perClass Mira for Cubert Utils

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Artificial Intelligence for Analyzing Hyperspectral Data in Real-Time

You are interested in deeper analyses and extracting more useful information from the spectral image data? The perClass Mira extension for Cubert Utils allows you to add a powerful image classification solution to the live data stream, without the need of understanding complex classification methods. Retrieve relevant information from your video stream faster than ever before. Mira is of course available for all Cubert camera models.

Applying Machine Learning

Mira is a software interface for analyzing hyperspectral image data. Based on a powerful machine learning engine Mira selects the best statistical model for given labeled samples fully automatically.

Mira helps creating specific solutions for image analysis that can be applied to Cubert’s hyperspectral snapshot cameras, such as the ULTRIS 20, in live mode.

ULTRIS 20 image of a hilly landscape in colored infrared (left) and segmented by Mira (right). The semantic information is displayed in different colors.

Intelligent Software Solution


Easy-to-use image classification & regression tool

Automated model building

Interactive fine-tuning

Pixel classification & object segmentation

Applicable to the hyperspectral live data stream

Mira for Cubert Utils - Cubert GmbH Hyperspectral imaging - GermanyColored Infrared Segmented by Mira

Flexible and Easy-to-use


Food quality control

Plant disease detection

Medical and pharmaceutic assessments

Supervision of production processes

Suited for full machine vision integration

Time-critical and non-destructive assessments in any industrial environment

Quality Assurance through Quantification and Qualification

Gathering hyperspectral images is only the first step of solving a problem. Analyzing the data can be challenging and time-consuming. It typically requires software development and a high level of expertise in applied statistics, math and remote sensing.

Mira enables anyone to create an interpretation solution timesaving and without needing this expertise – (1) record spectral data with your Cubert camera, (2) transfer this data to Mira and train as well as evaluate an efficient classifier for specific materials, and (3) apply this classifier to the live data stream as plugin in the Cubert Utils software.

With Mira users can quantify the composition of the hyperspectral image fully automatically. Furthermore, Mira allows you to qualify the samples in the image. Check if your fruits have rot, identify foreign objects during your production process or evaluate the degree of skin burns – within seconds!

Training the model

Mira for Cubert Utils - Cubert GmbH Hyperspectral imaging - Germany

Import your hyperspectral image to Mira. Define multiple classes for your samples. Label those classes in the image allowing Mira to learn on this training data. Mira analyzes this data and creates a classification using machine learning.

Pixel classification

Mira for Cubert Utils - Cubert GmbH Hyperspectral imaging - Germany

Mira assigns each pixel to the predefined classes. The composition of your samples in the hyperspectral image is gathered fully automatically. Validate the result of the trained classifier and fine-tune the model interactively.

Object segmentation

Mira for Cubert Utils - Cubert GmbH Hyperspectral imaging - Germany

Mira is also able to count the number of different objects, i.e. connected components, in the image. Set a threshold for the size to adapt to your individual application. Classify the pixels within an object and let Mira identify outliers.