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Practical
OpenCV is a hands-on project book that shows you how to get the best results
from OpenCV, the open-source computer vision library.

Computer vision is key to technologies like object recognition, shape
detection, and depth estimation. OpenCV is an open-source library with over
2500 algorithms that you can use to do all of these, as well as track
moving objects, extract 3D models, and overlay augmented reality. It´s
used by major companies like Google (in its autonomous car), Intel, and
Sony; and it is the backbone of the Robot Operating System´s computer vision capability.
In short, if you´re working with computer vision at all, you need to know
OpenCV.

With Practical OpenCV , you´ll be able to:

Get OpenCV up and running on Windows
or Linux.
Use OpenCV to control the camera board and
run vision algorithms on Raspberry Pi.
Understand what goes on behind the
scenes in computer vision applications like object detection, image stitching,
filtering, stereo vision, and more.
Code complex computer vision
projects for your class/hobby/robot/job, many of which can execute in real time
on off-the-shelf processors.
Combine different modules that you
develop to create your own interactive computer vision app.

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Part 1: Getting comfortable

Chapter 1: Introduction to Computer Vision and OpenCV

Chapter 2: Setting up OpenCV on your computer

Chapter 3: CV Bling – OpenCV inbuilt demos

Chapter 4: Basic operations on images and GUI windows

Part 2: Advanced computer vision problems and coding them in OpenCV

Chapter 5: Image filtering

Chapter 6: Shapes in images

Chapter 7: Image segmentation and histograms

Chapter 8: Basic machine learning and keypoint-based object detection

Chapter 9: Affine and Perspective transformations and their applications to image panoramas

Chapter 10: 3D geometry and stereo vision

Chapter 11: Embedded computer vision: Running OpenCV programs on the Raspberry Pi

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