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Practical Guide to Machine Vision Software: An Introduction with LabVIEW

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Practical Guide to Machine Vision Software

An Introduction with LabVIEW

By Kye-Si Kwon, Steven Ready

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Format: Paperback, 296 pages
Published In: United States, 01 April 2015
For both students and engineers in R&D, this book explains machine vision in a concise, hands-on way, using the Vision Development Module of the LabView software by National Instruments. Following a short introduction to the basics of machine vision and the technical procedures of image acquisition, the book goes on to guide readers in the use of the various software functions of LabView's machine vision module. It covers typical machine vision tasks, including particle analysis, edge detection, pattern and shape matching, dimension measurements as well as optical character recognition, enabling readers to quickly and efficiently use these functions for their own machine vision applications. A discussion of the concepts involved in programming the Vision Development Module rounds off the book, while example problems and exercises are included for training purposes as well as to further explain the concept of machine vision. With its step-by-step guide and clear structure, this is an essential reference for beginners and experienced researchers alike.

Table of Contents

About the Authors IX Preface XI 1 Basics of Machine Vision 1 1.1 Digital Images 1 1.1.1 Grayscale Image 1 1.1.2 Binary Image 2 1.1.3 Color Image 3 1.2 Components of Imaging System 5 1.2.1 Camera 6 1.2.2 Camera Bus: The Method to Connect PC and Camera 10 1.2.3 Lens 13 1.2.4 Lighting 15 2 Image Acquisition with LabVIEW 17 2.1 Acquiring Images with MAX 17 2.2 Acquiring Images Using LabVIEW 19 2.2.1 IMAQdx Functions 19 2.2.2 Image Management Functions 21 2.2.3 Block Diagram for Image Acquisition 23 2.2.4 Image Acquisition from Example 23 2.2.5 Vision Acquisition Express 26 3 Particle Analysis 33 3.1 Particle Analysis Using Vision Assistant 34 3.1.1 Image Acquisition Using Vision Assistant 35 3.1.2 Image Processing Functions 37 3.1.3 Setting a ROI (Region of Interest) 38 3.1.4 Binary Image Conversion 40 3.1.5 Morphology 43 3.1.6 Particle Analysis 44 3.2 LabVIEW Code Creation Using Vision Assistant 47 3.2.1 Block Diagram of Created LabVIEW Code 50 3.2.2 Image Type Modification 54 3.3 LabVIEW Code Modification 55 3.3.1 SubVI for Particle Analysis 55 3.4 Particle Analysis Using Vision Express 67 3.4.1 Vision Acquisition Express 67 3.4.2 Vision Assistant Express 68 3.5 Conversion of Pixels to Real-World Units 71 4 Edge Detection 75 4.1 Edge Detection via Vision Assistant 75 4.2 LabVIEW Code for Edge Detection 78 4.3 VI for Real-Time-Based Edge Detection 81 4.4 The Use of Vision Assistant Express for Real-Time Edge Detection 85 5 Pattern Matching 89 5.1 Pattern Matching Using Vision Assistant 90 5.2 LabVIEW Code Creation and Modification 96 5.3 Main VI for Pattern Matching 99 5.4 Vision Assistant Express 101 6 Color Pattern Matching 105 6.1 Color Pattern Matching Using Vision Assistant Express 105 6.1.1 Vision Acquisition Express 107 6.1.2 Vision Assistant Express 108 6.1.3 Main VI 112 7 Dimension Measurement 117 7.1 Dimension Measurement Using Vision Assistant Express 117 7.1.1 Find Circular Edge Function 119 7.1.2 Clamp Function 119 7.1.3 Caliper Function 123 7.2 VI Creation for Dimension Measurement 126 7.2.1 Vision Assistant Express VI for Dimension Measurement 126 7.2.2 ROI Array 127 7.2.3 Front Panel of Main VI 129 7.2.4 Block Diagram of the Main VI 130 8 Dimension Measurement Using Coordinate System 135 8.1 Measurement Based on a Reference Coordinate System Using Vision Assistant Express 135 8.1.1 Pattern Matching 137 8.1.2 Coordinate System 138 8.1.3 Dimension Measurement Using the Clamp Function 141 8.1.4 Measurement of Circle Edge 142 8.2 Conversion of Vision Assistant Express to a Standard VI 145 9 Geometric Matching 149 9.1 Geometric Matching Using Vision Assistant Express 150 9.1.1 Geometric Matching for Circles 151 9.1.2 Geometric Matching for Ellipses 155 9.2 VI Creation for Geometric Matching 158 9.3 Shape Detection 159 10 Binary Shape Matching 165 10.1 Accessing Previously Saved Images with Vision Acquisition Express 166 10.2 Binary Shape Matching Using Vision Assistant 168 10.2.1 Binary Template Images 169 10.2.2 Binary Shape Matching 170 10.3 Overlay VI Creation for Shape Matching 172 10.4 VI for Binary Shape Matching 173 11 OCR (Optical Character Recognition) 177 11.1 OCR Using Vision Assistant 177 11.1.1 Character Training Using Vision Assistant 177 11.1.2 Character Identification Using Vision Assistant 181 11.2 VI for OCR 185 11.2.1 VI Creation for OCR Using Vision Assistant 185 11.2.2 SubVI for OCR 185 11.2.3 Main VI 187 12 Binary Particle Classification 191 12.1 Vision Acquisition Express to Load Image Files 192 12.2 Vision Assistant Express for Classification 194 12.2.1 Train for Particle Classification 194 12.2.2 VI Creation 199 12.3 VI Modification 200 12.4 Overlay for Classification 204 12.5 Main VI for Classification 206 13 Contour Analysis 209 13.1 Contour Analysis 210 13.1.1 Image Acquisition Using a USB Camera 210 13.1.2 Contour Analysis Using Vision Assistant 212 13.1.3 Defect Detection Using Curvature 215 13.1.4 Defect Detection by Comparing Contours 216 13.1.5 VI Creation 219 13.2 VIs for Contour Analysis 219 13.2.1 Main VI 219 13.2.2 Overlay for Defects 222 13.2.3 Perspective Errors in Images 225 14 Image Calibration and Correction 227 14.1 Method for Creating an Image Correction File 227 14.1.1 Image Acquisition 228 14.1.2 New Calibration File 228 14.2 Image Correction 234 14.2.1 Image Correction Using Vision Assistant Express 234 14.2.2 VI Creation for Image Correction 237 15 Saving and Reading Images 241 15.1 Saving Image 241 15.2 Image Read from File 245 15.2.1 IMAQ Readfile 245 15.2.2 Example of Reading Image from Image Files 246 16 AVI File Write and Read 249 16.1 AVI File Creation Using Image Files 249 16.2 AVI File Creation Based on Real-Time Image Acquisition 251 16.3 Read Frame from AVI Files 252 17 Tracking 255 17.1 Tracking with the Use of Vision Assistant 255 17.2 VI Creation for Tracking Objects 259 18 LabVIEW Machine Vision Applicationsâ 263 18.1 Semiconductor Manufacturing 263 18.2 Automobile Industry 264 18.3 Medical and Bio Applications 266 18.4 Inspection 268 18.5 Industrial Printing 269 19 Student Projects 271 Project 1: Noncontact Motion Measurement and its Analysis 271 Project 2: Intelligent Surveillance Camera 271 Project 3: Driving a LEGO NXT Car (LEGO Mindstorm) with Finger Motion 273 Project 4: Piano Keyboard Using Machine Vision 273 Index 275

