Computer Vision Essentials 1

Study Group: Computer Vision Essentials Week 1

https://github.com/onlyphantom/cvessentials

Study Guide (Curriculum):
Chapter 1
Affine Transformation
Definition
Mathematical Definitions
Practical Examples
Motivation
Getting Affine Transformation
Trigonometry Proof
Code Illustrations
Summary and Key Points
Optional video
Rotation Matrix Explained Visually
w/ Bahasa Indonesia voiceover
References and learn-by-building modules
Chapter 2
Kernel Convolutions
Definition
Optional video
Kernel Convolutions Explained Visually
Mathematical Definitions
Padding
Smoothing and Blurring
A Note on Terminology
Kernels or Filters?
Correlations vs Convolutions?
Code Illustrations: Mean Filtering
Role in Convolution Neural Networks
Handy Kernels for Image Processing
Gaussian Filtering
Sharpening Kernels
Gaussian Kernels for Sharpening
Unsharp Masking
Summary and Key Points
References and learn-by-building modules
Chapter 3
Edge Detection
Definition
Gradient-based Edge Detection
Sobel Operator
Discrete Derivative
Code Illustrations: Sobel Operator
Gradient Orientation & Magnitude
Image Segmentation
Intensity-based Segmentation
Simple Thresholding
Adaptive Thresholding
Edge-based Contour Estimation
Contour Retrieval and Approximation
Canny Edge Detector
Edge Thinning
Hysteresis Thresholding
References and learn-by-building modules
Chapter 4
Digit Classification
A Note on Deep Learning
Why not MNIST?
Region of Interest
ROI identification
Arc Length and Area Size
Dive Deeper: ROI
ROI extraction
Morphological Transformations
Erosion
Dilation
Opening and Closing
Learn-by-building: Morphological Transformation
Seven-segment display
Practical Strategies
Contour Properties
References and learn-by-building modules
Chapter 5
Facial Recognition