OpenCV 3 - Getting started with Image processing [Video]

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OpenCV 3 - Getting started with Image processing [Video]

Robert Laganiere

Videos to help you build computer vision applications that make the most of the popular C++ library OpenCV 3
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Video Details

ISBN 139781788292368
Course Length2 hours and 37 minutes

Video Description

Making your applications see has never been easier with OpenCV. With it, you can teach your robot how to follow your cat, write a program to correctly identify the members of One Direction, or even help you find the right colors for your redecoration. This course provides a complete introduction to the OpenCV library and explains how to build your first computer vision program. You will be presented with a variety of computer vision algorithms and exposed to important concepts in image analysis that will enable you to build your own computer vision applications.

This video helps you to get started with the library, and shows you how to install and deploy the OpenCV library to write effective computer vision applications following good programming practices. You will learn how to read and display images. It also introduces the basic OpenCV data structures.

Moving on, you will see how to manipulate pixels, and how an image can be read. This section explores different methods to scan an image in order to perform an operation on each of its pixels.

After that, you will find out how to process the colors of an image, where you’ll be presented with various object-oriented design patterns that will help you to build better computer vision applications. This section also shows you the concept of colors in images.

Finally, you’ll discover how to count pixels with histograms, how to compute image histograms, and how they can be used to modify an image. This section presents different applications based on histograms so you can achieve image segmentation, object detection, and image retrieval.

Style and Approach

This course follows a problem-solution approach to the image processing tasks you’ll come across every day while working with OpenCV.

Table of Contents

Playing with Images
The Course Overview
Installing the OpenCV Library
Loading, Displaying, and Saving Images
Exploring the cv::Mat Data Structure
Defining Regions of Interest
Manipulating Pixels
Accessing Pixel Values
Scanning an Image with Pointers
Scanning an Image with Iterators
Writing Efficient Image-Scanning Loops
Scanning an Image with Neighbor Access
Performing Simple Image Arithmetic
Remapping an Image
Processing the Colors of an Image
Comparing Colors Using the Strategy Design Pattern
Segmenting an Image with the GrabCut Algorithm
Converting Color Representations
Representing Colors with Hue, Saturation, and Brightness
Counting the Pixels with Histograms
Computing an Image Histogram
Applying Look-Up Tables to Modify the Image's Appearance
Equalizing the Image Histogram
Backprojecting a Histogram to Detect Specific Image Content
Using the Mean Shift Algorithm to Find an Object
Retrieving Similar Images Using Histogram Comparison
Counting Pixels with Integral Images

What You Will Learn

  • Install OpenCV library
  • Access pixel values
  • Scan an image with pointers and neighbor access
  • Compare colors using the strategy design pattern
  • Segment an image with the GrabCut algorithm
  • Represent colors with hue, saturation, and brightness
  • Compute and Equalize image histogram
  • Retrieve similar images using the histogram comparison

Authors

Table of Contents

Playing with Images
The Course Overview
Installing the OpenCV Library
Loading, Displaying, and Saving Images
Exploring the cv::Mat Data Structure
Defining Regions of Interest
Manipulating Pixels
Accessing Pixel Values
Scanning an Image with Pointers
Scanning an Image with Iterators
Writing Efficient Image-Scanning Loops
Scanning an Image with Neighbor Access
Performing Simple Image Arithmetic
Remapping an Image
Processing the Colors of an Image
Comparing Colors Using the Strategy Design Pattern
Segmenting an Image with the GrabCut Algorithm
Converting Color Representations
Representing Colors with Hue, Saturation, and Brightness
Counting the Pixels with Histograms
Computing an Image Histogram
Applying Look-Up Tables to Modify the Image's Appearance
Equalizing the Image Histogram
Backprojecting a Histogram to Detect Specific Image Content
Using the Mean Shift Algorithm to Find an Object
Retrieving Similar Images Using Histogram Comparison
Counting Pixels with Integral Images

Video Details

ISBN 139781788292368
Course Length2 hours and 37 minutes
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