Technical Applications of Image Analysis (FSI-RUI)

Academic year 2024/2025
Supervisor: prof. RNDr. Miloslav Druckmüller, CSc.  
Supervising institute: ÚM all courses guaranted by this institute
Teaching language: Czech
Course type: departmental course
Aims of the course unit:

The aim of the course is to provide the students with information about application of modern image processing techniques, image analysis and pattern recognition.
Learning outcomes and competences:
 
Prerequisites:

Basic knowledge of mathematical logic, set theory and mathematical analysis
Course contents:

The course deals with digital image data acquisition, calibration, filtration and analysis.  Moreover the course consists of pattern recognition for applications in technology and science.
Teaching methods and criteria:
 
Assesment methods and criteria linked to learning outcomes:

Course-unit credit based on written test.
The exam has a written and oral part.

 

Attendance at seminars is controlled. An absence can be compensated via solving additional problems.
Controlled participation in lessons:
 
Type of course unit:
    Lecture  13 × 2 hrs. optionally                  
    Computer-assisted exercise  13 × 2 hrs. compulsory                  
Course curriculum:
    Lecture

1. Classical and digital photography and its nowadays applications
2. CCD technology
3. CMOS technology
4. Digital image calibration
5. Color and muli-spectral images and their applications
6. Noise, classification, analysis, filtration
7. Additive noise filtration
8. Impulse noise filtration
9. MTF a PSF, convolution, deconvolution
10. Fourier methods of image processing
11. Adaptive filters
12. Image segmentation
13. Classification of objects and pattern recognition
    Computer-assisted exercise

1. Digital image, formats
2. CCD technology, properties of chips, optimization
3. CMOS technology, properties of chips, optimization
4. Digital image calibration
5. Color and muli-spectral images
6. Noise analysis 


7. Additive noise filtration
8. Impulse noise filtration
9. MTF a PSF, convolution, deconvolution
10. Fourier methods of image processing
11. Adaptive filters
12. Image segmentation
13. Classification of objects and pattern recognition
Literature - fundamental:
1.

Jähne, B., Digital Image processing, 6th revised and extended edition, Springer Berlin Heidelberg New York, 2005, ISBN 3-540-24035-7 
2.  Pratt, W. K.: Digital Image Processing (4th Edition), New York: Wiley 2007
The study programmes with the given course:
Programme Study form Branch Spec. Final classification   Course-unit credits     Obligation     Level     Year     Semester  
N-IMB-P full-time study IME Engineering Mechanics -- Cr,Ex 5 Compulsory-optional 2 1 S
N-IMB-P full-time study BIO Biomechanics -- Cr,Ex 5 Compulsory-optional 2 1 S
N-MET-P full-time study --- no specialisation -- Cr,Ex 5 Compulsory 2 1 S
C-AKR-P full-time study CLS -- Cr,Ex 5 Elective 1 1 S