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17ADBZ2D - Digital 2D biosignal processing

Code Completion Credits Range Language
17ADBZ2D ZK 5 2P English
Department of Biomedical Informatics

The basic topics of the subject are techniques of 2D bio-signal processing, discrete 2D transforms, linear filtering, image reconstruction from projection, 3D reconstruction, 2D signal analysis (distortion and noise identification, wavelet decomposition, edge detection, segmentation, texture analysis), lossless and lossy compression, quality classification, 2D bio-signal processing in medicine (US, mammography, microscopic imaging, etc.)


Teaching takes place in the form of self-study with regular consultations. In addition to the examination, a written study is required by the student on the subject.

Syllabus of lectures:

1. 2D discrete transformations, DFT, Hadamard

2. Discrete cosine transformation

3. Wavelet decomposition and its utilization in 2D bio-signal analysis

4. Basic geometrical transformations

5. Mathematical model of the camera

6. Morphological image analysis, erosion, dilatation, morphological opening and closing, morphological filtering and its properties

7. Shape characteristics of objects in the image

8. Segmentation and thresholding (1)

9. Segmentation and thresholding (2)

10. FT, Cosine, Sine, Hadamard, Haar, Karhunen-Loeve transformations

11. Image restoration techniques (1)

12. Image restoration techniques (2)

13. Inverse filtering

14. Wiener filtering

Syllabus of tutorials:

The subject has only lectures

Study Objective:

The goal of the subject is provide knowledge of theoretically demanding methods of 2D bio-signal processing and their application or modification for particular purposes.

Study materials:


[1] Rafael C.Gonzales, Paul Wintz: Digital Image Processing, 2002.

[2] Sonka, Hlavac, Boyle: Image Processing, Analysis and Machine Vision, Thomson, 2008, ISBN: 0-495-08252-X


[3] Al Bovik: Handbook of Image & Video Processing. Academic Press, 2000.

[4] Gonzales, C.R., Woods, E.R., Eddins, L.S.: Digital Image Processing Using MATLAB. Prentice Hall, 2004.

[5] Sonka, M., Fitzpatrick, J.M.: Handbook of Medical Imaging, Volume 2. Medical Image Processing and Analysis, SPIE Press, 2000.

[6] Davies, E.R.: Machina Vision, Theory, Algorithms, Practicalities, 3rd edition, Elsevier Inc. 2005.

[7] Fontoura Costa, L., Marcondes Cesar, R.Jr.: Shape Analysis and Classification Tudory and Praktice, CRC Press, 2000.

[8] Soille, P.: Morphological Image Analysis, Principles and Applications, 2nd edition, Springer-Verlag, 2003.

The course is a part of the following study plans: