OpenCV 3 image and video processing with Python
OpenCV 3 with Python
Image - OpenCV BGR : Matplotlib RGB
Basic image operations - pixel access
iPython - Signal Processing with NumPy
Signal Processing with NumPy I - FFT and DFT for sine, square waves, unitpulse, and random signal
Signal Processing with NumPy II - Image Fourier Transform : FFT & DFT
Inverse Fourier Transform of an Image with low pass filter: cv2.idft()
Image Histogram
Video Capture and Switching colorspaces - RGB / HSV
Adaptive Thresholding - Otsu's clustering-based image thresholding
Edge Detection - Sobel and Laplacian Kernels
Canny Edge Detection
Hough Transform - Circles
Watershed Algorithm : Marker-based Segmentation I
Watershed Algorithm : Marker-based Segmentation II
Image noise reduction : Non-local Means denoising algorithm
Image object detection : Face detection using Haar Cascade Classifiers
Image segmentation - Foreground extraction Grabcut algorithm based on graph cuts
Image Reconstruction - Inpainting (Interpolation) - Fast Marching Methods
Video : Mean shift object tracking
Machine Learning : Clustering - K-Means clustering I
Machine Learning : Clustering - K-Means clustering II
Machine Learning : Classification - k-nearest neighbors (k-NN) algorithm