Chapter 1

Digital Image Fundamentals

Image formation models and color spaces

medium • 1 min read

Image enhancement in spatial domain (Histogram equalization)

medium • 2 min read

Linear filtering and frequency domain (Fourier transforms)

medium • 3 min read

Image restoration and noise models

medium • 4 min read

Morphological image processing algorithms

medium • 5 min read

Chapter 2

Feature Extraction and Segmentation

Edge detection (Canny, Sobel) and corner detection (Harris)

medium • 1 min read

Hough transform for line and circle detection

medium • 2 min read

Local feature descriptors (SIFT, SURF, ORB)

medium • 3 min read

Image segmentation (Thresholding, Region growing)

medium • 4 min read

Active contours and watershed algorithms

medium • 5 min read

Chapter 3

Multiple View Geometry

Camera calibration and pinhole camera model

medium • 1 min read

Stereo vision, epipolar geometry, and fundamental matrix

medium • 2 min read

Disparity map computation

medium • 3 min read

Structure from Motion (SfM)

medium • 4 min read

Visual Simultaneous Localization and Mapping (vSLAM)

medium • 5 min read

Chapter 4

Deep Learning for Computer Vision

Convolutional Neural Networks (CNNs) architecture

medium • 1 min read

Classic CNN models (AlexNet, VGG, ResNet, Inception)

medium • 2 min read

Transfer learning and fine-tuning strategies

medium • 3 min read

Semantic segmentation (FCN, U-Net)

medium • 4 min read

Instance segmentation (Mask R-CNN)

medium • 5 min read

Chapter 5

Object Detection and Tracking

Two-stage object detectors (R-CNN, Fast/Faster R-CNN)

medium • 1 min read

Single-stage object detectors (YOLO, SSD)

medium • 2 min read

Object tracking algorithms (Kalman filters, Mean Shift)

medium • 3 min read

Face recognition and facial landmark detection

medium • 4 min read

Action recognition in video sequences

medium • 5 min read