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More WAY-2C Image Interpretation and Measurement Examples
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The image on the left shows a portion of a ships hull, with the red paint partially covered with green seaweed and white barnacles. After being trained on typical examples of paint, paint with thin seaweed, seaweed, and barnacles WAY-2C generated the image on the right. |
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After being trained on red stained, blue stained, and unstained regions in the left image, WAY-2C can generate either sparse or complete interpretations of other images such as those shown on the right. Counters provide output of relative amounts of each class present. Click for more detail.
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Appearance and proper proportions can be critical in consumer acceptance of baked goods. After being trained on typical examples of chips, dough, and background for cookies such as the one shown on the left, WAY-2C generated the image on the right. It indicates that chips are exposed over 11.1 percent of the surface area of the cookie. Again statistics on amount of each class present can be written to files, printer or other external devices and used for process control, sorting or labelling.
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Although WAY-2C does not use mean color values for classification, it can generate such values when required. In this example the system locates the cookies on the tray, determines the size and mean color of each, and outputs the results for process control and analysis purposes.
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Measurement of shotgun shell diameter and verification that waterproof wax is present are performed in a single operation. The shell on the left has wax present, the shell on the right will be rejected because it has no wax.
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Modern bricks are manufactured in a wide variety of colors and designs. Equipment failure during the manufacturing process can result in bricks which do not meet the color design specifications. WAY-2C based inspections can minimize the effect of such failures by early recognition of discrepancies in the color statistics. | .
 
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Last Updated 6/2/11
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