Fundamentals of Computer Vision - Spring 2025
Course Staff
Course Logistics
- Lecture Videos:
Are available on Aparat
Office:
Room 402
Contact:
nasihatkon@kntu.ac.ir
Resources
- Computer Vision: Algorithms and Applications by Richard Szeliski
- Computer Vision: A Modern Approach
- Programming Computer Vision with Python By Jan Erik Solem
- OpenCV-Python Tutorials
- Selected Computer Vision Slides from Other Universites
Quera
Telegram channel
Previous Offerings:
Spring 2024 Spring 2022 Spring 2021 Spring 2020
Lectures
| Week | Topic | Lab | Course Material | |
|---|---|---|---|---|
Part 1 - Image Processing |
||||
| 1 | Introduction to Computer Vision and its real-world applications. Image representation, sampling and quantization, the light spectrum, visual perception, and color theory. |
Lab 0 : Introduction to Python Lab 0 - Instructions |
||
| 2 | Pixel-level operations, brightness and contrast adjustment, histograms, and histogram equalization. Introduction to color histograms and equalization. |
Lab 1 : Basics of NumPy and Matplotlib. Lab 1 - Instructions+Files |
||
| 3 | Image noise and Gaussian noise. Linear filtering and convolution and blurring techniques. | Lab 2 : Introduction to OpenCV. Reading, writing, and displaying images. Lab 2 - Instructions+Files Lab 3 : Working with videos and histograms. Lab 3 - Instructions+Files |
||
| 4 | Normalized cross-correlation and template matching. Types of noise and filtering techniques: box, gaussian, median and bilateral filters. |
Lab 4 : Working with noise, blurring, and filtering techniques Lab 4 - Instructions+Files |
||
| 5 | Image gradients and edge detection. Laplacian of Gaussian and the Canny edge detector. | Lab 5 : Capturing images from a camera device. Template matching and edge detection techniques. Lab 5 - Instructions+Files |
||
Part 2 - Computer Vision |
||||
| 6 | Image thresholding and binary image processing. Connected component analysis and basic morphological operations. |
Lab 6 : Binary image processing, connected components, thresholding, and morphology. Lab 6 - Instructions+Files |
||
| 7 | Hough Transform for shape detection: lines and circles. | Lab 7 : Hough Transforms Lab 7 - Instructions+Files |
Midterm Exam 2025 | |