System and method for authenticating and classifying products using hyper-spectral imaging

An apparatus for authenticating and classifying a material, comprising:

• a sample holder configured to contain a sample;
• a first plurality of light-emitting diodes (LEDs) and a spectrometer forming ends of a first optical path, wherein the spectrometer receives light emitted from the first plurality of LEDs and transmitted through the sample;
• a second plurality of LEDs and the spectrometer forming ends of a second optical path, wherein light emitted from the second plurality of LEDs is reflected from the sample and directed to the spectrometer;
• a temperature control system comprising a temperature sensor and a heater configured to maintain a consistent temperature of the sample;
• and
• a computing device comprising a processor and a memory, the computing device in electronic communication with the first and second pluralities of LEDs and the spectrometer, configured to control the LEDs, receive data from the spectrometer, and process the data using machine learning models to classify and authenticate the material.

A computer-readable storage media storing one or more computer instructions which, when executed by one or more computing processors, cause the one or more computing processors to perform:

• illuminating a sample material with light emitted from a plurality of light-emitting diodes (LEDs);
• collecting spectra of light reflected, transmitted, or emitted by the sample material using a chip-based spectrometer;
• processing the collected spectra with a computing device to determine a numerical difference between sample spectra and reference spectra from a training set;
• classifying the sample material based on the numerical difference using a machine learning model stored in the computing device;
• generating a unique spectral fingerprint of the sample material for authentication purposes;
• and
• providing an output indicating the authenticity of the sample material.