Image Acquisitionand Proces

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Morphology 143 I Closed { } = Erode Dilate( ISource ) Although performing two seemingly opposite morphs on the source image may suggest that it will result in the destination image being the same as the source, this is not the case. Original image data is lost on executing the Þrst operation, and hence the original image cannot be recovered. Dilate Þ Erode Þ As you can see, the small inner holes were Þlled, as was a portion of the upper inlet. 6.1.4 OPENING Opening an image (expanding holes and other background features in an image) requires the opposite sequence to closing: Þrst erode the source image, and then dilate it: I Opened { } = Dilate Erode( ISource ) Erode Þ Dilate Þ The opened image may not look much like its source, although the thinner portions of the object have been successfully opened, and only the bulk area remains. 6.1.5 NONBINARY MORPHOLOGY Although the simplest method of morphology is to Þrst threshold an image, creating a binary image (a pixel is either light or dark — there is no in-between), other methods exist such as gray and color morphology. Gray morphology is achieved by considering each of the neighboring colors as binary couples, and performing binary morphology between them. This process is
144 <strong>Image</strong> Acquisition <strong>Proces</strong>sing with LabVIEW FIGURE 6.1 Simple morphology — erosion and dilation. repeated for n colors –1 (i.e., the number of color neighboring couples), and then these morphed images are weighted back using their respective gray levels (each morphed binary is typically promoted to the next highest gray level) and recombined into an image with n colors –1 colors. 6.2 PRACTICAL MORPHOLOGY Simple dilation, erosion, opening and closing can be easily achieved using either IMAQ Morphology or IMAQ GrayMorphology 1 (Figure 6.1). The morphological function performed on the source image in Figure 6.1 was performed using the code shown in Figure 6.2. Similarly, both opening and closing FIGURE 6.2 Simple morphology: erosion and dilation — wiring diagram. can be achieved using the same VIs. As you can see in Figure 6.3, the opening routine discards the small specular objects around the main object, whereas the closing routine attempts to include the specular data to the east of the circle, effectively closing the spaces between the solid object and close outlying objects (Figure 6.4) 1 These vision routines presume that the object of an image is the brightest section, and the background is the darkest; therefore, you may need to invert an image before attempting practical morphology.
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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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194 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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