Better vision: Hyperspectral imaging technology research grant awarded
To increase the capabilities of robotic, food sorting, and unmanned aerial vehicles (UAV) vision by 10x, state of Montana awarded research funds to Montana State University, Resonon, and Impulse Accelerated Technologies.
Montana Governor Steve Bullock and Montana Department of Commerce Director Meg O’Leary announced research grant awards for hyperspectral imaging technology. The grants were awarded to for Montana State University, Resonon, and Impulse Accelerated Technologies. "These state-of-the-art projects will significantly and positively impact Montana’s opportunities for economic growth," Bullock said. "Through investments in innovative research and commercialization, we’re not only supporting cutting-edge projects and jobs today, but we’re also helping to define what Montana’s economy looks like for years to come."
Hyperspectral imaging refers to the measurement of hundreds colors at a point (pixel) instead of the typical three colors (RGB) that conventional color cameras measure. This means that hyperspectral cameras can generate 100 times the data as conventional color cameras. In applications that process large quantities of hyperspectral data in real time, such as in food sorting, field programmable gate arrays (FPGAs) are required to process the immense amount of data being generated. Impulse Accelerated uses tools enable FPGAs to be programmed at a high level in the C language.
Other applications might include more accurate robotic machine vision and more capable unmanned aerial vehicles (UAVs).
Resonon’s current systems use a PC to process the data from their hyperspectral cameras. However, the data cables from the camera to the PC and the CPU itself limit the data processing to a fraction of what the hyperspectral cameras are capable of generating. Currently, the system has a spatial resolution of 640 pixels, 240 colors, and can take pictures at a frame rate of 140 frames/sec. The MSU team demonstrated that an FPGA based system would be capable of a resolution of 2,048 pixels, 512 colors, and a frame rate of 340 frames/sec. The additional resolution would allow for users to notice smaller defects. The additional colors would allow finer gradients of color to be classified and the faster frame rate would allow the sorting to be done much faster. Rand Swanson, president of Resonon, said that this would be valuable in sorting and inspection applications.
The MSU academic team working under Dr. Ross Snider is helping to shift the PC software to run as multiple parallel streaming processes in FPGA hardware. Montana State is using tools and techniques provided by Impulse Accelerated Technologies of Bellevue Washington.
Impulse Accelerated created the tools and also provided engineering assistance to "refactor" the software code into efficient hardware code. The researchers are trying to increase parallelism and double the processing throughput with each additional processing pipeline. The team goal is a 10x improvement.
"This technology has surprisingly broad application," said Brian Durwood of Impulse. "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."
Impulse Accelerated Technologies
www.impulseaccelerated.com
Montana State University
Montana State University | Top Tier Research University | Montana State University
Resonon Inc.
– Edited by Chris Vavra, production editor, Control Engineering, CFE Media, cvavra@cfemedia.com. See more Control Engineering discrete sensor and vision stories.
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