IP Library Granted Patent US 12,277,669
Granted Patent B2
US 12,277,669 · App. 17/744,900 · Granted Apr 15, 2025

Devices, systems and methods for digital image analysis

Inventors: Douglas Karcher (Fayetteville, AR); Carlin Purcell (Fayetteville, AR); Kenneth Hignight (Jefferson, OR)
Assignee: NEXGEN Plant Science Center, LLC
G06T3/40G06T7/0004G06T7/11G06T7/90G06T7/41G06T2207/30108
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Quick Facts
Patent No.
US 12,277,669
App. No.
17/744,900
Granted
Apr 15, 2025
Kind
B2
Abstract

The disclosed devices, systems and methods relate to various devices, systems and methods related to objectively analyzing digital images of turfgrass to rate various parameters and to objectively measure overall quality. The system establishes thresholds and may execute a series of steps to determine green coverage, color, density, and uniformity. The system can scale images to determine uniformity.

Claims (42)

1. A turfgrass analyzing system comprising:

(a) a storage configured for storage of one or more digital images, each digital image comprising a green coverage parameter, a color parameter, a density parameter, and a uniformity parameter; and

(b) a processor in communication with the storage device,

wherein the processor is constructed and arranged to analyze green coverage, color, density of turfgrass, and uniformity in each digital image.

2. The system of claim 1 , further comprising a set of threshold values selected to identify pixels containing turfgrass.

3. The system of claim 2 , wherein the set of threshold values can be set to remove pixels from the one or more digital images of turfgrass.

4. The system of claim 2 , wherein each of the one or more digital images of turfgrass contains a contrasting frame.

5. The system of claim 2 , further comprising a database in communication with the processor and wherein the system is constructed and arranged to execute machine learning on data stored in the database.

6. The system of claim 5 , wherein overall turfgrass quality is determined from a weighted average of the green coverage, color, density of turfgrass, and uniformity.

7. A method for digital image analysis comprising:

receiving a digital image of turfgrass comprising a green coverage, a color, a density of turfgrass, and a uniformity;

retrieving by a processor the digital image;

processing on the processor the digital image by executing one or more steps to determine green coverage, color, density of turfgrass, and uniformity within the digital image.

8. The method of claim 7 , further comprising scaling the digital image.

9. The method of claim 8 , further comprising determining overall turfgrass quality from the green coverage, color, density of turfgrass, and uniformity.

10. The method of claim 7 , wherein green coverage is determined by:

setting a set of threshold values;

removing pixels outside of the set of threshold values; and

determining the number of green pixels relative to the total number of pixels.

11. The method of claim 7 , wherein color is determined by calculating the average DGCI value for the image.

12. The method of claim 7 , wherein density of turfgrass is determined by calculating the number of shadows in the digital image.

13. The method of claim 7 , wherein uniformity is determined by:

scaling the digital image;

grouping areas of similar color in the scaled image; and

comparing the areas of similar color to the digital image.

14. A turfgrass analysis device comprising:

(a) a storage device;

(b) a processor in communication with the storage device; and

(c) a display in communication with the processor,

wherein the processor retrieves a digital image from the storage device, wherein the processor is configured to calculate turfgrass quality from green coverage, color, density of turfgrass, and uniformity of the digital image, and wherein the processor displays the digital image and turfgrass quality on the display.

15. The device of claim 14 , wherein the digital image contains a contrasting frame.

16. The device of claim 14 , wherein turfgrass quality is determined by a weighted average of measurements of green coverage, color, density of turfgrass, and uniformity.

17. The device of claim 16 , wherein coverage is determined by

setting a set of threshold values;

removing pixels outside of the set of threshold values; and

determining the number of green pixels relative to the total number.

18. The device of claim 16 , wherein color is determined by calculating the average DGCI value for the image.

19. The device of claim 16 , wherein density of turfgrass is determined by determining the number of shadows in the digital image.

20. The device of claim 16 , wherein uniformity is determined by:

scaling the digital image;

grouping areas of similar color in the scaled image; and

comparing the areas of similar color to the digital image.

Assignments (2)
SECURITY INTEREST Recorded Nov 19, 2025
From: CENTRAL GARDEN & PET COMPANY; FOUR PAWS PRODUCTS, LTD.; IMS TRADING, LLC; K&H MANUFACTURING, LLC; NEXGEN PLANT SCIENCE CENTER, LLC; T.F.H. PUBLICATIONS, INC.; WELLMARK INTERNATIONAL
To: TRUIST BANK
Reel/Frame 073604/0698 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 27, 2023
From: KARCHER, DOUGLAS; PURCELL, CARLIN; HIGNIGHT, KENNETH
To: NEXGEN TURF RESEARCH, LLC
Reel/Frame 064407/0310 →
Continuity (3)
Continuation 16168531 · Oct 23, 2018
Provisional Application 62575710 · Oct 23, 2017
Related Publication 20220270206A1 · Aug 25, 2022
References Cited (8)
US 11334963B2 · Karcher · 2022 [cited by examiner]
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US 20140226900A1 · Saban · 2014 [cited by examiner]
US 20170208248A1 · Mowry · 2017 [cited by examiner]
Karcher et al., “Batch Analysis of Digital Images to Evaluate Turfgrass Characteristics”, Crop Science, Jun. 24, 2005, pp. 1536-1539, vol. 45. [cited by applicant]
Karcher et al., “Quantifying Turfgrass Color Using Digital Image Analysis”, Crop Science, May 1, 2003, pp. 944-951, vol. 43. [cited by applicant]
Richardson et al., “Quantifying Turfgrass Cover Using Digital Image Analysis”, Crop Science, Nov. 1, 2001, pp. 1884-1888, vol. 41. [cited by applicant]
Zhang et al., “Evaluation of Key Methodology for Digital Image Analysis of Turfgrass Color Using Open-Source Software”, Crop Science, Mar. 1, 2017, pp. 550-558, vol. 57. [cited by applicant]