Plant phenotyping optimizes crop quality or robustness by selecting best genotypes. Spectral imaging offers a unique non-invasive method to capture qualitative parameters of plants, seeds and fruit. perClass Mira enables plant breeders and biologists to quickly build and deploy custom phenotyping work-flows. In this case-study we illustrate an application on seed growth monitoring. This is important to assess the speed of growth and extract relevant parameters.
Solution for foreign object removal based on spectral imaging is discussed. Both design of classifiers and their real-time deployment to a custom C/C++ application processing live spectral data stream is demonstrated using publicly available release of perClass Mira. The processing speed of 1.45ms/frame (691fps) is achieved on a Linux system with a GPU.
Separating different types of meat (pork, beef and chicken) using Hyspex spectral sensor
Classification of different materials in a live stream of spectral data using Photonfocus camera.
Classifying different complex land cover types such as grass, trees, water, shadows in spectral images acquired from a drone (Hyspex)
We gave a live demo of white & transparent plastic detection in (white) food product at Agri&Food Tech event in Den Bosch, The Netherlands. (Specim FX17)
Dark textiles can be sorted based on spectral imaging (Imec SWIR SNAPSCAN)
Separating diverse types of nuts and grain using Specim FX17 camera
Detecting red blood cells (Imec VIS-NIR SNAPSCAN)
Detecting virus infection in potato plants using spectral imaging.
Separating different types of plastics using Specim FX17 line-scan camera.
