US 12,239,078 B2
Ripeness detection system using hue color space and peak finding
Ryan R. Knopf, Morehead, KY (US); and Joshua Aaron Lessing, Morehead, KY (US)
Assigned to ZORDI, INC., Boston, MA (US)
Appl. No. 17/430,771
Filed by APPHARVEST TECHNOLOGY, INC., Morehead, KY (US)
PCT Filed Feb. 14, 2020, PCT No. PCT/US2020/018395
§ 371(c)(1), (2) Date Aug. 13, 2021,
PCT Pub. No. WO2020/168264, PCT Pub. Date Aug. 20, 2020.
Claims priority of provisional application 62/806,492, filed on Feb. 15, 2019.
Prior Publication US 2022/0164989 A1, May 26, 2022
Int. Cl. G06T 7/90 (2017.01); A01H 6/54 (2018.01); G01N 21/95 (2006.01); G06T 7/44 (2017.01); G06V 20/68 (2022.01)
CPC A01H 6/542 (2018.05) [G01N 21/95 (2013.01); G06T 7/44 (2017.01); G06T 7/90 (2017.01); G06V 20/68 (2022.01); G06F 2218/14 (2023.01); G06T 2207/10024 (2013.01)] 26 Claims
OG exemplary drawing
 
1. A method for estimating ripeness of produce, the method comprising:
illuminating the produce with light;
measuring intensities of the light reflected from the produce at different frequencies;
selecting, by a convolutional neural network, a cropped region of an image of the produce, wherein the cropped region of the image of the produce is selected such that an image of a target item of produce within the cropped region of the image of the produce occupies more than 50% of the cropped region by an area and such that the target item of produce is less than 50% occluded by an object within the cropped region of the image of the produce;
converting the cropped region of the image to a hue, saturation, and value (HSV) color representation;
constructing a hue histogram of hues in the cropped region of the image; and
determining a degree of ripeness of the target item of produce from both the intensities of the light reflected from the produce at the different frequencies and a dominant peak in the hue histogram.