Computer_vision_fundamentals

Computer vision fundamentals interactive Jupyter notebooks from Introduction to Computer Vision Udacity course and the Computer Vision Algorithms, Applications book 2nd Edition by Richard Szeliski and opencv trutorials.

Contents:

1. FIRST_image_as_function
   • Generating_noise.ipynb
   • Image_contrast_and_brightness.ipynb
   • Simple_images_operations.ipynb
2. SECOND_filters
   • Noise_removal_filters.ipynb
3. THIRD_template_matching
   • Template_matching.ipynb
4. FOURTh_edge_detection
   • Finding_images_gradients.ipynb
5. SIXTH_frequesncy_domain.
   • TO DO: Fourier transform of images.
   • TO DO: Canny edge detector.
   • TO DO: Hough transform.
6. Object Detection
   • 1_basic_object_detection_with_color_range_thresholding.py
7. Classification

resources:

• https://docs.opencv.org/
• http://szeliski.org/Book/
• https://classroom.udacity.com/courses/ud810