Image Acquisitionand Proces

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Morphology 149 FIGURE 6.8 Particle removal. TABLE 6.2 Selection Values Cluster Example Cluster Item Value Description Parameter Area (pixels) Particle removal is based on the pixel area of detected particles (a calibrated area routine is also available) Lower value 0.00 Upper value 3000.00 Interval Include Process the routine using the values between and including the lower (zero pixels area) and upper (3000 pixels area) values FIGURE 6.9 Particle removal — wiring diagram.
150 Image Acquisition Processing with LabVIEW FIGURE 6.10 IMAQ basic particle basic reports. Source Image Global Rectangle Detected Particle FIGURE 6.11 The global rectangle. 6.4.3.2 IMAQ Danielsson Although IMAQ Distance is useful for fast distance contouring, as seen from Figure 6.14, the transform is far from accurate. A much more accurate, yet slower approach is to use IMAQ Danielsson (Figure 6.16). The Danielsson distance map algorithm, which was devised by Erik Danielsson, is based on the Euclidian distance map. The map values are coordinates giving the x and y distances to the nearest point on the boundary, and are stored as complex valued pixels. Then the absolute function is used to transform these into the radial distance. More information about the Danielsson distance map can be found in the paper “Distance Maps for Boundary Detection and Particle Rebuilding,” by Frédérique and Lefebvre (http://www.ici.ro/ici/revista/sic97_3/GUY.html). IMAQ Danielsson is even easier to use than IMAQ Distance, as it is not necessary to specify whether to use square or hexagonal pixel frames (Figure 6.17).
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IMAGE PROCESSING SERIES Series Edit
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Foreword The introduction of LabVIE
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FIGURE 1 Vision 6.1 FIGURE 2 Compan
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Acknowledgments My gratitude goes o
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Dedication To Don “old fella” P
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Contents Chapter 1 Image Types and
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Chapter 4 Displaying Images........
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Chapter 7 Image Analysis...........
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1 Image Types and File Management F
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Image Types and File Management 3 F
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Image Types and File Management 5 A
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Image Types and File Management 7 C
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Image Types and File Management 9 p
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Image Types and File Management 11
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Image Types and File Management 13
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2 Setting Up You should never under
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Setting Up 17 FIGURE 2.3 (a) Interl
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Setting Up 19 Linear Aray Light Sou
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Setting Up 21 FIGURE 2.7 National I
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Setting Up 23 2.1.3.2 Control and I
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Setting Up 25 FIGURE 2.11 X-Ray ima
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Setting Up 27 Apple Computer techno
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Setting Up 29 FIGURE 2.17 An inexpe
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Setting Up 31 Although this would b
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Setting Up 33 134 -115 \ Contrast =
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Setting Up 35 resolution printer wi
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Setting Up 37 C A B C Traditional T
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Setting Up 39 Camera Light Source O
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Setting Up 41 Camera Light Source (
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Setting Up 43 FIGURE 2.37 (a) An ob
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Setting Up 45 FIGURE 2.41 (a) PCB p
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48 Image Acquisition Processing wit
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Page 121 and 122: 98 Image Acquisition Processing wit
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200 Image Acquisition Processing wi
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8 Machine Vision A generally accept
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Machine Vision 219 TABLE 8.1 “IMA
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Machine Vision 221 TABLE 8.3 Input
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Machine Vision 223 packages, includ
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Machine Vision 225 good sense to ad
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Machine Vision 227 TABLE 8.4 “IMA
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Glossary 1-Bit Image An image compr
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Glossary 231 binary display device
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Glossary 233 spatial Þlters, each
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Glossary 235 Resolution There are t
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Image Acquisitionand Proces

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