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OpenCV By Example

You're reading from   OpenCV By Example Enhance your understanding of Computer Vision and image processing by developing real-world projects in OpenCV 3

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Product type Paperback
Published in Jan 2016
Publisher Packt
ISBN-13 9781785280948
Length 296 pages
Edition 1st Edition
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Authors (3):
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Vinícius G. Mendonça Vinícius G. Mendonça
Author Profile Icon Vinícius G. Mendonça
Vinícius G. Mendonça
David Millán Escrivá David Millán Escrivá
Author Profile Icon David Millán Escrivá
David Millán Escrivá
Prateek Joshi Prateek Joshi
Author Profile Icon Prateek Joshi
Prateek Joshi
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Toc

Table of Contents (13) Chapters Close

Preface 1. Getting Started with OpenCV FREE CHAPTER 2. An Introduction to the Basics of OpenCV 3. Learning the Graphical User Interface and Basic Filtering 4. Delving into Histograms and Filters 5. Automated Optical Inspection, Object Segmentation, and Detection 6. Learning Object Classification 7. Detecting Face Parts and Overlaying Masks 8. Video Surveillance, Background Modeling, and Morphological Operations 9. Learning Object Tracking 10. Developing Segmentation Algorithms for Text Recognition 11. Text Recognition with Tesseract Index

Images and matrices


The most important structure in a Computer Vision is without any doubt the images. The image in Computer Vision is a representation of the physical world captured with a digital device. This picture is only a sequence of numbers stored in a matrix format, as shown in the following image. 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). Each 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 gray, black, or white image (called a binary image as well) that stores only one value, such as 0 or 1, a gray-scale-level image that can store only one value, or a color image that can store three values. These values are usually integer numbers between 0 and 255, but you can use the other range. For example, 0 to 1 in a floating point numbers such as HDRI (High...

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