Lectures:
1. Introduction to the problematics of image processing. Using Matlab for image processing.
2.Properties of digital image.
3. Transformations of brightness, Histogram.
4. Image transforms. The Fourier transform, discrete Fourier transform, Properties of Fourier transform and its application in digital image processing.
5.Image filtering in frequency domain.
6. Geometrical transformations of images.
7. Sampling and reconstructing of images.
8. Morphological transformations of images.
9. Image segmentation.
10. Image recognition.
11. Color image processing.
12. JPEG and MPEG compression.
13. Final test.
Computer labs:
During the exercises, the students work out a series of practical tasks (convolution, Fourier transform, compression, transformations of brightness, geometrical transformations, measuring objects, and classification). The tasks are prepared in the form of templates (pre-prepared programs) into which the sudents fill their own source code. In this way, they can focus on substantial and interesting issues.
Project:
Student processes the project on "Image analysis using classical methods of image processing.".
Time demands of the project is 10 hours.
1. Introduction to the problematics of image processing. Using Matlab for image processing.
2.Properties of digital image.
3. Transformations of brightness, Histogram.
4. Image transforms. The Fourier transform, discrete Fourier transform, Properties of Fourier transform and its application in digital image processing.
5.Image filtering in frequency domain.
6. Geometrical transformations of images.
7. Sampling and reconstructing of images.
8. Morphological transformations of images.
9. Image segmentation.
10. Image recognition.
11. Color image processing.
12. JPEG and MPEG compression.
13. Final test.
Computer labs:
During the exercises, the students work out a series of practical tasks (convolution, Fourier transform, compression, transformations of brightness, geometrical transformations, measuring objects, and classification). The tasks are prepared in the form of templates (pre-prepared programs) into which the sudents fill their own source code. In this way, they can focus on substantial and interesting issues.
Project:
Student processes the project on "Image analysis using classical methods of image processing.".
Time demands of the project is 10 hours.