Embedded vision. An Introduction

581 Pages·2020·4.933 MB·English

by  Vijayalakshmi S.R., Muruganand S

E
MBEDDED
V
ISION
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E
MBEDDED
V
ISION
An Introduction
S. R. Vijayalakshmi, PhD
S. Muruganand, PhD
MERCURY LEARNING AND INFORMATION
Dulles, Virginia
Boston, Massachusetts
New Delhi
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Original title and copyright: Embedded Vision. Copyright ©2019 by
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S. R. Vijayalakshmi and S. Muruganand. Embedded Vision: An Introduction.
ISBN: 978-1-68392-457-9
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Contents
Preface xvii
Chapter 1 Embedded Vision 1
1.1 Introduction to Embedded Vision 1
1.2 Design of an Embedded Vision System 5
Characteristics of Embedded Vision System Boards Versus
Standard Vision System Boards 6
Benefits of Embedded Vision System Boards 7
Processors for Embedded Vision 7
High Performance Embedded CPU 9
Application Specific Standard Product (ASSP) in
Combination with a CPU 10
General Purpose Cpus 10
Graphics Processing Units with CPU 10
Digital Signal Processors with Accelerator(s) and a CPU 11
Field Programmable Gate Arrays (FPGAs) with a CPU 12
Mobile “Application Processor” 13
Cameras/Image Sensors for Embedded Vision 14
Other Semiconductor Devices for Embedded Vision 15
Memory 15
Networking and Bus Interfaces 16
1.3 Components in a Typical Vision System 16
Vision Processing Algorithms 17
Embedded Vision Challenges 18
1.4 Applications for Embedded Vision 19
Swimming Pool Safety System 20
Object Detection 20
Video Surveillance 21
Gesture Recognition 21
Simultaneous Localization and Mapping (SLAM) 21
Automatic Driver Assistance System (ADAS) 21
Game Controller 22
Face Recognition for Advertising Research 23
Mobile Phone Skin Cancer Detection 23
Gesture Recognition for Car Safety 23
Industrial Applications for Embedded Vision 23
vi • CONTENTS
Medical Applications for Embedded Vision 25
Automotive Applications for Embedded Vision 26
Security Applications for Embedded Vision 26
Consumer Applications for Embedded Vision 27
Machine Learning in Embedded Vision Applications 28
1.5 Industrial Automation and Embedded Vision: A Powerful
Combination 28
Inventory Tracking 29
Automated Assembly 30
Automated Inspection 31
Workplace Safety 32
Depth Sensing 33
1.6 Development Tools for Embedded Vision 34
Both General Purpose and Vendor Specific Tools 35
Personal Computers 35
OpenCV 36
Heterogeneous Software Development in an
Integrated Development Environment 36
Summary 36
Reference 37
Learning Outcomes 37
Further Reading 37
Chapter 2 Industrial Vision 39
2.1 Introduction to Industrial Vision Systems 40
PC-Based Vision Systems 46
Industrial Cameras 46
High-Speed Industrial Cameras 47
Smart Cameras 48
2.2 Classification of Industrial Vision Applications 48
Dimensional Quality 49
Surface Quality 53
Structural Quality 55
Operational Quality 56
2.3 3D Industrial Vision 56
Automated Inspection 57
Robotic Guidance 58
3D Imaging 59
3D Imaging Methods 59
3D Inspection 61
CONTENTS • vii
3D Processing 63
3D Robot Vision 63
High-Speed Imaging 64
High-Speed Cameras 65
Line Scan Imaging 66
Capture and Storage 67
High-Speed Inspection for Product Defects 68
Labels and Marking 68
Web Inspection 69
High-Speed Troubleshooting 69
Line Scan Technology 70
Contact Image Sensors 72
Lenses 73
Image Processing 74
Line Scan Inspection 74
Tracking and Traceability 76
Serialization 77
Direct Part Marking 77
Product Conformity 78
Systems Integration Challenges 80
2.4 Industrial Vision Measurement 81
Character Recognition, Code Reading, and Verification 83
Making Measurements 84
Pattern Matching 85
3D Pattern Matching 86
Preparing for Measurement 86
Industrial Control 87
Development Approaches and Environments 88
Development Software Tools for Industrial Vision Systems 89
Image Processing and Analysis Tools 90
Summary 91
References 92
Learning Outcomes 92
Further Reading 92
Chapter 3 Medical Vision 93
3.1 Introduction to Medical Vision 94
Advantages of Digital Processing for Medical Applications 95
Digital Image Processing Requirements for Medical Applications 96
Advanced Digital Image Processing Techniques in Medical Vision 96
Image Processing Systems for Medical Applications 97
Stereoscopic Endoscope 98
viii • CONTENTS
3.2 From Images to Information in Medical Vision 109
Magnifying Minute Variations 116
Gesture and Security Enhancements 116
3.3 Mathematics, Algorithms in Medical Imaging 117
Artificial Intelligence (AI) 117
Computer-Aided Diagnostic Processing 120
Vision Algorithms for Biomedical 123
Real-Time Radiography 123
Image Compression Technique for Telemedicine 127
Region of Interest 128
Structure Sensitive Adaptive Contrast Enhancement Methods 129
LSPIHT Algorithm for ECG Data Compression and Transmission 130
Retrieval of Medical Images in a PACs 130
Digital Signature Realization Process of DICOM Medical Images 131
Computer Neural Networks (CNNs) in Medical Image Analysis 132
Deep Learning and Big Data 133
3.4 Machine Learning in Medical Image Analysis 135
Convolutional Neural Networks 135
Convolution Layer 136
Rectified Linear Unit (RELU) Layer 137
Pooling Layer 137
Fully Connected Layer 137
Feature Computation 143
Feature Selection 143
Training and Testing: The Learning Process 143
Example of Machine Learning with Use of Cross Validation 144
Summary 145
References 146
Learning Outcomes 146
Further Reading 147
Chapter 4 Video Analytics 149
4.1 Definition of Video Analytics 149
Applications of Video Analytics 151
Image Analysis Software 153
Security Center Integration 156
Video Analytics for Perimeter Detection 157
Video Analytics for People Counting 157
Traffic Monitoring 158
Auto Tracking Cameras for Facial Recognition 158
Left Object Detection 158
CONTENTS • ix
4.2 Video Analytics Algorithms 160
Algorithm Example: Lens Distortion Correction 161
Dense Optical Flow Algorithm 162
Camera Performance Affecting Video Analytics 163
Video Imaging Techniques 167
4.3 Machine Learning in Embedded Vision Applications 168
Types of Machine-Learning Algorithms 170
Implementing Embedded Vision and Machine Learning 177
Embedded Computers Make Inroads to Vision Applications 179
4.4 Examples for Machine Learning 180
1. Convolutional Neural Networks for Autonomous Cars 180
2. CNN Technology Enablers 186
3. Smart Fashion AI Architecture 188
4. Teaching Computers to Recognize Cats 190
Summary 194
References 194
Learning Outcomes 195
Further Reading 195
Chapter 5 Digital Image Processing 197
5.1 Image Processing Concepts for Vision Systems 198
Image 198
Signal 199
Systems 199
5.2 Image Manipulations 203
Image Sharpening and Restoration 203
Histograms 203
Transformation 205
Edge Detection 213
Vertical Direction 214
Horizontal Direction 214
Sobel Operator 215
Robinson Compass Mask 217
Kirsch Compass Mask 219
Laplacian Operator 221
Positive Laplacian Operator 222
Negative Laplacian Operator 222
5.3 Analyzing an Image 223
Color Spaces 232
JPEG Compression 234