS credits |
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| Type of Course Unit * | Optional |
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| Level of Course Unit * | Second Cycle |
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| Year of Study * | |
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| Semester when the Course Unit is delivered | Summer Semester |
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| Mode of Delivery | Face-to-face |
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| Language of Instruction | English |
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| Prerequisites and Co-Requisites | Course succeeds to compulsory courses of previous semester |
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| Name of Lecturer(s) | Personal ID | Name |
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| MAC37 | Ing. Zdeněk Macháček, Ph.D. |
| Summary |
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The course Methods of Audio and Image Signal Processing in Control Systems provides a comprehensive modern foundation for working with digital audio and image signals, focusing on applications in industry, automation, measurement, and control systems. Students will become familiar with methods of signal acquisition, digitization, preprocessing, analysis, and interpretation, utilizing both classical digital signal processing techniques and artificial intelligence methods.
The curriculum covers audio signal analysis, including frequency analysis, synthesis, feature extraction, and speech recognition. Simultaneously, students are introduced to image signal processing, ranging from data preprocessing and geometric and brightness transformations to edge detection, segmentation, and object recognition in an industrial environment.
In the laboratories, students practically implement the discussed methods in the Python environment using the OpenCV library and MATLAB simulation software. They also test implementations on microcontrollers used in industrial technologies. Laboratory instruction includes work with virtual instrumentation as well as camera and acoustic measurement systems that correspond to real industrial applications, such as acoustic machine diagnostics, image-based quality control, process measurement and monitoring, and automated object recognition.
The course is designed for students specializing in control, industrial automation, robotics, measurement technology, acoustic diagnostics, and industrial and machine vision. |
| Learning Outcomes of the Course Unit |
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Mathematical algorithms, methods and principles of audio and video signal processing are studied in this subject. Students will study the processing methods for digital audio and video signals, which can be implemented in digital technology, microprocessor and processor technology. The subject includes knowledge in the fields of measurement, regulation, electronics, biomedical techniques, audio and video signal processing.
Learning outcomes of the course is presenting basic methods and algorithms of audio and video signal processing using methods of audio signal processing, sound effects, audio signal propagation, audio signal digitalization, analysis and synthesis of audio signal, audio signal compression, basics for speech signal processing, image signal processing, image signal digitization, image segmentation, edge detection, image transformation , image signal geometry, image signal filtering, object recognition. Students will be introduced to the implementation of selected basic methods in digital technology, microprocessor and processor technologies.
The elementary methods of audio and video signal processing are presented at lectures and in exercises the students practically realize the assignment of individual protocols, which thematically correspond to the topics discussed in the lectures. Practical usage of tools for processing and analysis of audio and video signals.
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| Course Contents |
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Lectures
1. Introduction to audio and image signal processing in control and industrial systems.
2. Sound acquisition and digitization using microphones and ADC for industrial applications.
3. Frequency analysis of audio signals using DFT, FFT, and spectrogram methods.
4. Synthesis and generation of audio signals using modulation.
5. Speech signal analysis using MFCC, LPC, and classical recognition methods.
6. AI methods for audio processing using neural networks.
7. Acquisition and digitization of image signals in industrial camera systems.
8. Image data preprocessing using filters for noise removal and normalization.
9. Geometric and brightness transformations of images, including histogram methods.
10. Image frequency analysis using 2D FFT and frequency domain filters.
11. Convolutional methods for edge detection and morphological operations in machine vision.
12. Image segmentation and object detection methods for control and automation.
13. AI methods for object recognition and advanced methods in industry.
Labs
1. Measurement and processing of audio and image data using MATLAB, Python, and virtual instrumentation.
2. Implementation and digitization of sound using ADC and DAC in MATLAB, Python, and a microcontroller.
3. Preprocessing of audio signals using filters and noise removal methods.
4. Audio analysis using frequency methods in MATLAB and Python.
5. Generation and synthesis of audio signals using digital methods.
6. Audio signal feature extraction using signal recognition methods.
7. Implementation of AI models for sound and speech classification in Python.
8. Measurement and processing of image data from camera systems using MATLAB, Python, and virtual instruments.
9. Image preprocessing and filtration for machine vision.
10. Geometric and brightness image transformations, including histogram adjustments.
11. Image frequency analysis using 2D FFT and frequency filters.
12. Implementation of edge detection and morphological operations in MATLAB, Python, and a microcontroller.
13. Image segmentation and implementation of object recognition methods using artificial intelligence. |
| Recommended or Required Reading |
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| Required Reading: |
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Gonzales, R.C., Woods, R.E.: Digital Image Processing. Prentice Hall,2017. ISBN 978-0133356724
Zolzer U.: Digital Audio Signal Processing. Wiley, 2008. ISBN 978-0470997857
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Hájovský, R., Pustková, R., Kutálek, F.:Zpracování obrazu v měřicí a řídicí technice. Učební text vytvořený v rámci projektu CZ.O4.01.3/3.2.15.2/0326 -E-learningové prvky pro podporu výuky odborných a technických předmětů. Ostrava, 2010.
Psutka J., Matoušek J.: Mluvíme s počítačem česky. Praha. Academia. 2006. ISBN 80-200-1309-1.
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| Recommended Reading: |
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| Petrou M., Petrou C.: Image Processing: The Fundamentals. Wiley, 2010. ISBN 978-0470745861 |
Hlaváč, V., Sedláček, M.: Zpracování signálů a obrazů, ČVUT, Praha, 2007.ISBN 978-80-01-03110-0.
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| Planned learning activities and teaching methods |
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| Lectures, Individual consultations, Experimental work in labs |
| Assesment methods and criteria |
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| Tasks are not Defined |