Machine vision and image processing

The course is not on the list Without time-table
Code Completion Credits Range Language
BI-SVZ Z,ZK 5 2P+2C Czech
Garant předmětu:
Marcel Jiřina
Lukáš Brchl, Marcel Jiřina, Jakub Novák
Lukáš Brchl, Marcel Jiřina, Jakub Novák, Jakub Žitný
Department of Applied Mathematics

Camera systems are becoming a common part of life by being universally available. Related to this phenomenon is the need to process and evaluate image information. The course introduces students to different types of camera systems and a variety of methods for image and video processing. The course is focused on practical use of camera systems for solving problems of practice that the graduates may encounter.



Syllabus of lectures:

1. Machine vision and physical nature

2. Types of sensors and optics

3. Camera system and image processing

4. Image as a matrix

5. Perspective and geometry of the image

6. Image preprocessing - Transformation and correction

7. Image preprocessing - Spatial and frequency domain filtering

8. Image segmentation - Edge

9. Image Segmentation - Surface

10. Image preprocessing - Morphology and shape characteristics

11. Video processing

12. Image recognition, object detection, modern trends

13. Modern trends in image processing.

Syllabus of tutorials:

1. Introductory exercise, familiarization with tools

2. Working in Jupyter notebook

3. Optical defects, camera calibration

4. Basics of segmentation

5. Advanced segmentation techniques

6. Perspective image

7. Image perspective, 360 ° lenses

8. Work with depth camera

9. Image classification, object detection

10. Basics of measurement with thermocamera

11. Line cameras

12. Practical exam tutorials

Study Objective:

The aim of the course is to acquaint students with the entire issue of the applications of machine vision from the theoretical fundamentals, through the use of the camera hardware, optics and lighting to create custom image processing algorithms with the aim of applying the task in real practice.

Study materials:

[1] McAndrew A., Computational Introduction to Digital Image Processing, CRC Press, 2. vydání, 2016

[2] Sundararajan D., Digital Image Processing: A Signal Processing and Algorithmic Approach, Springer, 2017

[3] Birchfield S., Image Processing and Analysis, Cengage Learning, 2016

[4] Acharya T., Ray A. K., Image Processing: Principles and Applications, Wiley, 2005

[5] Burger W., Burge M. J., Principles of Digital Image Processing: Fundamental Techniques, Springer-Verlag, 2009

Further information:
No time-table has been prepared for this course
The course is a part of the following study plans:
Data valid to 2023-09-28
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