Course detail

Technical Applications of Image Analysis

FSI-RUI Acad. year: 2024/2025 Summer semester

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

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

The study programmes with the given course

Programme N-MET-P: Mechatronics, Master's, compulsory

Programme N-IMB-P: Engineering Mechanics and Biomechanics, Master's
specialization BIO: Biomechanics, compulsory-optional

Programme C-AKR-P: , Lifelong learning
specialization CLS: , elective

Programme N-IMB-P: Engineering Mechanics and Biomechanics, Master's
specialization IME: Engineering Mechanics, compulsory-optional

Type of course unit

 

Lecture

26 hours, optionally

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 hours, compulsory

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