Mastering going faster

In many vision applications, speed is the most important factor facing systems integrators. In automotive testing, for example, automakers use high-speed imaging techniques to test the effects of vehicle collision on airbags. As contributing editor Randal Chinnock explains, Lear, a supplier of instrument panels, seats, and interiors, is using digital cameras, motion analysis, and image-storage systems to test automotive components (see p. 24).

Mastering going faster

George Kotelly Executive Editor

georgek@pennwell.com

In many vision applications, speed is the most important factor facing systems integrators. In automotive testing, for example, automakers use high-speed imaging techniques to test the effects of vehicle collision on airbags. As contributing editor Randal Chinnock explains, Lear, a supplier of instrument panels, seats, and interiors, is using digital cameras, motion analysis, and image-storage systems to test automotive components (see p. 24).

Even the fastest electronic computers cannot match the speed of optical processing systems. Originally developed for military applications, optical processors are now finding use in commercial feature detection systems. On p. 38, contributing editor Richard Parker takes a look at the latest developments in optical computing and shows how frame-rate spatial light modulators are moving from the laboratory into commercial applications.

In semiconductor inspection, too, speed is critical to both throughput and cost-effectiveness. That`s why Veeco (Santa Barbara, CA) has built a micro x-ray fluorescence tool that allows semiconductor wafers, ball-grid arrays, multichip modules, and surface-mount devices to be examined. Contributing editor John Haystead shows how induced fluorescence is used to analyze such advanced semiconductor packages (see p. 30).

Newer networking implementations are also increasing the speed of data transfer. Contributing editor Rick Nelson explains that, in specifying such networks, designers of image-processing systems must determine the optimum topology to network image data from its source to image-processing hardware, storage, and display systems (see p. 42).

But not all vision systems designs call for speed, as Dave Wilson explains (see p. 16). In an interview with Prof. Brian Barsky of the University of California at Berkeley, Dave shows how, by simulating the results from a videokeratograph, researchers have managed to map the curvature of the cornea, predict conditions such as astigmatism, and generate more accurate contact lenses.

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