This tutorial to help you understand the basics of image processing and to develop computer vision tasks with OpenCV. This tutorial is supported with examples. The theory of most functions used is explained at a basic level. It is explained what the functions are for and what the function parameters are. Someone who understands and completes this tutorial will be able to easily develop basic level computer vision tasks.

1. Reading and Showing Images
2. Changing Colorspaces
3. Create Histogram
4. Histogram Equalization
   • Adaptive Histogram Equalization
5. Thresholding
6. Image Resizing
7. Drawing and Writing in Images
8. Arithmetic Operations on Images
   • Image Addition
   • Image Blending
   • Bitwise Operations
9. Morphological Transformations
   • 1. Erosion
   • 2. Dilation
   • 3. Opening
   • 4. Closing
   • 5. Morphological Gradient
   • Structuring Element
10. Image Smoothing
11. Perspective Warping
12. Shifting and Rotation
13. Harris Corner Detection
14. Shi-Tomasi Corner Detector & Good Features to Track
15. Image Gradients
16. Canny Edge Detection
17. Contours
    • Contour Features
      • 1. Moments
      • 2. Contour Area
      • 3. Contour Perimeter
      • 4. Contour Approximation
      • 5. Convex Hull
      • 6. Bounding Rectangle
        • 6.1. Straight Bounding Rectangle
        • 6.2 Rotated Rectangle
18. Template Matching
19. Probabilistic Hough Line Transform
20. Hough Circle Transform
21. Haar Cascades
    • 1. Face Detection
    • 2. Eye Detection
    • 3. Mouth Detection
    • 4. Smile Detection
    • 5. Simple Mask Detection

1. Capture Video from Camera
2. Capture Video from IP Camera
3. Playing Video from File
4. Playing Video from Youtube
5. Saving a Video
6. Video Capture Properties
7. Background Subtraction
8. Trackbar
9. Simple Blob Detection
10. Calculate FPS
11. Image to Text
    • Real Time Text Recognition

1. https://docs.opencv.org

2. https://www.geeksforgeeks.org

3. https://learnopencv.com

4. https://stackoverflow.com

5. https://codimp.com

6. P. Viola and M. Jones, "Rapid object detection using a boosted cascade of simple features," Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, 2001, pp. I-I, doi: 10.1109/CVPR.2001.990517.

• Additionally, other resources are mentioned in the notebook.