On-line oil and foreign matter detection system and method employing hyperspectral imaging
US-11222203-B2 · Jan 11, 2022 · US
US11976973B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-11976973-B2 |
| Application number | US-202217573062-A |
| Country | US |
| Kind code | B2 |
| Filing date | Jan 11, 2022 |
| Priority date | Nov 19, 2012 |
| Publication date | May 7, 2024 |
| Grant date | May 7, 2024 |
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Provided is a method for blending of agricultural product utilizing hyperspectral imaging. At least one region along a sample of agricultural product is scanned using at least one light source of different wavelengths. Hyperspectral images are generated from the at least one region. A spectral fingerprint for the sample of agricultural product is formed from the hyperspectral images. A plurality of samples of agricultural product is blended based on the spectral fingerprints of the samples according to parameters determined by executing a blending algorithm.
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What is claimed: 1. A method for determining parameters for an agricultural product utilizing hyperspectral imaging comprising: scanning multiple regions along a sample of the agricultural product using a light source, the agricultural product is a blended agricultural product containing tobacco from at least two different bales; generating hyperspectral images from the multiple regions; forming a spectral fingerprint for the sample from the hyperspectral images; correlating one or more features of the spectral fingerprint to one or more sensory attributes of the sample; and determining blending parameters for a new blended product based on the one or more sensory attributes of the agricultural product, the new blended product including at least one additional agricultural product in combination with the agricultural product. 2. The method of claim 1 , further comprising: storing data about the spectral fingerprint within a computer storage means. 3. The method of claim 2 , further comprising: utilizing the data to form the new blended product. 4. The method of claim 1 , further comprising: forming a spectral library within a computer storage means containing spectral fingerprints for a plurality of blended agricultural products. 5. The method of claim 1 , further comprising: determining a physicochemical code for the sample. 6. The method of claim 1 , wherein the light source is positioned to reduce an angle of incidence of each beam of light with the sample. 7. The method of claim 1 , wherein the light source includes a light source having different wavelengths. 8. The method of claim 1 , wherein the light source for providing a beam of light includes a light source including a tungsten light source, a halogen light source, a xenon light source, a mercury light source, an ultraviolet light source, or any combination thereof. 9. The method of claim 1 , further comprising: correlating one or more features of the spectral fingerprint to a cost of the sample. 10. The method of claim 9 , wherein the cost of the sample is an independent parameter in the determining blending parameters for the new blended product. 11. The method of claim 1 , wherein the light source includes multiple light sources. 12. The method of claim 11 , wherein the multiple light sources includes a first light source having a first wavelength and a second light source having a second wavelength, and wherein the first wavelength is different from the second wavelength. 13. The method of claim 11 , wherein the light source includes a xenon light source, a mercury light source, and an ultraviolet light source. 14. The method of claim 1 , further comprising: obtaining a dark image and a reference image of the multiple regions. 15. The method of claim 1 , wherein the scanning is in an enclosure segregated from ambient light.
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