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  • Montana Invests in Optics for Agriculture

Photonics.com
Aug 2015
Hyperspectral imaging eyed for machine vision, crop management, medicine


BOZEMAN, Mont., Aug. 25, 2015 — More than $2.8 million in state funding aims to kick hyperspectral imaging and other optical technologies into hyperdrive.

Two sets of grants will aid commercialization of technologies developed at Montana State University (MSU), fostering partnerships with several Bozeman-area businesses and even helping to launch a pair of university spinoffs.

"In this overall effort, what we're trying to do is strengthen and broaden out the high-tech portions of the Montana economy, specifically optics and photonics … and start coupling them with some of the more traditional Montana economies like agriculture," said Dr. Joseph Shaw, a professor and director of the university's Optical Technology Center.

Image processing

In one project, university researchers will develop new image processing technology for Resonon Inc., a manufacturer of hyperspectral machine vision systems used for automated sorting and inspection (among other applications).



Resonon's hyperspectral imagers are already used on production lines to identify defects in nuts and berries. This is possible because the imagers capture 240 color bands rather than the three or four used by conventional cameras. But due to computer processing constraints, only a small portion of all that color data can be used in real time.

"There are only a few seconds (and in some cases, less than that) between the time the hyperspectral data are collected and when algorithms need to convert the data into useful information to direct the actuators (e.g., robots)," said Resonon President Rand Swanson. "Currently, we do not have the computational bandwidth to exploit the data to its fullest extent, plus we are imaging at relatively low resolution."

Resonon is counting on field-programmable gate arrays (FPGAs) to ease the bottleneck and enable higher-resolution hyperspectral imaging. The FPGAs will be developed by researchers at MSU and Impulse Accelerated Technologies Inc. of Bellevue, Wash.

Current hyperspectral imaging systems operate with separate cameras, frame grabbers and computers, which constrains how quickly data can be transferred, according to Dr. Ross Snider, an associate professor of electrical and computer engineering at MSU. FPGAs would cut out the intermediate step and increase computational bandwidth by allowing cameras to perform their own image processing.

Faster processing of hyperspectral images has potential uses outside the food industry.

"This technology has surprisingly broad application," said Brian Durwood, co-owner of Impulse Accelerated Technologies. "The same algorithmic architecture that visually sorts shells from almonds can also be used to more quickly scan the sea and 'sort out' a person overboard as differentiated from the surrounding sea, from an automated camera suspended under a Coast Guard plane."

The MSU project, though, will have a narrower scope. It is focused on two application areas: food sorting based on shape detection using mid- and high-end FPGAs, and data recording for environmental monitoring using low-end FPGAs.

Last month the Montana Board of Research and Commercialization Technology (MBRCT) awarded the project a $100,000 grant. The project will also share in a $2.5 million grant awarded by the Montana Research and Economic Development Initiative and overseen by Shaw.

Other projects

Announced Aug. 18, the $2.5 million Montana Research and Economic Development Initiative grant will support a total of seven collaborations between the university and nearby optical technology companies.

Joseph Shaw

Professor Joseph Shaw discusses optical research projects targeted for commercialization under a $2.5 million grant announced Aug. 18. Courtesy of Kelly Gorham, Montana State University.


Shaw, who coordinated the grant proposal, said MSU is ripe for this kind of public-private partnership, with robust optics research at the university and the highest per-capita concentration of optics companies in the U.S.

Seven of those companies will take part in the grant-funded projects, including:

• Snider, Shaw and professor Edward Dratz will work with Resonon on another FPGA-enhanced hyperspectral imaging device to be used with microscopes for real-time imaging of live cells.

• The startup Advanced Microcavity Sensors LLC will develop microscale hyperspectral imaging filters for applications including skin cancer detection and counterfeit drug detection. Company cofounder and MSU research scientist Dr. Russell Barbour also recently received a $209,015 MBRCT grant to support the research.

• The startup Revibro Inc. will develop adjustable-focus optics based on microelectromechanical systems (MEMS).

• University researchers will collaborate with S2 Corp., AdvR Inc., Scientific Materials Corp. and Montana Instruments Corp. on active waveguides for integrated optical circuits.

• Assistant professor Kevin Repasky will work with AdvR on optical parametric oscillator technology for tunable lasers that could be used in gas detection.

• Professor Robert A. Walker will work with Altos Photonics Inc. on devices based on nonlinear optical overtone spectroscopy for detecting surface contaminants.

• Shaw will work with NWB Sensors Inc. to develop spectral imagers for discriminating between crops and weeds in precision agriculture, wildfire mapping and other remote sensing applications. The imagers will be compact and may be used on unmanned aerial vehicles (UAVs).

Meanwhile, Resonon earlier this year won federal funding to develop its own UAV-based hyperspectral imager for agricultural and environmental monitoring applications. The $224,999 Small Business Innovation Research grant was awarded by the U.S. Department of Energy.

The system will incorporate a patented anamorphic optical scheme "that provides an additional degree of engineering freedom as compared to conventional 'pushbroom' hyperspectral imager designs," Swanson said.




GLOSSARY
hyperspectral imaging
Methods for identifying and mapping materials through spectroscopic remote sensing. Also called imaging spectroscopy; ultraspectral imaging.
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