SubjectsSubjects(version: 955)
Course, academic year 2019/2020
Image Processing - D445015
Title: Zpracování obrazů
Guaranteed by: Department of Computing and Control Engineering (445)
Faculty: Faculty of Chemical Engineering
Actual: from 2019 to 2020
Semester: both
Points: 0
E-Credits: 0
Examination process:
Hours per week, examination: 0/0, other [HT]
Capacity: winter:unknown / unknown (unknown)
summer:unknown / unknown (unknown)
Min. number of students: unlimited
State of the course: taught
Language: Czech
Teaching methods: full-time
Teaching methods: full-time
Note: course is intended for doctoral students only
can be fulfilled in the future
you can enroll for the course in winter and in summer semester
Guarantor: Procházka Aleš prof. Ing. CSc.
Mudrová Martina Ing. Ph.D.
Examination dates   Schedule   
Annotation -
The subject presents basic principles of image processing and applications of functional transforms in image analysis, A special attention is paid to processing of colors, image segmentation, rejection of noise components, image enhancement, data compression, pattern recognition and feature classification including estimation of accuracy and cross-validation errors. Applications include processing of images related to chemistry, material engineering, biochemistry, and biomedicine.
Last update: Procházka Aleš (20.01.2018)
Aim of the course -

Student will know how:

  • to choose appropriate methods for image processing
  • to apply selected mathematical methods and computational tools for image analysis
  • to use pattern recognition and classification methods in multidimensional data processing

Last update: Procházka Aleš (20.01.2018)
Literature -

Z - Gonzales R., Woods R., Digital Image Processing, Prentice Hall, 2008

D - I.T. Jolliffe: Principal Component Analysis, 2nd ed., Springer-Verlag, New York, 2002

D -

Last update: Procházka Aleš (20.01.2018)
Learning resources -

Last update: Procházka Aleš (20.01.2018)
Requirements to the exam -

During studies of this subject it is necessary either to submit the own paper using image processing methods in the area of own research or to evaluate an individual project.

Last update: Procházka Aleš (20.01.2018)
Syllabus -

1. Fundamentals of computational, programming and visualization system MATLAB / SIMULINK

2. Mathematical representation of multidimensional signals, image coding

3. Selected numerical methods for image processing: interpolation, approximation

4. Two-dimensional discrete Fourier transform in image analysis and resolution changes

5. Multi-dimensional digital filters in image-denoising

6. Gradient methods in image enhancement

7. Selected methods of image segmentation, feature extraction and classification

8. Discrete wavelet transform in data compression image denoising

9. Computational intelligence in microscopic data analysis and classification

10. Spatial data visualization and processing

11. Selected methods of biomedical multidimensional data processing

12. CASE STUDY 1: Image spectral analysis

13. CASE STUDY 2: Digital filtration and enhancement of multidimensional signals

14. CASE STUDY 3: Feature detection and classification of image components

Last update: Procházka Aleš (20.01.2018)
Registration requirements -

Mathematics 1, 2

Last update: Procházka Aleš (20.01.2018)
Course completion requirements -

Evaluation is based upon the individual project

Last update: Procházka Aleš (20.01.2018)
Coursework assessment
Form Significance
Defense of an individual project 100