About the Author

Kye-Si Kwon is an associate professor at Soonchunhyang Universityin Korea in the department of mechanical engineering. After hisPhD, obtained from KAIST, Korea, in 1999, he was a member ofresearch staffs in companies such as Samsung and LG electronics. Hejoined Soonchunhyang University in 2006 where his teaching andresearch is centered on inkjet-related measurement methods andsystem developments. In 2012, he spent one year at Palo AltoResearch Center (PARC) in Palo Alto, California, as a visitingresearcher. He also established a start-up company and is CEO ofPS. Co. Ltd (www.psolution.kr). Steven Ready joined the Palo Alto Research Center more than twodecades ago, where he designed and developed several high-accuracyinkjet printers for printed organic electronics and documents;studied the role of hydrogen in amorphous, polycrystalline, andcrystalline silicon and associated applications; and contributed tothe development of large-area amorphous and polycrystalline siliconarrays for optical and x-ray imaging, displays, and organicsemiconductor materials and devices. Steven Ready has also madesignificant contributions to developing laser crystallization ofsilicon thin films; a fragile book scanner; control software forMOCVD reactors; and a scanning tunneling microscope. He is a memberof the SPIE, MRS, and IS&T professional societies. He obtainedhis degree in Physics from the University of California at SantaCruz.

EAN: 9783527337569
ISBN: 3527337563
Publisher: Wiley-Vch
Dimensions: 24.13 x 17.02 x 1.52 centimetres (0.65 kg)
Age Range: 15+ years
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