COURSE DESCRIPTION
Practical examples and applications of Image Processing and Pattern Recognition
A seminar that offers a deepening of the theory of digital image processing and recognition of the NPGR002 course and its supplementation with experiments and practical applications in the MATLAB programming language environment. Attention is paid to digital image digitization, preprocessing (noise suppression, contrast enhancement, blur removal), edge detection, geometric transformations, flag-based object description, and automatic recognition (classification) methods. The course can be taken concurrently with NPGR002, as a practicum, or independently after completing NPGR002.
ZS 2024/2025
Google form for enrolling students and arranging an online tutorial.
NPGR002
We highly recommend taking the optional exercises for this course (in person).
LABS SOURCES
Individual materials for the exercises will be published here during the semester.
- Lab 1 - NPGR032 - 07. 10. 2024 - 08:00 a.m.
- Introduction to Python, Python fundamentals for Image Processing, Colab, GitHub, Basic Image Manipulation, Fourier Transform
- GitHub Classroom link
- Lab 2 - NPGR032 - 4. 11. 2024 - 08:00 a.m.
- Noise reduction, Edge detection, Histogram
- GitHub Classroom link
- Lab 3 - NPGR032 - 17. 11. 2024 - 08:00 a.m.
- Image Registration, Morphological Transformations
- GitHub Classroom link
- Lab 4 - NPGR032 - 2. 12. 2024 - 08:00 a.m.
- Hough and Radon Transform
- GitHub Classroom link