Code: 17DAZ2D Digital 2D Biosignal Processing
Lecturer: doc. Ing. Zoltán Szabó Ph.D. Weekly load: 2+0 Assessment: ZK
Department: 17112 Credits: 5 Semester: W,S
Description:
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 and ecology (US, mammography, microscopic imaging)


Contents:
1. Linear 2D systems, 2D spectra, digital representation of images, 2D discrete
operators
2. 2D discrete transformations, DFT, cosine and sine, Hadamard, Haar
transformation
3. Image restoration, distortion and noise identification, Wiener filtering in
frequency domain
4. Image segmentation. Texture analysis, brightness calibration, image
segmentation based on histogram, optimal tresholding
5. Spline curves, image segmentation based on deformable models
6. Wavelet decomposition and its utilization in 2D bio-signal analysis and
compression
7. Noise suppression, nonlinear filtering, Gauss, median, mode, rank-order
filtering and their properties
8. Morphological image analysis, erosion, dilatation, morphological opening and
closing, morphological filtering and its properties
9. 3D reconstruction of object position and orientation based on its 2D
projection, manual transport analysis
10. Image registration, geometrical transformation, image registration
11. Image compression, Lossless and lossy compression JPEG, JPEG2000
12. Line detection, Hough transformation, circle detection, generalized Hough
transform
13. 2D objects representation based on their contours, object classification
based on contour descriptors
14. 2D bio-signal processing in medicine and ecology

Recommended literature:
[1]Rafael C.Gonzales, Paul Wintz: Digital Image Processing, 2002.
[2]Al Bovik: Handbook of Image & Video Processing. Academic Press, 2000.
[3]Gonzales, C.R., Woods, E.R., Eddins, L.S.: Digital Image Processing Using
MATLAB. Prentice Hall, 2004.
[4]Sonka, M., Fitzpatrick, J.M.: Handbook of Medical Imaging, Volume 2. Medical
Image Processing and Analysis, SPIE Press, 2000.
[5]Davies, E.R.: Machina Vision, Theory, Algorithms, Practicalities, 3rd
edition, Elsevier Inc. 2005.
[6]Fontoura Costa, L., Marcondes Cesar, R.Jr.: Shape Analysis and
Classification, Tudory and Praktice, CRC Press, 2000.
[7]Soille, P.: Morphological Image Analysis, Principles and Applications, 2nd
edition, Springer-Verlag, 2003.