IP Library › Granted Patent US 12,307,310
Granted Patent B2
US 12,307,310 · App. 18/616,267 · Granted May 20, 2025

System and method using a histogram and colorspaces to create a matrix barcode having a plurality of colors

Inventors: Austin Grant Walters (Savoy, IL); Jeremy Edward Goodsitt (Champaign, IL); Fardin Abdi Taghi Abad (Champaign, IL)
Assignee: Capital One Services, LLC
G06K19/06037G06K7/1417G06T5/40G06T7/90G06V10/50G06V10/507G06V10/56G06K2019/06225G06T2207/10016G06T2207/10024G06T2207/20072G06T2207/30208
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,307,310
App. No.
18/616,267
Granted
May 20, 2025
Kind
B2
Abstract

A computer-implemented method includes determining, by a processor based on a histogram of an environment, a most prevalent color of a plurality of prevalent colors associated with the environment by mapping the most prevalent color and the plurality of prevalent colors according to a red-green-blue (RGB) colorspace. The processor determines a related plurality of colors by determining at least one set of color coordinates for each one of the most prevalent color and the plurality of prevalent colors according to the another colorspace and determines at least one set of color coordinates for the related plurality of colors according to the another colorspace. A matrix barcode is generated using the related plurality of colors.

Claims (36)

1. A computer-implemented method, comprising:

determining, by a processor based on a histogram of an environment, a most prevalent color of a plurality of prevalent colors associated with the environment by mapping the most prevalent color and the plurality of prevalent colors according to a red-green-blue (RGB) colorspace;

determining, by the processor based on the histogram and another colorspace, a related plurality of colors by determining at least one set of color coordinates for each one of the most prevalent color and the plurality of prevalent colors according to the another colorspace and determining at least one set of color coordinates for the related plurality of colors according to the another colorspace; and

generating, by the processor, a matrix barcode using the related plurality of colors.

2. The computer-implemented method of claim 1 , wherein the related plurality of colors include at least one of an absent color in relation to the environment or a least prevalent color associated with the environment.

3. The computer-implemented method of claim 1 , wherein the histogram of the environment is based on one or more images of the environment.

4. The computer-implemented method of claim 3 , further comprising:

generating the histogram of the environment based on the one or more images of the environment.

5. The computer-implemented method of claim 1 , wherein the another colorspace includes a luminance channel, the method further comprising:

removing the luminance channel from the another colorspace.

6. The computer-implemented method of claim 5 , wherein removal of the luminance channel generates the color coordinates according to the another colorspace.

7. The computer-implemented method of claim 1 , wherein the matrix barcode is embedded with data, wherein the data is represented by a plurality of pixels associated with the related plurality of colors.

8. The computer-implemented method of claim 7 , wherein the plurality of pixels are associated with at least three color-channels forming the matrix barcode.

9. The computer-implemented method of claim 1 , wherein the matrix barcode is a fiducial marker for conveying spatial information.

10. The computer-implemented method of claim 1 , wherein the another colorspace is different than the RGB colorspace.

11. A non-transitory computer-readable storage medium, the computer-readable storage medium including instructions that when executed by a processor, cause the processor to:

determine, based on a histogram of an environment, a most prevalent color of a plurality of prevalent colors associated with the environment by mapping the most prevalent color and the plurality of prevalent colors according to a red-green-blue (RGB) colorspace;

determine, based on the histogram and another colorspace, a related plurality of colors by determining at least one set of color coordinates for each one of the most prevalent color and the plurality of prevalent colors according to the another colorspace and determining at least one set of color coordinates for the related plurality of colors according to the another colorspace; and

generate a matrix barcode using the related plurality of colors.

12. The computer-readable storage medium of claim 11 , wherein the related plurality of colors include at least one of an absent color in relation to the environment or a least prevalent color associated with the environment.

13. The computer-readable storage medium of claim 11 , wherein the histogram of the environment is based on one or more images of the environment.

14. The computer-readable storage medium of claim 13 , wherein the instructions further cause the processor to:

generate the histogram of the environment based on the one or more images of the environment.

15. The computer-readable storage medium of claim 11 , wherein the another colorspace includes a luminance channel, wherein the instructions further cause the processor to:

remove the luminance channel from the another colorspace.

16. The computer-readable storage medium of claim 15 , wherein removal of the luminance channel generates the color coordinates according to the another colorspace.

17. A computing apparatus comprising:

a processor; and

a memory storing instructions that, when executed by the processor, cause the processor to:

determine, based on a histogram of an environment, a most prevalent color of a plurality of prevalent colors associated with the environment by mapping the most prevalent color and the plurality of prevalent colors according to a red-green-blue (RGB) colorspace;

determine, based on the histogram and another colorspace, a related plurality of colors by determining at least one set of color coordinates for each one of the most prevalent color and the plurality of prevalent colors according to the another colorspace and determining at least one set of color coordinates for the related plurality of colors according to the another colorspace; and

generate a matrix barcode using the related plurality of colors.

18. The computing apparatus of claim 17 , wherein the related plurality of colors include at least one of an absent color in relation to the environment or a least prevalent color associated with the environment.

19. The computing apparatus of claim 17 , wherein the histogram of the environment is based on one or more images of the environment.

20. The computing apparatus of claim 17 , wherein the another colorspace includes a luminance channel, wherein the instructions further cause the processor to:

remove the luminance channel from the another colorspace.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 9, 2024
From: WALTERS, AUSTIN GRANT; GOODSITT, JEREMY EDWARD; ABDI TAGHI ABAD, FARDIN
To: CAPITAL ONE SERVICES, LLC
Reel/Frame 067046/0650 →
Continuity (6)
Continuation 18120571 · Mar 13, 2023
Continuation 17706758 · Mar 29, 2022
Division 17011283 · Sep 3, 2020
Continuation 16690064 · Nov 20, 2019
Division 16357231 · Mar 18, 2019
Related Publication 20240232563A1 · Jul 11, 2024
References Cited (23)
US 8079525B1 · Zolotov · 2011 [cited by examiner]
US 10496862B1 · Walters · 2019 [cited by examiner]
US 10496911B1 · Walters · 2019 [cited by examiner]
US 10509991B1 · Walters · 2019 [cited by examiner]
US 10529300B1 · Walters · 2020 [cited by examiner]
US 10534948B1 · Walters · 2020 [cited by examiner]
US 10614635B1 · Walters · 2020 [cited by examiner]
US 10867226B1 · Walters · 2020 [cited by examiner]
US 11024256B2 · Walters · 2021 [cited by examiner]
US 11302036B2 · Walters et al. · 2022 [cited by applicant]
US 11645787B2 · Walters et al. · 2023 [cited by applicant]
US 11720776B2 · Walters · 2023 [cited by examiner]
US 11798194B2 · Walters · 2023 [cited by examiner]
US 11799484B2 · Walters · 2023 [cited by examiner]
US 11954545B2 · Walters · 2024 [cited by examiner]
US 11961267B2 · Walters et al. · 2024 [cited by applicant]
US 20040197021A1 · Huang · 2004 [cited by examiner]
US 20190371433A1 · Wang et al. · 2019 [cited by applicant]
US 20210241522A1 · Guler et al. · 2021 [cited by applicant]
US 20220058835A1 · Walters et al. · 2022 [cited by applicant]
US 20220198718A1 · Walters et al. · 2022 [cited by applicant]
JP 2017016635A · 2017 [cited by applicant]
KR 20120013405A · 2012 [cited by applicant]