Syllabus
Matlab basics
Fourier transform ( basics: amplitude, phase, real and imaginary part; filtering in frequency domain)
Noise removal (noise and its variations, noise parameters, noise removal - convolution filters, frequency based filters, averaging)
Edge detection and histogram equalization (Roberts, Sobel, Maar-Hilbert, edge enhancement, histogram equalization)
Morphology (erosion, dilatation, opening, closing, object counting, skeletonization)
Image registration (correlation, a registration of an affinely transformed image )
Deconvolution (convolution theorem, inverze filtering, Wiener filter, parameter estimation)
Classification (Fourier descriptors, feature space, distance matrix, classification, moment invariants)
Hough transform
Segmentation ( image segmentation, object classification)
Detailed info can be found here http://zoi.utia.cas.cz/teaching.
Recomended lectures: NPGR013 (J. Flusser, B. Zitová), NPGR022 (J. Flusser, B. Zitová), a NAIL072 (J. Štanclová).
Annotation
The seminar aims at digital image processing and pattern recognition. It complements NPGR002.
Moreover, experiments and practical applications will be demonstrated here, in the programming language MATLAB. The covered topics are: image acquisition and preprocessing (noise reduction, contrast enhancement, deblurring), edge detection, geometric transformations, features for object description and methods of automatic recognition (classification).