Module #1 Introduction to Machine Vision Overview of machine vision, its applications, and importance in industry and daily life
Module #2 History and Evolution of Machine Vision Development and growth of machine vision, key milestones, and influential contributions
Module #3 Fundamentals of Image Processing Basic concepts of image processing, pixel manipulation, and filter operations
Module #4 Image Acquisition and Sensing Camera types, image sensors, and techniques for capturing high-quality images
Module #5 Image Preprocessing and Enhancement Removing noise, correcting distortions, and enhancing image features for analysis
Module #6 Thresholding and Segmentation Separating objects from the background, thresholding techniques, and region-based segmentation
Module #7 Feature Extraction and Representation Extracting meaningful features from images, shape, color, and texture analysis
Module #8 Object Recognition and Classification Techniques for recognizing objects, classification algorithms, and performance evaluation
Module #9 Deep Learning for Machine Vision Introduction to deep learning, convolutional neural networks (CNNs), and transfer learning
Module #10 Convolutional Neural Networks (CNNs) for Image Classification Designing and training CNNs for image classification tasks
Module #11 Object Detection and Localization Detecting and localizing objects within images, sliding window, and region proposal techniques
Module #12 Image Registration and Mosaicking Aligning and combining multiple images, feature-based and intensity-based registration
Module #13 Stereo Vision and 3D Reconstruction Computing depth information from stereo images, triangulation, and 3D model reconstruction
Module #14 Optical Character Recognition (OCR) and Document Image Analysis Extracting text from images, document layout analysis, and OCR techniques
Module #15 Medical Image Analysis and processing Applications of machine vision in medical imaging, image segmentation, and feature extraction
Module #16 Quality Inspection and Defect Detection Automated visual inspection, anomaly detection, and quality control using machine vision
Module #17 Robotics and Computer Vision Integration of machine vision with robotics, visual servoing, and grasping
Module #18 Surveillance and Monitoring Applications of machine vision in surveillance, object tracking, and activity recognition
Module #19 Machine Vision for Autonomous Vehicles Computer vision techniques for perception, localization, and control in autonomous vehicles
Module #20 Machine Vision for Agriculture and Food Processing Applications of machine vision in agriculture, plant phenotyping, and food processing
Module #21 Machine Vision for Quality Control in Manufacturing Automated visual inspection, defect detection, and quality control in manufacturing
Module #22 Machine Vision for Retail and E-commerce Applications of machine vision in retail, product recognition, and inventory management
Module #23 Machine Vision for Healthcare and Biomedical Applications Applications of machine vision in healthcare, biomedical imaging, and medical diagnosis
Module #24 Course Wrap-Up & Conclusion Planning next steps in Machine Vision career
