摘要:
Devices, systems and methods for sorting and labeling food products are provided. Respective spectra of food products for a plurality of segments of a line are received at a controller from at least one line-scan dispersive spectrometer configured to acquire respective spectra of the food products for the plurality of segments of the line. The controller applies one or more machine learning algorithms to the respective spectra to classify the plurality of segments according to at least one of one or more food parameters. The controller controls one or more of a sorting device and a labeling device according to classifying the plurality of segments to cause the food products to be one or more of sorted and labeled according to the at least one of the one or more food parameters.
摘要:
A method and an apparatus for increasing the accuracy of a spectrometer system corrects for light source quality, exposure time, distortion in y direction, distortion in x direction, temperature dependence, pixel alignment variability, dark pixels, bad pixels, pixel read noise, and pixel dark current noise. The method and apparatus produces an algorithm for optimizing spectral data and for measuring a sample within the spectrometer system using the optimization algorithm. The spectrometer apparatus comprises a composite external light source, a source light collector, an illumination light structuring component, a sample, a sample light collector, a spectrometer light structuring component, a light dispersing engine, photo detectors, an electrical signal converter, a data preprocessing unit, and a data analyzer. The method and apparatus can include a corrected photo detector algorithm, sample illumination correction algorithm, LDE-PD alignment procedure, SLSC-LDE alignment procedure, distortion correction matrix, and an algorithm for optimizing of spectral data.