Image Acquisitionand Proces

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Image Analysis 199 distance between them is trivial. For example, if a user draws a line ROI between two points, the pixel distance between them can be easily determined (Figure 7.49 and Figure 7.50). While this is simple when we know the spatial positions of the two points, it becomes more difÞcult when their coordinates must be determined programmatically. FIGURE 7.51 Finding edges and their parameters — wiring diagram. 7.7.3 FINDING EDGES PROGRAMMATICALLY An edge in an image is generally deÞned as a feature interface with high contrast; if an image’s intensity changes dramatically within a small spatial range, then it can be considered as an edge. The IMAQ Edge Tool can be used to detect and classify edges in an image by inspecting the pixel intensity values along a trace applied to the image. The example in Figure 7.51 obtains the pixel coordinates of points along a line ROI drawn by the user, and uses them to search for edges. The pixel coordinates are obtained using IMAQ ROIProfile, and are wired into IMAQ Edge Tool. IMAQ Edge Tool outputs the number of edges detected, their coordinates and an array of clusters detailing comprehensive information regarding each of the edges (Figure 7.52). FIGURE 7.52 Finding edges and their parameters. IMAQ Edge Tool is conÞgured by deÞning the edge parameters to use during the search. Contrast speciÞes the threshold for the edge’s intensity difference between features — edges with a contrast less than this threshold are not treated as edges, and are subsequently ignored. The contrast is calculated as the difference
200 Image Acquisition Processing with LabVIEW between the average pixel intensity before the edge and the average pixel intensity after the edge over the Þlter width (Figure 7.53), which is the maximum and minimum number of pixels over which you deÞne an edge can occur. A small Þlter width ensures that the change in contrast occurs rapidly, whereas a larger Þlter width allows for a more gradual change. Filter Width Pixel Intensity Contrast FIGURE 7.53 Edge parameters. Steepness Distance Along Pixel Coordinate Path Consider a pixel position a. The contrast is determined by considering the pixels along the line of interest, both before and after a, that exist within the Þlter width: fw È x a ù Èx a ù = 2 Í ú Í ú Contrast = Í Â I( x) ú ∏ Í Â I( x) ú fw x a x a Î Í = -( ) û ú Í = ú 2 Î û = +( ) The edge information array output of IMAQ Edge Tool contains an array of clusters, each describing respective detected edges. The two elements of the cluster describe the position, which deÞnes the pixel coordinate location of the detected edge. This output is not the (x,y) position of the edge, nor does it represent the pixel number along the ROI where the edge is detected. When IMAQ Edge Tool executes, it searches the intensities that correspond to the pixel locations deÞned in the pixel coordinates input. This input in not necessarily linear, nor continuous. It is possible to deÞne the pixel coordinates, so that IMAQ Edge Tool inspects pixels that are far from each other. For example, the array shown in Figure 7.54 is an entirely valid pixel coordinates input. This example shows a spatial discontinuity between the 3rd and 4th elements. IMAQ Edge Tool does not interpolate between these coordinates, instead it considers them as continuous, and applies the edge detection across them. The edge information array output also contains the contrast of the detected edge, and the polarity. A polarity of 1 indicates a rising edge (the intensities are changing from dark to light), whereas a polarity of –1 indicates a falling edge (light to dark).The Þnal output cluster element is called score, and is unused.
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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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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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Page 180 and 181: Morphology 157 6.5 CASE STUDY: FIND
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