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Hyperspectral Machine Vision, Next Generation

Seamless integration into your system

Hyperspectral machine vision is a cutting-edge technology that enables advanced imaging and analysis capabilities. Its ability to capture and process data across a wide range of spectral bands allows for enhanced detection and characterization of materials and objects.

Hyperspectral imaging applications in various industries is growing, hyperspectral machine vision holds immense promise for future advancements in imaging and analysis.

Resonon machine vision hyperspectral technology is used by leading companies in food production, biotechnology, manufacturing, and consumer electronics.


To be an industry leader, you need to stay on top. Resonon’s hyperspectral machine vision systems are providing sorting and grading, process and quality control, and product identification for our customers that exceed the performance of other technologies.

Introduction to Hyperspectral Machine Vision

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Hyperspectral Machine Vision System Components

  • Hyperspectral imaging camera
  • RVS (Real-time Vision System) Machine Vision software
  • Touch screen interface
  • Stabilized lighting
  • Integration and training services
  • System documentation
  • Expert support

Hyperspectral Imaging Camera Options

Resonon offers hyperspectral imaging cameras that scan wavelengths from the near-ultraviolet (NUV), through the visible (VIS), to the near-infrared (NIR).   
Our team will help you identify the system best suited to your needs.  Please contact us for further information.
Hyperspectral Machine Vision, Next GenerationHyperspectral Machine Vision, Next Generation
Pika L-FPika IR
Spectral Range (nm)420 - 980900 - 1700
Spectral Resolution - FWHM (nm)3.18.8
Spectral Channels224168
Spatial Pixels720320
Max Frame Rate (fps)585508
Weight, w/o lens (kg)0.642.95

Frequently Asked Questions

Hyperspectral machine vision is useful in automated sorting applications. Automated sorters typically use hyperspectral imaging to determine one of two types of information:
  • Classification: Category prediction (e.g., conforming or non-conforming product, product or foreign material, type of plastic, bruised or unbruised apple)
  • Regression: Quantity prediction (e.g., ripeness of a fruit, moisture content in a baked food product, percentage of a specific material in a mixed group, deviation from a nominal value such as product color variance)

Resonon hyperspectral cameras are line-scan imagers (also known as push-broom). This means that the camera collects a line of data with each frame of the detector, and either the camera must translate over the object being scanned or the object being scanned must translate in front of the camera.

In machine vision applications, the objects being scanned are generally traveling on a conveyor belt with the camera positioned above the belt. Resonon provides the hyperspectral camera, our RVS (Resonon Vision System) software, specialized lighting system, and an automated calibration solution (if required for the application). The conveyor belt is provided by the customer. Other components required for integration might include a mounting structure for the camera and lights, a rotary encoder, or an enclosure for the system. These components can be provided by Resonon or by the customer.

The RVS software runs a socket server output. The server broadcasts a highly customizable signal for each object detected by the system. Data that can be included for each object are encoder stamps, time stamps, pixel coordinates mapped to belt geometry, classification results, shape, size, and orientation. This output is intended to be completely customizable and configurable so as to drive additional hardware down the line, such as picking robots, air-jet sorters, etc. The socket server output is designed to be simple to configure, either by an end-user with software experience or by a Resonon Software Engineer.

You can train Resonon’s machine vision software (RVS) by scanning both in- and out-of-spec products and collecting spectral data for each. From there, you can apply different models to the training data to determine a solution that meets your application’s inspection accuracy and line speed requirements.

Resonon’s RVS software can calculate shape statistics (e.g., area, perimeter, orientation), but it does not use shape for classification. If your application would benefit from shape-based classification, Resonon can develop a custom application.


Texture indicates variable spectral response, so it can be a challenge or an asset depending on how the system is programmed. Resonon has developed models that leverage texture data, but most simple models ignore it.


Color is spectrum, so it is a critical parameter. If the product color is variable, the system needs to be trained on the complete range of color it could encounter. Statistical models cannot be expected to make accurate predictions outside of the range of their training data.

If it impacts the relationship of the item of interest to the lighting source, product orientation can be important to the RVS software models training and predictions.

It depends on factors like object size, product density, complexity of inspection algorithm, and belt speed. The maximum camera line speed (Max Frame Rate) is around 500 lines per second. Using the number of spatial pixels of the camera (see our camera specifications table), you can calculate the number of pixels imaged per second. Nine pixels per object is a reasonable starting point for the smallest detectable object. Using the number of pixels imaged per second and 9 pixels per object, you can estimate a theoretical maximum. The number achieved in practice is generally less than the theoretical maximum.

Factors like belt speed, belt width, camera properties, objective lens selection, camera position, and lighting limit the minimum detectable defect size. Generally, the system can confidently detect defects or differences that are around 9 pixels (3 by 3) per object of interest.

Resonon hyperspectral imagers are line-scan devices, so maximum belt speeds are closely linked to the size of the objects or defects under inspection. Other important factors are the difficulty and accuracy requirements of the inspection task and the physical constraints of the camera and lighting system.

The formula for calculating along-track (in the direction of belt travel) spatial resolution of the hyperspectral camera as a function of belt speed is as follows:�����������������(��)=���������(������/������)���������(�����/������)∗100060High-speed imagers scan at about 500 lines per second. At a belt speed of 16 m/min (~50 ft/min), the along-track spatial resolution of the camera is 0.5 mm. The machine vision system can generally detect objects or defects that are 9 pixels (3 by 3) in size. For this example, an object or defect that is 1.5mm in size is detectable. Reach out to a Resonon application specialist for an estimate specific to your system.

The system can see through some materials and, depending on the material and the spectral range of the camera, it is sensitive to some depth ,as well. We recommend testing samples to determine if the technology meets your needs. Please contact a member of the Resonon Sales Team to have your samples tested at our facility.

Like many imaging technologies, hyperspectral imaging is primarily sensitive to the surface. However, these systems can detect some sub-surface characteristics, like fruit bruising and fruit ripeness. See our bruised apples application example.

You will want an enclosure to protect your system. Some parts of the system are not waterproof and are only partially dustproof. Enclosures are available off the shelf, and Resonon has experience designing and procuring custom enclosures if needed.

The system requires specialized, controlled lighting that is enclosed or otherwise blocked so that it won’t be impacted by external lighting from the factory.

We do not sell turnkey systems for installation into factory lines because machine vision installations require some level of customization. We work with you to determine what aspects of the integration your team has the expertise to manage and support you in completing the rest.

That said, we do sell turnkey hyperspectral imaging systems for pilot projects. These include our Benchtop system and Bio-LIF system.

The spectral signatures of the objects or defects in your application will dictate which wavelengths are important. It is challenging to know what those signatures are without testing. Please contact the Resonon Sales Team if you’d like samples tested.

A Resonon machine vision expert will install and set up the system.

Yes, we do. A Resonon machine vision expert will be on-site for installation. In-person training is typically hosted after initial set-up.

Yes, Resonon is happy to provide proof-of-concept testing on your samples. Please contact the Resonon Sales Team and tell us what you’re looking to use our system for.

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.

Hyperspectral Machine Vision, Next Generation


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