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Development Programming Languages Image Processing

Learning Path: OpenCV: Master Image Processing with OpenCV 3

Develop interactive computer vision applications with the popular C++ libraries of OpenCV 3
Rating: 3.1 out of 53.1 (71 ratings)
568 students
Created by Packt Publishing
Last updated 10/2017
English
English [Auto]
30-Day Money-Back Guarantee

What you'll learn

  • Scan an image with pointers and neighbor access
  • Represent colors with hue, saturation, and brightness
  • Retrieve similar images using the histogram comparison
  • Calibrate the camera from different image observations
  • Detect people and objects in images using machine learning techniques
  • Reconstruct a 3D scene from images
  • Add the miniaturizing tilt-shift effect
  • Load videos and store them

Course content

3 sections • 58 lectures • 5h 18m total length

  • Preview03:02
  • Installing the OpenCV Library
    11:52
  • Loading, Displaying, and Saving Images
    11:35
  • Exploring the cv::Mat Data Structure
    08:28
  • Defining Regions of Interest
    04:40
  • Preview05:48
  • Scanning an Image with Pointers
    09:25
  • Scanning an Image with Iterators
    04:52
  • Writing Efficient Image-Scanning Loops
    03:41
  • Scanning an Image with Neighbor Access
    05:21
  • Performing Simple Image Arithmetic
    04:46
  • Remapping an Image
    03:05
  • Comparing Colors Using the Strategy Design Pattern
    16:03
  • Segmenting an Image with the GrabCut Algorithm
    05:50
  • Converting Color Representations
    05:18
  • Representing Colors with Hue, Saturation, and Brightness
    09:56
  • Computing an Image Histogram
    08:16
  • Applying Look-Up Tables to Modify the Image's Appearance
    04:54
  • Equalizing the Image Histogram
    03:24
  • Backprojecting a Histogram to Detect Specific Image Content
    05:12
  • Using the Mean Shift Algorithm to Find an Object
    05:14
  • Retrieving Similar Images Using Histogram Comparison
    04:07
  • Counting Pixels with Integral Images
    12:21
  • OpenCV 3 - Getting started with Image processing
    5 questions

  • Preview02:07
  • Detecting Corners in an Image
    09:04
  • Detecting Features Quickly
    04:39
  • Detecting Scale-Invariant Features
    06:20
  • Detecting FAST Features at Multiple Scales
    03:04
  • Matching Local Templates
    07:22
  • Describing and Matching Local Intensity Patterns
    08:57
  • Matching Keypoints with Binary Descriptors
    05:01
  • Computing the Fundamental Matrix of an Image Pair
    05:14
  • Matching Images Using Random Sample Consensus
    08:32
  • Computing a Homography Between Two Images
    04:28
  • Detecting a Planar Target in Images
    05:12
  • Recognizing Faces Using Nearest Neighbors
    05:15
  • Finding Objects and Faces with a Cascade of Haar Features
    05:08
  • Detecting Objects and People with Support Vector Machines
    10:13
  • OpenCV 3 - Advanced Image Detection and Reconstruction
    5 questions

  • Preview02:30
  • Building OpenCV
    07:27
  • Creating a New Project
    03:21
  • Loading Images
    03:17
  • Showing Images
    01:33
  • Keyboard Events
    02:35
  • Understanding Brightness and Contrast
    03:40
  • Adjusting Brightness and Contrast with OpenCV
    02:41
  • Interactive Image Adjustment
    10:14
  • Storing Images
    02:00
  • Miniature Faking
    02:27
  • Blurring Images
    04:35
  • Compositing Images
    02:12
  • The Miniature Effect via Partial Blurring
    01:41
  • Handling Mouse Events
    03:07
  • Color Filters
    02:30
  • Remapping Colors
    01:36
  • Processing Video
    02:12
  • Recoloring Video
    01:34
  • Saving Video
    09:13
  • OpenCV 3 Projects for Photo Filtering
    5 questions

Requirements

  • Basic programming knowledge on C++ is needed.

Description

OpenCV 3 is a native cross-platform C++ Library for computer vision, machine learning, and image processing. Computer vision applications are the latest buzz of recent time! Big brands such as Microsoft, Apple, Google, Facebook, and Apple are increasingly making use of computer vision for object, pattern, image, and face recognition. This has led to a very high demand for computer vision expertise. So, if you're interested to know how to use the OpenCV library to build computer vision applications, then go for this Learning Path.

Packt’s Video Learning Paths are a series of individual video products put together in a logical and stepwise manner such that each video builds on the skills learned in the video before it.

The highlights of this Learning Path are:

  • Dive into the essentials of OpenCV and build your own projects
  • Learn how to apply complex visual effects to images
  • Reconstruct a 3D scene from images
  • Master the fundamental concepts in computer vision and image processing

Let’s take a quick look at your learning journey. This Learning Path helps you to get started with the OpenCV library and shows you how to install and deploy it to write effective computer vision applications following good programming practices. You will learn how to read and display images. You will then be introduced to the basic OpenCV data structures.

Further, you will start a new project and see how to load an image file and show it. Next, you'll find out how to handle keyboard events in our display window. In the next project, you will jump into interactively adjusting image brightness. You will then learn to add a miniaturizing tilt-shift effect and how to blur images. In the final project, you will learn to apply Instagram-like color ambiance filters to images.

By the end of this Learning Path, you will be able to build computer vision applications that make the most of OpenCV 3.

Meet Your Experts:

We have combined the best works of the following esteemed authors to ensure that your learning journey is smooth:

  • Robert Laganiere is a professor at the School of Electrical Engineering and Computer Science of the University of Ottawa, Canada. He is also a faculty member of the VIVA research lab and is the co-author of several scientific publications and patents in content-based video analysis, visual surveillance, driver-assistance, object detection, and tracking. Robert authored the OpenCV2 Computer Vision Application Programming Cookbook in 2011 and co-authored Object Oriented Software Development, published by McGraw Hill in 2001. He is also a consultant in computer vision and has assumed the role of Chief Scientist in a number of startups companies such as Cognivue Corp, iWatchlife, and Tempo Analytics.
  • AdiShavit is an experienced software architect and has been an OpenCV user since it was in early beta back in 2000. Since then he has been using it pretty much continuously to build systems and products ranging from embedded, vehicle, and mobile apps to desktops and large, distributed cloud-based servers and services. His specialty is in computer vision, image processing, and machine learning with an emphasis on real-time applications. He specializes in cross-platform, high performance software combined with a high production-quality maintainable code base. He builds many products, apps, and services that leverage OpenCV.

Who this course is for:

  • This learning path is appropriate for novice C++ programmers who want to learn how to use the OpenCV library to build computer vision applications. It is also suitable for professional software developers who wish to be introduced to the concepts of computer vision programming.

Instructor

Packt Publishing
Tech Knowledge in Motion
Packt Publishing
  • 3.9 Instructor Rating
  • 59,015 Reviews
  • 354,116 Students
  • 1,418 Courses

Packt has been committed to developer learning since 2004. A lot has changed in software since then - but Packt has remained responsive to these changes, continuing to look forward at the trends and tools defining the way we work and live. And how to put them to work.

With an extensive library of content - more than 4000 books and video courses -Packt's mission is to help developers stay relevant in a rapidly changing world. From new web frameworks and programming languages, to cutting edge data analytics, and DevOps, Packt takes software professionals in every field to what's important to them now.

From skills that will help you to develop and future proof your career to immediate solutions to every day tech challenges, Packt is a go-to resource to make you a better, smarter developer.

Packt Udemy courses continue this tradition, bringing you comprehensive yet concise video courses straight from the experts.



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