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Special Features Highlights 2006 p1 of 6:

• Vision system measures scallops
  The US NOAA Fisheries Service conducts surveys to determine the abundance and size distribution of deep-sea scallops in areas between Cape Hatteras, NC, and Georges Bank. To do this, measurements from 125,000 scallops are taken from approximately 500 randomly selected locations. William Kramer, an IT specialist at the NOAA Woods Hole Laboratory, obtained a Pioneer Funding grant from the Chesapeake Bay Trust to develop a prototype machine-vision system for this.
• Reader software brings value to Data Matrix
  Data Matrix is a compact, 2-D symbology capable of holding relatively large amounts of data compared to earlier-generation barcodes. The main benefits of Data Matrix compared to the earlier linear symbologies include higher information density, scalability, omnidirectionality, and stronger error-correction capability. Data Matrix is becoming the 2-D barcode of choice, especially where space is at a premium, such as on semiconductor wafers and circuit boards.
• Color-matching systems test visual quality
  Color is a human perception based on a number of factors, and it is one of the most important visual cues we have for inspecting objects. For example, to make sure a consumer product elicits the desired color perception from the purchaser or user, manufacturers must test it under standardized conditions with a system that mimics human vision.
• Single-pixel imaging compresses information
  Researchers at Rice University (Houston, TX, USA; www.rice.edu) have combined a MEMS array with a single optical sensor to create an image/video camera that incorporates compressed sensing. "White noise is the key," says Richard Baraniuk, the Victor E. Cameron professor of electrical and computer engineering at Rice. "Thanks to some deep new mathematics, we're able to get a useful, coherent image out of the randomly scattered measurements."
• Hyperspectral system picks pickles
  Light-based methods for detecting vegetable quality have been developed but are not useful on an assembly line because of the execution time required. To speed inspection, researchers at Michigan State University (East Lansing, MI, USA; www.msu.edu) are developing a hyperspectral imaging system to check the quality of pickling cucumbers.
• System boosts web inspection
  The growing quality requirements of reprocessing mills and end-product users are pushing web-inspection system developers to increase the spatial and gray-scale resolutions of their systems. Normally, a single-camera solution would not be able to find the variety of defects that mills must identify, and, therefore several cameras with dedicated software have been used.
• Bottling inspection guaranteed by vision
  Customer satisfaction is a decisive factor in the face of tough competition in the brewery business. Ottakringer Brauerei (Vienna, Austria; www.ottakringer.com) needed to guarantee that packaging units contained the full number of defect-free products. Ottakringer contacted the image-processing department of Schmachtl (Linz, Austria; www.schmachtl.at), which determined production automation needs and priorities.
• Microscanner images at high speed
  Researchers at the University of California at Berkeley Microfabrication Laboratory (Berkeley, CA, USA; microlab.berkeley.edu) have fabricated a MEMS-based microscanner that can rotate a mirror 24,000 times/s with great precision. According to researchers Hyuck Choo and David Garmire, applications range from a head-up display that projects a video image onto the retina to advanced endoscopy tools outfitted with onboard CT scanners.
• Vision sensor checks color LED displays
  Color LEDs are a standard element of many consumer and industrial electronic displays, but engineers need a reliable and affordable method for automating the testing of the LEDs during production. SensoPart Industriesensorik (Pontiac, MI, USA; www.sensopart.com) recognized this need during the production of its industrial light barriers and photoelectric proximity switches.
• Vision system speeds marble sorting
  The ability to classify materials based on color or visual appearance creates a quality-control limitation in many manufacturing sectors, including the sorting of materials. When sorting is performed manually, it is subjective and prone to error. To automate the task, Asiris Vision Technologies (San Sebastian, Spain; www.asinistech.com) has developed a technology that the company says can reproduce human behavior in color-classification tasks.

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