arduino 机器视觉编程_Arduino机器视觉学习资料.pdf

【实例简介】Arduino Computer Vision Programming.pdf

【实例截图】

【核心代码】

Table of Contents

Preface v

Chapter 1: General Overview of Computer Vision Systems 1

Introducing computer vision systems 1

Approaching computer vision problems 2

Data acquisition 3

Preprocessing 5

Feature extraction by image processing 6

Post-processing and post-filtering 8

Recognition or detection 8

Acting in the real world 9

Connecting the pieces 10

Summary 11

Chapter 2: Fundamentals and Installation of OpenCV 13

Fundamentals of OpenCV 13

The installation of OpenCV 14

Installing OpenCV on Linux 15

Installing and configuring packages 15

Using OpenCV with Eclipse CDT 16

Installing OpenCV on Mac OS 20

Getting command-line tools 20

Installing HomeBrew 20

Using OpenCV in Xcode 21

Installing OpenCV on Windows 21

Installing MS Visual Studio 2013 22

OpenCV on iOS 24

OpenCV on Android 25

Installing OpenCV4Android 25

Eclipse integration 25

Running samples 27

Summary 28

Table of Contents

[ ii ]

Chapter 3: Data Acquisition with OpenCV and Arduino 29

Image and video acquisition 29

Camera selection 30

Resolution 30

Color capabilities 32

Frame rate 32

2D or 3D 33

Communication interface 33

Image acquisition 34

Reading a static image 34

Taking a snapshot from a webcam 37

Getting a video stream from the webcam 38

Interaction with Kinect 40

Integration of Kinect with OpenCV 40

Sensor data acquisition 47

Setting up an Arduino environment 47

Fundamentals of sensors 48

Sensor types 48

Sampling theorem 49

Dealing with noise 50

Reading data from the temperature sensor 50

Summary 54

Chapter 4: Filtering Data with OpenCV 55

Getting started with filtering 55

2D convolution 56

Spatial domain filtering 56

Smoothing 57

Sharpening 58

Color conversions 59

Grayscale 60

Binary 61

Constant thresholding 62

Adaptive thresholding 63

Morphological filters 64

Erosion and dilation 64

Erosion 64

Dilation 65

Opening and closing 66

Closing 66

Opening 66

Gradients and edge detection 67

The Canny edge detector 67

Laplacian of Gaussian filter 69

Sobel 71

Table of Contents

[ iii ]

Custom filtering 72

Histogram equalization 75

Chapter project 76

Summary 84

Chapter 5: Processing Vision Data with OpenCV 85

Extracting features 85

Using basic statistics 86

Using color features 90

Using template matching features 91

Using contours 91

Using the convex hull 93

Using moments 94

Using the Hough transform 95

Using corners 96

Using SIFT 97

Using SURF 99

Using ORB 99

Using blob analysis 100

Summary 100

Chapter 6: Recognition with OpenCV 101

Building applications which can think 101

Template matching 103

Feature matching 105

FLANN-based matching 109

Using cascade classifiers 110

Using support vector machines 111

Summary 114

Chapter 7: Communicating with Arduino Using OpenCV 115

Communicating with Arduino 115

Wired communications 117

Communicating via USB 117

Communicating via the serial port 124

Communicating via Ethernet 127

Wireless communications 128

Communicating via Bluetooth Low Energy 128

Communicating via ZigBee 130

Communicating via Wi-Fi 130

Communicating via radio frequency 131

Communicating with Java 132

Communicating with C 138

Summary 139

Table of Contents

[ iv ]

Chapter 8: Acting in the Real World with Arduino 141

Interfacing electric motors 141

Driving DC motors 142

Driving stepper motors 145

Driving servo motors 148

Using display screens 151

Using LCD screens 152

Using TFT screens 154

Summary 158

Chapter 9: Building a "Click-to-Go" Robot 159

System overview 159

Building a robot 163

Building mechanics 164

Building the electronics 165

Robot/receiver and transmitter drawings 166

Building the robot controller and communications 168

Building the vision application 177

Building a vision controller and communications 178

Summary 188

Index 189