Course detail

Technical Applications of Image Analysis

FSI-RUIAcad. year: 2025/2026

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.

Language of instruction

Czech

Number of ECTS credits

5

Mode of study

Not applicable.

Guarantor

prof. RNDr. Miloslav Druckmüller, CSc.

Department

Institute of Mathematics (ÚM)

Entry knowledge

Basic knowledge of mathematical logic, set theory and mathematical analysis

Rules for evaluation and completion of the course

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.

Aims

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

Study aids

Jähne, B., Digital Image processing, 6th revised and extended edition, Springer Berlin Heidelberg New York, 2005, ISBN 3-540-24035-7 

 

Pratt, W. K., Digital image Processing, 4th edition, A John Wiley & Sons, Inc., Publication, 2007, ISBN: 978-0-471-76777-0

Prerequisites and corequisites

Not applicable.

Basic literature

 Pratt, W. K.: Digital Image Processing (4th Edition), New York: Wiley 2007 (EN)
Jähne, B., Digital Image processing, 6th revised and extended edition, Springer Berlin Heidelberg New York, 2005, ISBN 3-540-24035-7  (EN)

Recommended reading

Not applicable.

Classification of course in study plans

  • Programme N-IMB-P Master's

    specialization IME , 1 year of study, summer semester, compulsory-optional
    specialization BIO , 1 year of study, summer semester, compulsory-optional

  • Programme N-MET-P Master's 1 year of study, summer semester, compulsory

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

prof. RNDr. Miloslav Druckmüller, CSc.

Syllabus

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

26 hod., compulsory

Teacher / Lecturer

prof. RNDr. Miloslav Druckmüller, CSc.

Syllabus

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