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Computer Science
Computer Vision
Computer Vision with OpenCV
1. Introduction to OpenCV
2. Core Operations and Data Structures
3. Image Processing Fundamentals
4. Histograms and Image Analysis
5. Feature Detection and Description
6. Object Detection and Recognition
7. Video Analysis and Object Tracking
8. Advanced Image Processing
9. Camera Calibration and 3D Vision
10. Deep Learning Integration
Image Processing Fundamentals
Color Spaces and Conversions
BGR Color Space
Grayscale Conversion
HSV Color Space
HLS Color Space
LAB Color Space
YCrCb Color Space
Color Space Conversion Functions
Thresholding Techniques
Simple Thresholding
Binary Thresholding
Inverse Binary Thresholding
Truncate Thresholding
ToZero Thresholding
Inverse ToZero Thresholding
Adaptive Thresholding
Mean Adaptive Method
Gaussian Adaptive Method
Otsu's Binarization
Automatic Threshold Selection
Combined with Gaussian Filtering
Geometric Transformations
Scaling and Resizing
Interpolation Methods
Aspect Ratio Preservation
Translation
Affine Matrix for Translation
Pixel Coordinate Mapping
Rotation
Rotation Center and Angle
Rotation Matrix Calculation
Affine Transformation
Three-Point Mapping
Affine Matrix Estimation
Perspective Transformation
Homography Matrix
Four-Point Mapping
Image Warping
Image Filtering and Smoothing
2D Convolution
Custom Kernel Design
Border Handling
Averaging Filter
Box Filter Implementation
Gaussian Blurring
Kernel Size Selection
Sigma Parameter Tuning
Median Blurring
Noise Reduction Properties
Bilateral Filtering
Edge-Preserving Smoothing
Spatial and Color Parameters
Morphological Operations
Structuring Elements
Rectangular Elements
Elliptical Elements
Cross-shaped Elements
Custom Elements
Basic Operations
Erosion
Dilation
Advanced Operations
Opening
Closing
Morphological Gradient
Top Hat Transform
Black Hat Transform
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2. Core Operations and Data Structures
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4. Histograms and Image Analysis