Explains the theory behind basic computer vision and provides
a bridge from the theory to practical implementation using the
industry standard OpenCV libraries

Computer Vision is a rapidly expanding area and it is becoming
progressively easier for developers to make use of this field due
to the ready availability of high quality libraries (such as OpenCV
2). This text is intended to facilitate the practical use of
computer vision with the goal being to bridge the gap between the
theory and the practical implementation of computer vision. The
book will explain how to use the relevant OpenCV library routines
and will be accompanied by a full working program including the
code snippets from the text. This textbook is a heavily
illustrated, practical introduction to an exciting field, the
applications of which are becoming almost ubiquitous. We are
now surrounded by cameras, for example cameras on computers &
tablets/ cameras built into our mobile phones/ cameras
in games consoles; cameras imaging difficult modalities (such as
ultrasound, X-ray, MRI) in hospitals, and surveillance cameras.
This book is concerned with helping the next generation of computer
developers to make use of all these images in order to develop
systems which are more intuitive and interact with us in more
intelligent ways.

* Explains the theory behind basic computer vision and provides a
bridge from the theory to practical implementation using the
industry standard OpenCV libraries

* Offers an introduction to computer vision, with enough theory
to make clear how the various algorithms work but with an emphasis
on practical programming issues

* Provides enough material for a one semester course in computer
vision at senior undergraduate and Masters levels

* Includes the basics of cameras and images and image processing
to remove noise, before moving on to topics such as image
histogramming; binary imaging; video processing to detect and model
moving objects; geometric operations & camera models; edge
detection; features detection; recognition in images

* Contains a large number of vision application problems to
provide students with the opportunity to solve real problems.
Images or videos for these problems are provided in the resources
associated with this book which include an enhanced eBook

Kenneth Dawson-Howe, School of Computer Science and Statistics, Trinity College Dublin, Ireland
Dr. Dawson-Howe is a Lecturer in the School of Computer Science and Statistics and part of the Graphics, Vision and Visualisation (GV2) Research Group at Trinity College Dublin. He currently teaches the course Computer Vision/Vision Systems to final year undergraduate and Masters students. He has been teaching courses in the area of computer vision for over 20 years. He is co-author of the Dictionary of Computer Vision & Image Processing published by Wiley in 2005 (2^nd Edition to publish December 2013).

Computer Vision is a rapidly expanding area and it is becoming progressively easier for developers to make use of this field due to the ready availability of high quality libraries such as OpenCV3. This book discusses the theory behind basic computer vision and provides a bridge from the theory to practical implementation using the industry standard OpenCV libraries. It explains how to use the relevant OpenCV library routines and is accompanied by a full working program including the code snippets from the text. It is a heavily illustrated, practical introduction to an exciting field, the applications of which are becoming ubiquitous.

Key features:

• Offers an introduction to computer vision, with enough theory to make clear how the various
  algorithms work but with an emphasis on practical programming issues.
• Explains the basics of cameras and images and image processing to remove noise, before moving on to topics such as image histogramming; binary imaging; video processing to detect and model moving objects; geometric operations & camera models; edge detection; feature detection; and recognition in images.
• Contains a large number of vision application problems to provide students with the opportunity to solve real problems.
• Includes a companion website hosting images and code from the book, as well as application problem videos and images which allow students to attempt to solve the problems presented in the book.

Explains the theory behind basic computer vision and provides a bridge from the theory to practical implementation using the industry standard OpenCV libraries

Computer Vision is a rapidly expanding area and it is becoming progressively easier for developers to make use of this field due to the ready availability of high quality libraries (such as OpenCV 2). This text is intended to facilitate the practical use of computer vision with the goal being to bridge the gap between the theory and the practical implementation of computer vision. The book will explain how to use the relevant OpenCV library routines and will be accompanied by a full working program including the code snippets from the text. This textbook is a heavily illustrated, practical introduction to an exciting field, the applications of which are becoming almost ubiquitous. We are now surrounded by cameras, for example cameras on computers & tablets/ cameras built into our mobile phones/ cameras in games consoles; cameras imaging difficult modalities (such as ultrasound, X-ray, MRI) in hospitals, and surveillance cameras. This book is concerned with helping the next generation of computer developers to make use of all these images in order to develop systems which are more intuitive and interact with us in more intelligent ways.

• Explains the theory behind basic computer vision and provides a bridge from the theory to practical implementation using the industry standard OpenCV libraries
• Offers an introduction to computer vision, with enough theory to make clear how the various algorithms work but with an emphasis on practical programming issues
• Provides enough material for a one semester course in computer vision at senior undergraduate and Masters levels
• Includes the basics of cameras and images and image processing to remove noise, before moving on to topics such as image histogramming; binary imaging; video processing to detect and model moving objects; geometric operations & camera models; edge detection; features detection; recognition in images
• Contains a large number of vision application problems to provide students with the opportunity to solve real problems. Images or videos for these problems are provided in the resources associated with this book which include an enhanced eBook

Preface xiii

1 Introduction 1

1.1 A Difficult Problem 1

1.2 The Human Vision System 2

1.3 Practical Applications of Computer Vision 3

1.4 The Future of Computer Vision 5

1.5 Material in This Textbook 6

1.6 Going Further with Computer Vision 7

2 Images 9

2.1 Cameras 9

2.1.1 The Simple Pinhole Camera Model 9

2.2 Images 10

2.2.1 Sampling 11

2.2.2 Quantisation 11

2.3 Colour Images 13

2.3.1 Red-Green-Blue (RGB) Images 14

2.3.2 Cyan-Magenta-Yellow (CMY) Images 17

2.3.3 YUV Images 17

2.3.4 Hue Luminance Saturation (HLS) Images 18

2.3.5 Other Colour Spaces 20

2.3.6 Some Colour Applications 20

2.4 Noise 22

2.4.1 Types of Noise 23

2.4.2 Noise Models 25

2.4.3 Noise Generation 26

2.4.4 Noise Evaluation 26