Introduction to OpenCV

• Overview of computer vision and its applications
• Introduction to OpenCV library and its features
• Installation and setup of OpenCV with Python

Basic Image Processing

• Loading and displaying images with OpenCV
• Manipulating image properties (size, color channels, etc.)
• Applying basic image transformations (scaling, rotation, etc.)

Image Filtering and Enhancement

• Applying various image filters (blur, sharpen, etc.)
• Histogram equalization and contrast enhancement
• Noise reduction techniques (Gaussian, median filtering)

Image Segmentation and Thresholding

• Segmenting images into regions of interest
• Applying thresholding techniques (simple, adaptive, etc.)
• Extracting contours and shapes from images

Feature Detection and Description

• Identifying and extracting image features (corners, edges, etc.)
• Understanding keypoint detection algorithms (SIFT, SURF, ORB)
• Describing and matching image features

Object Detection and Tracking

• Performing object detection using Haar cascades
• Implementing object tracking algorithms (CamShift, Optical Flow)
• Applying deep learning-based object detection with OpenCV

Camera Calibration and 3D Reconstruction

• Camera calibration techniques for image rectification
• Estimating camera parameters and distortion correction
• Performing 3D reconstruction from multiple images

Image Stitching and Panorama Creation

• Stitching multiple images to create a panorama
• Understanding image registration and homography estimation
• Implementing image stitching algorithms with OpenCV

Face Detection and Recognition

• Detecting and recognizing faces using OpenCV
• Training and utilizing face recognition models
• Implementing face-related applications (face tracking, emotion detection, etc.)

Image and Video Analysis

• Extracting and analyzing image features
• Performing motion detection and tracking
• Processing and analyzing video streams with OpenCV

Object Segmentation and Image Matting

• Understanding object segmentation techniques
• Implementing image matting algorithms
• Extracting foreground objects from images and videos

Image and Video Processing in Real-Time

• Implementing real-time image and video processing with OpenCV
• Utilizing webcam and video streams for real-time applications
• Optimizing OpenCV applications for real-time performance

Deep Learning Integration with OpenCV

• Integrating deep learning models with OpenCV
• Performing image classification and object detection with deep learning
• Transfer learning and fine-tuning with OpenCV and deep learning frameworks

OpenCV for Robotics and Computer Vision Applications

• Applying OpenCV for robotics and computer vision projects
• Building interactive applications and user interfaces with OpenCV
• Exploring real-world use cases and applications of OpenCV