Image Acquisitionand Proces

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Setting Up 33 134 -115 \ Contrast = = 134 + 115 0. 076 indicates a low-contrast image, whereas the following example image: 123 180 193 221 247 186 183 149 173 185 255 208 89 143 136 250 210 11 78 102 246 205 15 101 66 I Brightest = 255, I = 11 Darkest 255 -11 \ Contrast = = 255 + 11 0. 917 indicates an image with a high-contrast level. A high-contrast image often appears to be sharper than that of a lower contrast image, even when the acquired image is of identical resolution. 2.3.4 PERSPECTIVE (PARALLAX) Perspective errors occur when the object’s surface is not perpendicular to the camera axis (Figure 2.21). The second image is quite badly distorted (skewed) due to the high angle between the object’s surface and the camera axis. Perspective errors occur in just about every lens system that exists, unless the only object feature that you are interested in is directly below the camera axis, and is only a few pixels wide. There are two common methods of minimizing perspective error: software calibration and telecentricity.
34 Image Acquisition Processing with LabVIEW Image Image Minimal Perspective Error High Perspective Error FIGURE 2.21 Camera perspectives. 2.3.4.1 Software Calibration Calibration occurs when an object with known features is acquired, and the differences between the known object and the acquired image are used to process subsequently acquired images. The Vision Toolkit ships with several intuitive calibration routines and known grids to help make calibration easier. Consider the standard Vision Toolkit Calibration Grid in Fi gure 2.22. This grid is provided FIGURE 2.22 Calibration grid. with the Vision Toolkit as a PDF document, and can found using the following path: Start > Programs > National Instruments > Vision > Documentation > Calibration Grid. The calibration grid’s dots have radii of 2 mm and center-to-center distances of 1 cm, although this may vary slightly depending on your printer setup (using a high-
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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 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
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84 Image Acquisition Processing wit
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100 Image Acquisition Processing wi
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6 Morphology When applied to vision
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Morphology 143 I Closed { } = Erode
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Morphology 145 FIGURE 6.3 Simple mo
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Morphology 147 FIGURE 6.5 Custom st
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Morphology 149 FIGURE 6.8 Particle
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Morphology 151 FIGURE 6.12 Fill hol
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Morphology 153 FIGURE 6.17 Danielss
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Morphology 155 Detected circles wit
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Morphology 157 6.5 CASE STUDY: FIND
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Morphology 159 6.6 USER SOLUTION: D
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Morphology 161 ULTRASOUND MACHINE (
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Morphology 163 FIGURE 6.31 The Edit
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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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