• Brno University of Technology - Centre of Sports Activities
  • Research centres

  • Pravděpodobně máte vypnutý JavaScript. Některé funkce portálu nebudou funkční.

Course detail

Numerical Methods of Image Analysis

Course unit code: FSI-TNM
Academic year: 2016/2017
Type of course unit: compulsory
Level of course unit: Master's (2nd cycle)
Year of study: 1, 2
Semester: summer
Number of ECTS credits:
Learning outcomes of the course unit:
Basic knowledge of classic and digital photography, modern mathematical methods of image processing,
image analysis and pattern recognition.
Mode of delivery:
90 % face-to-face, 10 % distance learning
Prerequisites:
Real and complex analysis, functional analysis, basic knowledge of programming
Co-requisites:
Not applicable.
Recommended optional programme components:
Not applicable.
Course contents (annotation):
The course familiarises students with the digital image processing theory and selected topics of image analysis. It focuses on digital images representation and reconstruction, filtration in frequency and spatial domain, noise analysis and filtration, image enhancement, image segmentation, objects analysis and recognition, analysis of multi-spectral images.
Recommended or required reading:
Klíma, M.; Bernas, M.; Hozman J.; Dvořák, P. : Zpracování obrazové informace, , 0
Pratt, W. K.: Digital Image Processing (Second Edition), New York: Wiley 1991
Druckmüller, M.; Heriban, P.: Digital Image Processing System 5.0, , 0
Petrou, M., and Bosdogianni, P., Image Processing: The Fundamentals, John Wiley& Sons, 1999.
Planned learning activities and teaching methods:
The course is taught through lectures explaining the basic principles and theory of the discipline. Exercises are focused on practical topics presented in lectures.
Assesment methods and criteria linked to learning outcomes:
Graded course-unit redit is awarded on condition of having passed a written test, and submitted a semester work.
Language of instruction:
Czech
Work placements:
Not applicable.
Course curriculum:
Not applicable.
Aims:
The aim of the course is to provide students with information about modern mathematical method of image processing, including programming techniques.
Specification of controlled education, way of implementation and compensation for absences:
Missed lessons can be compensated for via make-up topics of exercises.

Type of course unit:

Lecture: 26 hours, optionally
Teacher / Lecturer: prof. RNDr. Miloslav Druckmüller, CSc.
Syllabus: 1. Principles of classic and digital photography
2. Numeric image representation, graphics formats, image data compression
3. Images reconstruction, statistical image characteristics
4. Pixel values transforms
5. Convolution, space domain filtration
6. Fourier transform, frequency domain filtration
7. Low-pass and high-pass filters, nonlinear filters
8. Adaptive filters
9. Additive noise - analysis and filtration
10. Impulse noise - analysis and filtration
11. Image segmentation
12. Object analysis
13. Pattern recognition and object classification
seminars in computer labs: 26 hours, compulsory
Teacher / Lecturer: doc. Ing. Pavel Štarha, Ph.D.
Syllabus: 1. Using of ACC 6.0 image analyzer - basic principles.
2. Programming techniques in numerical image processing and analysis
3 Data compression (lossy and lossless)
4. Statistical methods of image analysis
5. Convolution, space domain filtration
6. FFT algorithm and its using in image processing
7. Low-pass and high-pass filters, nonlinear filters
8. Adaptive filters
9. Additive noise - analysis and filtration
10. Impulse noise - analysis and filtration
11. Image segmentation
12. Object analysis, moment method
13. Pattern recognition and object classification

The study programmes with the given course