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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
Histograms and Image Analysis
Histogram Calculation
Grayscale Histograms
Color Channel Histograms
Multi-dimensional Histograms
Histogram Parameters
Bin Count
Value Ranges
Mask Usage
Histogram Equalization
Standard Histogram Equalization
Contrast Limited Adaptive Histogram Equalization
CLAHE Parameters
Tile Grid Size
2D Histograms
Joint Color Channel Analysis
Visualization Techniques
Histogram Backprojection
Object Tracking Applications
Probability Map Generation
Image Gradients
Gradient Concepts
Sobel Operator
X-direction Gradients
Y-direction Gradients
Combined Gradients
Scharr Operator
Laplacian Operator
Gradient Magnitude and Direction
Edge Detection
Canny Edge Detection
Noise Reduction Stage
Gradient Calculation Stage
Non-Maximum Suppression
Double Thresholding
Edge Tracking by Hysteresis
Parameter Tuning
Lower Threshold
Upper Threshold
Aperture Size
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3. Image Processing Fundamentals
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5. Feature Detection and Description