Course detail

Digital Image Processing

CESA-SCZOAcad. year: 2023/2024

The course contains:
- basic concepts of multidimensional data,
- digital image processing and analysis,
- visualisation of image data and 3D graphics,
as a elementary and necessary instruments in the field of modern sport technology.

Language of instruction

Czech

Number of ECTS credits

5

Mode of study

Not applicable.

Guarantor

Ing. Jiří Chmelík, Ph.D.

Department

Department of Biomedical Engineering (UBMI)

Entry knowledge

successful completion of previous courses of the respective study branch, particularly:
- basic university mathematics
- introduction to theory of one-dimensional digital signal processing

Rules for evaluation and completion of the course

Requirements for successful completion of the subject:
- obtaining at least 12 points (out of 24 as course-unit credit based on active presence in demonstration exercises and two tests),
- successful passing of final written exam (up to 76 points, min. 38 points)
Obligatory attendance at tutorials, only 20% absence may be justified by an official medical certificate.
Attendance at the lectures is recommended.

Aims

The aim of course is
- understanding of basic terms and relations in the image processing field
- introducing into the most important approaches and methods of image processing, analysis and visualisation
- understandable interpretation and demonstration of corresponding practical applications
After completing the course, the student is capable of:
- interpreting the fundamental knowledge, concepts and their relationships in the field of signal and image processing,
- describing the basic methods in this area,
- describing the most important application processes and their practical use,
- choosing a proper approach and method to a given problem from this area,
- practically utilizing the chosen method in a specific computer implementation.
Written final exam will be certified by the acquired knowledge and skills to explain the learning material including a description of specific tasks.

Study aids

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

J. JAN: Číslicová filtrace, analýza a restaurace signálů (2. vydání), VUTIUM (Brno) 2002 (CS)
V. ŠEBESTA, Z. SMÉKAL: Signály a soustavy. Brno: VUT v Brně, 2003 (CS)
J. ŽÁRA: Moderní počítačová grafika (2. vydání). Computer Press, 2005, ISBN 80-251-0454-0 (CS)

Recommended reading

Not applicable.

eLearning

eLearning: currently opened course

Classification of course in study plans

  • Programme BPC-STC Bachelor's, 3. year of study, winter semester, compulsory

Type of course unit

 

Lecture

26 hours, optionally

Teacher / Lecturer

Ing. Jiří Chmelík, Ph.D.

Syllabus

1. Fundamentals of signal representation of images (two-dimensional signal, continuous and discrete image, sampling, random fields, two-dimensional image spectrum, time sequences of images)
2. Digital images and operators (classification of operators, basic point and local operators)
3. Basic image editing methods (contrast and color transformation)
4. Filtering in the time and frequency domain (mask operations, sharpening, noise suppression, customized filtering)
5. Parametric images and texture analysis 1 (local features, statistical and spectral parameters, parametric images, detection of edges, lines and corners, rough and adjusted edge representation)
6. Parametric images and texture analysis 2 (texture descriptors in the original and spectral domain, feature-oriented and syntactic analysis, texture-parametric images, texture gradient, local binary patterns, Markov random fields)
7. Image segmentation 1 (edge-oriented segmentation and Hough transform, segmentation based on parametric and texture-param. images, region-oriented segmentation, watershed method)
8. Image segmentation 2 (flexible contours, segmentation based on pattern recognition)
9. Geometric transformations and matching of images (interpolation in images, similarity criteria, optimization matching, basic methods of single- and multimodal matching)
10. Motion tracking and analysis (point detectors, models, classification approaches)
11. Pattern recognition (linear and non-linear models, pattern classification)
12. Basics of visualization techniques and computer graphics (color spaces, curves, surfaces, lighting models, texturing, projection methods)

Laboratory exercise

26 hours, compulsory

Teacher / Lecturer

Ing. Petra Nemčeková

Syllabus

1. Fundamentals of signal representation of images (two-dimensional signal, continuous and discrete image, sampling, random fields, two-dimensional image spectrum, time sequences of images)
2. Digital images and operators (classification of operators, basic point and local operators)
3. Basic image editing methods (contrast and color transformation)
4. Filtering in the time and frequency domain (mask operations, sharpening, noise suppression, customized filtering)
5. Parametric images and texture analysis 1 (local features, statistical and spectral parameters, parametric images, detection of edges, lines and corners, rough and adjusted edge representation)
6. Parametric images and texture analysis 2 (texture descriptors in the original and spectral domain, feature-oriented and syntactic analysis, texture-parametric images, texture gradient, local binary patterns, Markov random fields)
7. Image segmentation 1 (edge-oriented segmentation and Hough transform, segmentation based on parametric and texture-param. images, region-oriented segmentation, watershed method)
8. Image segmentation 2 (flexible contours, segmentation based on pattern recognition)
9. Geometric transformations and matching of images (interpolation in images, similarity criteria, optimization matching, basic methods of single- and multimodal matching)
10. Motion tracking and analysis (point detectors, models, classification approaches)
11. Pattern recognition (linear and non-linear models, pattern classification)
12. Basics of visualization techniques and computer graphics (color spaces, curves, surfaces, lighting models, texturing, projection methods)

eLearning

eLearning: currently opened course