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
Supervisor
Department
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