Computer Vision: From Fundamentals to Real-World AI Applications

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Course Modules:

Module 1: Introduction to Computer Vision

What is computer vision and how does it work?

Common applications in industry

Tools and setup: OpenCV, Python, and libraries

Module 2: Image Processing Essentials

Color models and pixel operations

Blurring, filtering, and edge detection

Thresholding and segmentation techniques

Module 3: Feature Extraction & Shape Detection

Corners, contours, and histogram analysis

Detecting lines, shapes, and motion

Keypoint matching with ORB and SIFT (OpenCV)

Module 4: Face and Emotion Recognition

Using Haar Cascades and DNNs for face detection

Real-time face tracking and landmark detection

Emotion recognition using pre-trained models

Module 5: Video Analysis and Object Tracking

Reading and writing video files

Real-time frame analysis

Multi-object tracking and background subtraction

Module 6: Deep Learning for Vision Tasks

Convolutional Neural Networks (CNNs)

Training image classifiers with TensorFlow and Keras

Using transfer learning (VGG, ResNet)

Module 7: Object Detection and Localization

YOLO, SSD, and MobileNet-based models

Drawing bounding boxes and labels

Object tracking in real-time systems

Module 8: OCR and Scene Understanding

Optical Character Recognition with Tesseract

Reading license plates, text, and signs

Image captioning and scene classification

Module 9: Capstone Project

Choose from:

Real-time surveillance vision system

Medical image classifier

Smart retail shelf-monitoring tool

Submit working demo, codebase, and final documentation

Tools & Technologies Used:

OpenCV (Python)

TensorFlow / Keras

YOLO / SSD models

Google Colab or Jupyter Notebooks

Target Audience:

Developers and engineers entering AI

Students of data science and ML

Innovators building vision-based applications

Robotics and automation enthusiasts

Global Learning Benefits:

Learn to build AI systems that can interpret images and videos

Apply both classic and modern techniques in real-world projects

Get hands-on experience with OpenCV and deep learning vision tools

Prepare for roles in AI engineering, surveillance tech, and smart automation

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