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Course, academic year 2023/2024
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Digital Image Processing in Practice - NPGR032
Title: Digitální zpracování obrazu v praxi
Guaranteed by: Department of Software and Computer Science Education (32-KSVI)
Faculty: Faculty of Mathematics and Physics
Actual: from 2013
Semester: winter
E-Credits: 3
Hours per week, examination: winter s.:0/2, C [HT]
Capacity: unlimited
Min. number of students: unlimited
4EU+: no
Virtual mobility / capacity: no
State of the course: taught
Language: Czech
Teaching methods: full-time
Teaching methods: full-time
Additional information:
Guarantor: doc. RNDr. Barbara Zitová, Ph.D.
Class: Informatika Bc.
Informatika Mgr. - volitelný
Classification: Informatics > Computer Graphics and Geometry
Annotation -
Last update: G_I (15.05.2013)
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).
Course completion requirements -
Last update: RNDr. Tomáš Holan, Ph.D. (29.10.2019)

Úspěšné absolvování závěrečného testu - řešení zadané úlohy ze zpracování obrazu v Matlabu.

Literature -
Last update: G_I (14.05.2013)

Gonzales R. C., Woods R. E., Digital Image Processing (3rd ed.), Addison-Wesley, 2008

Pratt W. K.: Digital Image Processing (3rd ed.), John Wiley, New York, 2001

Syllabus -
Last update: G_I (14.05.2013)

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

Recomended lectures: NPGR013 (J. Flusser, B. Zitová), NPGR022 (J. Flusser, B. Zitová), a NAIL072 (J. Štanclová).

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