Image Acquisitionand Proces

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Image Processing 111 FIGURE 5.37 Image averaging alternatives — Front panel example. FIGURE 5.38 Image averaging alternatives — comparison with other averagers.
112 Image Acquisition Processing with LabVIEW FIGURE 5.39 Image averaging alternatives — how it works. In the example shown in Figure 5.37, a low-resolution sample image (89 ¥ 44 pixels) plus simulated noise is provided as the input to demonstrate these routines. An unsigned 8-bit (U8) format with images scaled between 0 and 255 is used. Array transposition for the version using intensity graphs was necessary. A two-dimensional interpolation routine 1 has been integrated to allow enlarging the image while retaining the smoothing effect. The size of the active plotting area is adjusted in terms of width and height in pixels based on the interpolation factor chosen (interpolation factor numeric control will display when interpolation is selected in radio button control). The interpolation routine is only implemented in this example for the intensity graph container but can easily be integrated into the examples using IMAQ and Picture Control display containers. For practical use of these routines, one would substitute NI-IMAQ routines that perform continuous live image acquisitions from a CCD or other type of camera. The frame rate one obtains will be inversely proportional to the number of frames being averaged (as well as the physical size/number of pixels of the frames and size of intensity graph indicator). On a Compaq 1.5 GHz Xeon single processor-based system, I was able to process about 50 fps with 10 frames averaged and a 1-ms delay in the while loop of the block diagram. Keep in mind a two-dimensional array of noise is calculated within each loop iteration while for an actual machine vision situation, frame grabbing would be occurring instead and this will affect the true frame rate achieved. A color table control routine is also included, allowing the user to modify the color table during acquisition, although a gray scale color table is provided as the default. 1 NI Developer Zone Example: 2D Interpolation demo.llb.
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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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Morphology 161 ULTRASOUND MACHINE (
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Morphology 163 FIGURE 6.31 The Edit
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166 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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