OpenCV 3 by Example
Open CV is a cross-platform, free-for-use library that is primarily used for real-time Computer Vision and image processing. It is considered to be one of the best open source libraries that helps developers focus on constructing complete projects on image processing, motion detection, and image segmentation.Whether you are completely new to the concept of Computer Vision or have a basic understanding of it, this video will be your guide to understanding the basic OpenCV concepts and algorithms through amazing real-world examples and projects.
More
Starting from the installation of OpenCV on your system and understanding the basics of image processing, we swiftly move on to creating optical flow video analysis or text recognition in complex scenes, and will take you through the commonly-used Computer Vision techniques to build your own Open CV projects from scratch.By the end of this video, you will be familiar with the basics of Open CV such as matrix operations, filters, and histograms, as well as more advanced concepts such as segmentation, machine learning, complex video analysis, and text recognition
Style and Approach
This video is a practical tutorial with lots of tips, and is closely focused on developing Computer vision applications with OpenCV. Beginning with the fundamentals, the complexity increases with each chapter. Sample applications are developed throughout the course that you can execute and use in your own projects.
What you'll learn:
- Install OpenCV 3 on your operating system
- Create the required CMake scripts to compile the C++ application and manage its dependencies
- Get to grips with the Computer Vision workflows and understand the basic image matrix format and filters
- Understand the segmentation and feature extraction techniques
- Remove backgrounds from a static scene to identify moving objects for video surveillance
- Track different objects in a live video using various techniques
- Use the new OpenCV functions for text detection and recognition with Tesseract
Watch Online OpenCV 3 by Example
| # | Title | Duration |
|---|---|---|
| 1 | The Course Overview | 05:49 |
| 2 | Getting Started with OpenCV | 04:56 |
| 3 | What Can You Do with OpenCV? | 12:09 |
| 4 | Installing OpenCV | 10:17 |
| 5 | Basic CMakeConfiguration and Creating a Library | 04:04 |
| 6 | Managing Dependencies | 03:16 |
| 7 | Making the Script More Complex | 03:42 |
| 8 | Images and Matrices | 02:33 |
| 9 | Reading/Writing Images | 05:07 |
| 10 | Reading Videos and Cameras | 03:09 |
| 11 | Other Basic Object Types | 02:03 |
| 12 | Basic Matrix Operations, Data Persistence, and Storage | 04:39 |
| 13 | The OpenCVUser Interface and a Basic GUI | 05:25 |
| 14 | The Graphical User Interface with QT | 01:49 |
| 15 | Adding Slider and Mouse Events to Our Interfaces | 04:37 |
| 16 | Adding Buttons to a User Interface | 03:56 |
| 17 | OpenGL Support | 04:37 |
| 18 | Generating a CMakeScript File | 01:59 |
| 19 | Creating the Graphical User Interface | 02:25 |
| 20 | Drawing a Histogram | 04:38 |
| 21 | Image Color Equalization | 02:57 |
| 22 | Lomography Effect | 04:18 |
| 23 | The CartoonizeEffect | 04:56 |
| 24 | Isolating Objects in a Scene | 02:22 |
| 25 | Creating an Application for AOI | 01:49 |
| 26 | Preprocessing the Input Image | 09:17 |
| 27 | Segmenting Our Input Image | 11:19 |
| 28 | Introducing Machine Learning Concepts | 07:05 |
| 29 | Computer Vision and the Machine Learning Workflow | 02:46 |
| 30 | Automatic Object Inspection Classification Example | 02:21 |
| 31 | Feature Extraction | 11:25 |
| 32 | Understanding HaarCascades | 04:32 |
| 33 | What Are Integral Images | 02:57 |
| 34 | Overlaying a Facemask in a Live Video | 04:26 |
| 35 | Get Your Sunglasses On | 03:23 |
| 36 | Tracking Your Nose, Mouth, and Ears | 01:32 |
| 37 | Background Subtraction | 04:13 |
| 38 | Frame Differencing | 02:53 |
| 39 | Morphological Image processing | 03:22 |
| 40 | Other Morphological Operators | 04:18 |
| 41 | Tracking Objects of a Specific Color | 03:18 |
| 42 | Building an Interactive Object Tracker | 05:56 |
| 43 | Detecting Points Using the Harris Corner Detector | 03:28 |
| 44 | Shi-Tomasi Corner Detector | 02:24 |
| 45 | Feature-Based Tracking | 08:21 |
| 46 | Introducing Optical Character Recognition | 02:41 |
| 47 | The Preprocessing Step | 10:00 |
| 48 | Installing Tesseract OCR on Your Operating System | 06:22 |
| 49 | Using Tesseract OCR Library | 08:07 |