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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

Preprocessing the input image


This section introduces you to some of the most common techniques that can be applied to preprocess images in the context of object segmentation/detection. The preprocess is the first change that we make in a new image before we start with our work and extract the information that we require from it.

Normally, in the preprocessing step, we try to minimize the image noise, light conditions, or image deformations due to the camera lens. These steps minimize the errors when you try to detect objects or segment our image.

Noise removal

If we don't remove the noise, we can detect more objects than we expect because normally noise is represented as a small point in the image and can be segmented as an object. The sensor and scanner circuit normally produce this noise. This variation of brightness or color can be represented in different types, such as Gaussian noise, spike noise, and shot noise. There are different techniques that can be used to remove the noise. We...

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