Resonon hyperspectral systems enable you to accurately and consistently distinguish between similar colors or materials. Our systems are in use worldwide on platforms ranging from airplanes to microscopes. As the following examples demonstrate, our solutions solve a wide range of problems.
Resonon's hyperspectral imaging systems are used in agriculture research all over the world, enabling identification of weeds, monitoring of plant health, and evaluation of ripeness. Early detection of crop stress is a common application.
Application Example
Hyperspectral Fluorescence in Grapevine
A Resonon Pika L hyperspectral imager was used to quantify chlorophyll and nitrogen in Cabernet Sauvignon grapevines.
An autonomous robotic team was developed that can rapidly learn the characteristics of environments it has never seen before using a Pika XC2. This study describes the characterization of an aquatic environment over just a few minutes.
A group at the Max Planck Institute in Germany used a Resonon hyperspectral camera to non-invasively identify pigments in single cells and map the spatial organization of phototrophic groups in complex microbial communities.
Resonon hyperspectral imaging cameras are used in air, space, and underwater vehicles to capture detailed spectral data for a wide range of applications.
Application Example
Yield estimation in wheat
A Resonon Airborne Pika L system was used to help predict yield in wheat as a function of fertilizer concentration. LAI and chlorophyll were measured for 24 plots using 8 nitrogen treatments.
Resonon has partnered with NASA to design and build the ARCSTONE hyperspectral instrument to measure calibrate lunar reflectance from low-Earth orbit. The calibration accuracy will improve by more than 10x, helping to increase understanding of Earth systems (i.e., weather, climate change) while reducing future imaging satellite costs.
Resonon's hyperspectral imaging systems are used in food research and industry to identify defects, characterize product quality, and locate contaminants.
Application Example
Bruised Apples
A Resonon IR+ hyperspectral camera was used to scan apples, some of which were purposefully bruised pre-scanning. Resonon’s Spectronon software was used to classify the bruises. Peeling the skin shows the bruising, undetectable in a standard RGB image.
Application Example
Nut Sorting
Hyperspectral imaging enables robotic sorting of nuts from shells and other foreign material, a job traditionally accomplished via manual sorting.
The image of walnuts shows the classification of the walnut meat (green) and shell (orange) components.
Application Example
Cooked Food
Subtle color changes associated with food quality can readily be identified using hyperspectral imaging.
The image of chicken nuggets shows the classification: missing breading (red), crispy (green), and appropriately-cooked (blue).
Machine Vision
Hyperspectral machine vision detects small color differences more accurately and identifies different materials more reliably than conventional imaging.
Resonon's system can be interfaced to robots, labeling devices, or used as feedback for sorting, grading, or process control.
Application Example
Pharmaceuticals
Hyperspectral infrared imagers can identify counterfeits, find defects, and eliminate prescription errors.
The image shows three types of white pills, indistinguishable by color to the human eye, but accurately classified via Resonon IR+ hyperspectral machine vision.
Application Example
Identifying Finished Goods
A major manufacturer of laminates uses Resonon machine vision systems at multiple facilities to identify over 30,000 products daily from a library of several thousand.
The image shows two nearly-identical products that are accurately differentiated using Resonon machine vision.
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