The most important structure in computer vision is, without doubt, the images. The image in a computer vision is the representation of the physical world captured with a digital device. This picture is only a sequence of numbers stored in a matrix format (refer to the following diagram). Each number is a measurement of the light intensity for the considered wavelength (for example, red, green, or blue in color images) or for a wavelength range (for panchromatic devices). Every point in an image is called a pixel (for a picture element), and each pixel can store one or more values depending on whether it is a black and white image (also referred to as a binary image) that stores only one value, such as 0 or 1, a grayscale-level image that stores two values, or a color image that stores three values. These values are usually between 0 and 255 in an integer number...
Learn OpenCV 4 By Building Projects - Second Edition
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Learn OpenCV 4 By Building Projects - Second Edition
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Overview of this book
OpenCV is one of the best open source libraries available, and can help you focus on constructing complete projects on image processing, motion detection, and image segmentation. Whether you’re completely new to computer vision, or have a basic understanding of its concepts, Learn OpenCV 4 by Building Projects – Second edition will be your guide to understanding OpenCV concepts and algorithms through real-world examples and projects.
You’ll begin with the installation of OpenCV and the basics of image processing. Then, you’ll cover user interfaces and get deeper into image processing. As you progress through the book, you'll learn complex computer vision algorithms and explore machine learning and face detection. The book then guides you in creating optical flow video analysis and background subtraction in complex scenes. In the concluding chapters, you'll also learn about text segmentation and recognition and understand the basics of the new and improved deep learning module.
By the end of this book, you'll be familiar with the basics of Open CV, such as matrix operations, filters, and histograms, and you'll have mastered commonly used computer vision techniques to build OpenCV projects from scratch.
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Current Title:
Learn OpenCV 4 By Building Projects - Second Edition
Table of Contents (14 chapters)
Preface
Free Chapter
Getting Started with OpenCV
An Introduction to the Basics of OpenCV
Learning Graphical User Interfaces
Delving into Histogram and Filters
Automated Optical Inspection, Object Segmentation, and Detection
Learning Object Classification
Detecting Face Parts and Overlaying Masks
Video Surveillance, Background Modeling, and Morphological Operations
Learning Object Tracking
Developing Segmentation Algorithms for Text Recognition
Text Recognition with Tesseract
Deep Learning with OpenCV
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