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Lecturer(s)
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Kmec Jakub, Mgr. Ph.D.
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Michálek Václav, Bc. Ing. Ph.D.
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Course content
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1. Introduction. Example of a practical problem. How to capture a defect and how to automatically find it. 2. Image sensors, types, properties, camera interfaces (analog, digital), image transmission, image formats. 3. Image digitization. 4. Image processing: image histogram and its use for thresholding. Basic operations, brightness corrections, histogram equalization, convolution. Image brightness equalization. 5. Types of noise: Gaussian noise, uniform noise, salt and pepper noise, poisson noise, speckle noise. Noise filtering in spatial and frequency domain (mean filter, median filter, FIR filter, Wiener filter, Fourier transform and its usage in filtering, inverse filter, ...). 6. Creating HDR images, combining images with different exposures. Video analysis and processing. Practical demonstration from industry. 7. Image morphology: dilation, erosion, closing and opening. Edge detection in images: zerocrossing, Canny edge detector. Finding the image perimeter, skeletonization. 8. Signal analysis and processing. Signal filtering, classification, use of neural networks for classification. Practical demonstration: signal classification in acoustic emission, signal detection in astroparticle physics. 9. Interpolation, splines and their construction in 1D and 2D. Use in image analysis.
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Learning activities and teaching methods
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Lecture
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Learning outcomes
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Image sensors, image digitization, image capturing, image processing. Demonstration using software.
The course focuses on the acquisition of knowledge and understanding of the processing of visual information. Present a method for processing image files.
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Prerequisites
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unspecified
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Assessment methods and criteria
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Student performance
Knowledge within the scope of the course topics
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Recommended literature
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Ian Goodfellow, Yoshua Bengio, Aaron Courville. (2016). Deep Learning.
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John F. Hughes, Andries van Dam, Morgan McGuire, David F. Sklar, James D. Foley, Steven K. Feiner, Kurt Akeley. (2013). Computer Graphics: Principles and Practice, 3rd edition.
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Milan Sonka, Vaclav Hlavac, Roger Boyle. (2008). Image Processing, Analysis, and Machine Vision.
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Rafael C. Gonzalez, Richard E. Woods. (2018). Digital Image Processing, 4th edition.
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Rafael C. Gonzalez, Richard E. Woods, Steven L. Eddins. (2020). Digital Image Processing Using MATLAB, 3rd edition.
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William K. Pratt. (2007). Digital Image Processing: PIKS Scientific Inside, 4th edition.
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