Image Acquisitionand Proces

Recommendations

Info

Morphology 153 FIGURE 6.17 Danielsson example — wiring diagram. Irregular Object Object with a Section Missing Object with a Hole Image Border FIGURE 6.18 Irregular objects touching the image border. tions could be made to extend these fragments to full objects, not enough information is present to accurately do so. This is why it is often appropriate to ignore any objects that are touching the image border, and perhaps consider them in future acquired frames if the objects are moving. FIGURE 6.19 Border rejection example. The example shown in Figure 6.19 counts and labels the total number of objects that are wholly within the image. This was achieved using IMAQ RejectBorder, which has very few inputs: the source and destination image data spaces and the connectivity (Figure 6.20). 6.4.5 FINDING AND CLASSIFYING CIRCULAR OBJECTS If the image contains circular objects that you want to classify, a very simple VI to use is IMAQ Find Circles. This VI will search for circles in the image and return
154 Image Acquisition Processing with LabVIEW FIGURE 6.20 Find and classify circular objects — wiring diagram. FIGURE 6.21 Find and classify circular objects . all sorts of information about them, including the number of circles detected, and their respective center positions, radii and calculated area (Figure 6.21). IMAQ Find Circles uses a Danielsson distance map to determine the radius of each object and can also separate perceived overlapping circles. This is implemented using the code shown in Figure 6.22, and an example application is shown in Figure 6.23. FIGURE 6.22 Find and classify circular objects — wiring diagram.
Page 3:
IMAGE PROCESSING SERIES Series Edit
Page 6:
Foreword The introduction of LabVIE
Page 9 and 10:
FIGURE 1 Vision 6.1 FIGURE 2 Compan
Page 12 and 13:
Acknowledgments My gratitude goes o
Page 14:
Dedication To Don “old fella” P
Page 18 and 19:
Contents Chapter 1 Image Types and
Page 20 and 21:
Chapter 4 Displaying Images........
Page 22 and 23:
Chapter 7 Image Analysis...........
Page 24 and 25:
1 Image Types and File Management F
Page 26 and 27:
Image Types and File Management 3 F
Page 28 and 29:
Image Types and File Management 5 A
Page 30 and 31:
Image Types and File Management 7 C
Page 32 and 33:
Image Types and File Management 9 p
Page 34 and 35:
Image Types and File Management 11
Page 36 and 37:
Image Types and File Management 13
Page 38 and 39:
2 Setting Up You should never under
Page 40 and 41:
Setting Up 17 FIGURE 2.3 (a) Interl
Page 42 and 43:
Setting Up 19 Linear Aray Light Sou
Page 44 and 45:
Setting Up 21 FIGURE 2.7 National I
Page 46 and 47:
Setting Up 23 2.1.3.2 Control and I
Page 48 and 49:
Setting Up 25 FIGURE 2.11 X-Ray ima
Page 50 and 51:
Setting Up 27 Apple Computer techno
Page 52 and 53:
Setting Up 29 FIGURE 2.17 An inexpe
Page 54 and 55:
Setting Up 31 Although this would b
Page 56 and 57:
Setting Up 33 134 -115 \ Contrast =
Page 58 and 59:
Setting Up 35 resolution printer wi
Page 60 and 61:
Setting Up 37 C A B C Traditional T
Page 62 and 63:
Setting Up 39 Camera Light Source O
Page 64 and 65:
Setting Up 41 Camera Light Source (
Page 66 and 67:
Setting Up 43 FIGURE 2.37 (a) An ob
Page 68:
Setting Up 45 FIGURE 2.41 (a) PCB p
Page 71 and 72:
48 Image Acquisition Processing wit
Page 73 and 74:
Page 75 and 76:
Page 77 and 78:
Page 79 and 80:
Page 81 and 82:
Page 83 and 84:
Page 85 and 86:
Page 87 and 88:
Page 89 and 90:
Page 91 and 92:
Page 93 and 94:
Page 95 and 96:
Page 97 and 98:
Page 99 and 100:
Page 101 and 102:
Page 103 and 104:
Page 105 and 106:
Page 107 and 108:
Page 109 and 110:
Page 111 and 112:
Page 113 and 114:
Page 115 and 116:
Page 117 and 118:
Page 119 and 120:
Page 121 and 122:
Page 123 and 124:
100 Image Acquisition Processing wi
Page 125 and 126: 102 Image Acquisition Processing wi
Page 164 and 165: 6 Morphology When applied to vision
Page 166 and 167: Morphology 143 I Closed { } = Erode
Page 168 and 169: Morphology 145 FIGURE 6.3 Simple mo
Page 170 and 171: Morphology 147 FIGURE 6.5 Custom st
Page 172 and 173: Morphology 149 FIGURE 6.8 Particle
Page 174 and 175: Morphology 151 FIGURE 6.12 Fill hol
Page 178 and 179: Morphology 155 Detected circles wit
Page 180 and 181: Morphology 157 6.5 CASE STUDY: FIND
Page 182 and 183: Morphology 159 6.6 USER SOLUTION: D
Page 184 and 185: Morphology 161 ULTRASOUND MACHINE (
Page 186: Morphology 163 FIGURE 6.31 The Edit
Page 227 and 228:
Page 229 and 230:
Page 231 and 232:
Page 233 and 234:
Page 235 and 236:
Page 237 and 238:
Page 240 and 241:
8 Machine Vision A generally accept
Page 242 and 243:
Machine Vision 219 TABLE 8.1 “IMA
Page 244 and 245:
Machine Vision 221 TABLE 8.3 Input
Page 246 and 247:
Machine Vision 223 packages, includ
Page 248 and 249:
Machine Vision 225 good sense to ad
Page 250 and 251:
Machine Vision 227 TABLE 8.4 “IMA
Page 252 and 253:
Glossary 1-Bit Image An image compr
Page 254 and 255:
Glossary 231 binary display device
Page 256 and 257:
Glossary 233 spatial Þlters, each
Page 258:
Glossary 235 Resolution There are t
Page 261 and 262:
Page 263 and 264:
Page 265 and 266:
Page 267:
show all

Image Acquisitionand Proces

Create successful ePaper yourself

Delete template?

Save as template?