Ann R. Thryft

November 15, 2011

3 Min Read
Machine Vision Advances Showcased at Stuttgart  Conference

This year's Vision 2011 conference in Stuttgart, Germany, featured a Medical Discovery Tour throughout the show. The showcase will include exhibits by several suppliers of hardware and software aimed at medical applications, a growing area for machine vision.

This exhibit represents a homecoming of sorts. The relationship between machine vision and medical imaging is complex. Many nondestructive technologies now used in industrial inspection originated in medical imaging. Some of these technologies are now being used to inspect medical products on the assembly line, including products with vision capabilities, and to identify different classes of objects in automated medical laboratories.

The rapid growth in the number and variety of medical devices -- from handheld patient monitors to large instruments -- has meant a big jump in the use of machine vision for inspection during their manufacturing. It has also meant more machine vision hardware inside imaging devices used in doctor's offices, hospitals, and labs.

For instance, computed tomography (CT) and X-ray technologies are now recognized parts of high-end electronics and industrial inspection. CT inspection has been used for years in aerospace manufacturing to identify things such as cracks in engine turbine blades, and more recently it came to circuit board inspection. Now it's becoming an adjunct to 2D X-ray and optical inspection techniques for its ability to perform 3D inspection. Another technology that began in medical imaging is amorphous silicon X-ray detection, which has recently moved into inline circuit board inspection.

Several vision technologies are being deployed to inspect medical products during manufacturing. CT imaging provides many images of an object taken at different angles. These images can be combined into a single 3D image that serves as a model of the component, which is then analyzed via software for defects. CT imaging is especially helpful for inspecting the internal structures of complex manufactured shapes.

In the production of high-value components or products in fields that require a zero-defect quality level, such as medical, automotive, aerospace, and electronics, every single part must be inspected. That means throughput must be high, or the whole line gets slowed down. In the past, CT X-ray technology has been subject to inadequate processing power and slow camera frame rates, lowering throughput. CMOS image sensors are helping to change this by boosting camera frame rates and increasing sensitivity to light. For example, in the Shad-o-Box 1280 HS X-ray camera from Teledyne Dalsa's Rad-icon Imaging division, the CMOS sensor's resolution is 1.6 megapixels at 30fps, the image acquisition speed needed in high-speed, high-volume production lines.

Smart cameras such as those made by Vision Components already inspect medical devices on the production line and sort blood samples in automated medical laboratories by reading and analyzing their color codes and barcodes. Now, as part of desktop vision systems, the cameras are identifying surgical instruments in operating rooms by reading and analyzing their data matrix codes.

Just as color cameras have become more important in industrial machine vision for identifying different colored parts, so have color-recognition abilities in machine vision software. Color recognition in image processing software used for medical imaging, such as MVTec Software's HALCON 10, is especially important. Color classifier algorithms are key elements in the vision software used in automated labs for cytology, cell biology diagnostics, and tissue identification.

About the Author(s)

Ann R. Thryft

Ann R. Thryft has written about manufacturing- and electronics-related technologies for Design News, EE Times, Test & Measurement World, EDN, RTC Magazine, COTS Journal, Nikkei Electronics Asia, Computer Design, and Electronic Buyers' News (EBN). She's introduced readers to several emerging trends: industrial cybersecurity for operational technology, industrial-strength metals 3D printing, RFID, software-defined radio, early mobile phone architectures, open network server and switch/router architectures, and set-top box system design. At EBN Ann won two independently judged Editorial Excellence awards for Best Technology Feature. She holds a BA in Cultural Anthropology from Stanford University and a Certified Business Communicator certificate from the Business Marketing Association (formerly B/PAA).

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