Subjects

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Image Processing - AP445002

Title:	Image Processing
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:	3/0, other [HT]
Capacity:	winter:unlimited / unknown (unknown) summer:unknown / unknown (unknown)
Min. number of students:	unlimited
State of the course:	taught
Language:	English
Teaching methods:	full-time
Level:
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:	Mareš Jan prof. Ing. Ph.D.
Interchangeability :	P445002

Examination dates Schedule

Annotation -

The subject presents principles of image processing and functional transforms usage in image analysis. Special attention is paid to colour processing, image segmentation, noise components rejection, 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: MUDROVAM (29.08.2018)

Course completion requirements -

Evaluation is based upon the individual project and oral exam

Last update: Pátková Vlasta (08.06.2018)

Literature -

R: Gonzales R., Woods R., Digital Image Processing, Prentice Hall, 2008

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

Last update: MUDROVAM (17.09.2018)

Teaching methods -

Lectures, project focussed on image processing metohod use

Last update: Pátková Vlasta (08.06.2018)

Requirements to the exam -

nothing

Last update: Pátková Vlasta (08.06.2018)

Syllabus -

Subject is focussed primarily on

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

Last update: Pátková Vlasta (08.06.2018)

Learning resources -

http://uprt.vscht.cz/prochazka/pedag/lectures/ATHENS_DSP.pdf

http://uprt.vscht.cz/prochazka/pedag/lectures/SP0_MATLAB_2006EN.pdf

http://basic-eng.blogspot.com/2005/12/object-detection-using-hough-transform.html

Last update: Pátková Vlasta (08.06.2018)

Learning outcomes -

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: Pátková Vlasta (08.06.2018)

Entry requirements -

nothing

Last update: Pátková Vlasta (08.06.2018)

Registration requirements -

nothing

Last update: Pátková Vlasta (08.06.2018)

Coursework assessment
Form	Significance
Defense of an individual project	90
Oral examination	10