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OpenCV 3 by Example

3h 53m 58s
English
Paid

OpenCV 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, aiding developers in constructing comprehensive projects on image processing, motion detection, and image segmentation. Whether you are completely new to Computer Vision or have a basic understanding of it, this video guide will help you grasp the fundamental OpenCV concepts and algorithms through impressive real-world examples and projects.

Getting Started with OpenCV

Beginning with the installation of OpenCV on your system and a basic understanding of image processing, we quickly transition to creating optical flow video analysis or text recognition in complex scenes. This course will introduce you to commonly-used Computer Vision techniques, empowering you to build your own OpenCV projects from scratch. By the end of this video, you will be familiar with the basics of OpenCV, such as matrix operations, filters, and histograms, as well as more advanced concepts like segmentation, machine learning, complex video analysis, and text recognition.

Course Style and Approach

This video course is a practical tutorial filled with many tips and is closely focused on developing Computer Vision applications with OpenCV. Beginning with the fundamentals, the course gradually increases in complexity with each chapter. Sample applications are developed throughout the course, which you can execute and use in your projects.

What You'll Learn

  • Install OpenCV 3 on your operating system
  • Create the necessary CMake scripts to compile the C++ application and manage its dependencies
  • Familiarize yourself with Computer Vision workflows and understand the basic image matrix format and filters
  • Understand 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
  • Utilize the new OpenCV functions for text detection and recognition with Tesseract

About the Author: packtpub

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Founded in 2004 in Birmingham, UK, Packt's mission is to help the world put software to work in new ways, through the delivery of effective learning and information services to IT professionals. Working towards that vision, we have published over 6,500 books and videos so far, providing IT professionals with the actionable knowledge they need to get the job done - whether that's specific learning on an emerging technology or optimizing key skills in more established tools.

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#1: The Course Overview
All Course Lessons (49)
#Lesson TitleDurationAccess
1
The Course Overview Demo
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
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