IP Library Granted Patent US 11,922,259
Granted Patent B2
US 11,922,259 · App. 17/810,613 · Granted Mar 5, 2024

Universal product labeling for vision-based commerce

Inventor: William Glaser (Berkeley, CA)
Assignee: Grabango Co.
G06K7/10722G06K7/1417
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 11,922,259
App. No.
17/810,613
Granted
Mar 5, 2024
Kind
B2
Abstract

A system and method for computer vision assisted physical-labels functions to use functional, large format product labeling for better computer vision (CV) identification. The product labels and detection capabilities of the system and method enhance product label detection and interpretation for use with image sensing at a distance. The product labels are non-obtrusive and can mitigate changes to sizing or visual appearance of packaging of goods or products. The system and method can enable universal product labeling for vision-based commerce and other applications.

Claims (46)

1. A method for sensor detectable physical labels comprising:

receiving a product identifier of a product;

encoding a partial product identifier into a graphical machine-readable code, wherein the partial product identifier is unique for a local classification group and is associated with the product identifier;

at the imaging devices of the imaging system, collecting image data;

detecting, by processing the image data using a code detection computer vision model, an imaged product label with an imaged graphic machine readable code;

decoding the imaged graphic machine-readable code into an imaged partial identifier;

determining a classification group of the imaged product label; and

compiling a product identifier output from the imaged partial identifier and the classification group of the imaged product label.

2. The method of claim 1 , wherein the graphical machine-readable code is defined through an arrangement of graphical data elements in different states, and wherein each graphical data element is sized in the physical product label greater than one centimeter in one dimension.

3. The method of claim 1 , wherein the graphical machine-readable code is defined through an arrangement of graphical data elements in different states, and wherein graphical data elements are each in one of a set of three or more color states.

4. The method of claim 1 , wherein the classification group is based on location; wherein determining a classification group of the imaged product label comprises determining location of the imaged graphic machine readable code and selecting the classification group of the imaged product label based on the location of the imaged graphic machine readable code.

5. The method of claim 1 , wherein the partial product identifier represents a weight property.

6. The method of claim 1 , further comprising storing a data record in a product label management data system, where the data record associates the partial product identifier to the product identifier.

7. The method of claim 6 , further comprising detecting, through processing of image data, the product satisfying an end of use condition and in response updating the product label management system to free usage of the partial product identifier for a new product identifier.

8. The method of claim 1 , wherein determining a classification group of the imaged product label may include: detecting, through processing of the image data using a computer vision model, a product property, wherein the product property is associated with the local classification group.

9. The method of claim 1 , wherein determining a classification group of the imaged product label comprises: detecting, through processing of the image data using a computer vision model, a classifier graphical code and decoding the classifier graphical code into an identifier of the classification group thereby determining the classification group.

10. The method of claim 1 , further comprising applying the product label to the product.

11. The method of claim 1 , wherein the partial product identifier represents a price property.

12. A system for product label detection comprising:

a computer vision monitoring system with a plurality of imaging devices distributed in an environment, the computer vision monitoring system configured to collect image data;

a label management system comprising one or more computer-readable mediums storing instructions that, when executed by the one or more computer processors, cause a computing platform to perform operations comprising:

receiving a product identifier of a product;

encoding a partial product identifier into a graphical machine-readable code, wherein the partial product identifier is unique for a local classification group and is associated with the product identifier;

detecting, by processing the image data using a code detection computer vision mode, an imaged product label with an imaged graphic machine readable code;

decoding the imaged graphic machine-readable code into an imaged partial identifier;

determining a classification group of the imaged product label; and

compiling a product identifier output from the imaged partial identifier and the classification group of the imaged product label.

13. The system of claim 12 , wherein the graphical machine-readable code is defined through an arrangement of graphical data elements in different states, and wherein each graphical data element is sized in the physical product label greater than one centimeter in one dimension.

14. The system of claim 12 , wherein the classification group is based on location; wherein determining a classification group of the imaged product label comprises determining location of the imaged graphic machine readable code and selecting the classification group of the imaged product label based on the location of the imaged graphic machine readable code.

15. The system of claim 12 , further comprising storing a data record in a product label management data system, where the data record associates the partial product identifier to the product identifier.

16. The system of claim 15 , further comprising detecting, through processing of image data, the product satisfies an end of use condition and in response updating the product label management system to free usage of the partial product identifier for a new product identifier.

17. The system of claim 12 , wherein the partial product identifier represents one of a price property or a weight property.

18. A non-transitory computer-readable medium storing instructions that, when executed by one or more computer processors of a computing platform, cause the computing platform to:

receiving a product identifier of a product;

encoding a partial product identifier into a graphical machine-readable code wherein the partial product identifier is unique for a local classification group and is associated with the product identifier;

at the imaging devices of the imaging system, collecting image data;

detecting, by processing the image data using a code detection computer vision model, an imaged product label with an imaged graphic machine readable code;

decoding the imaged graphic machine-readable code into an imaged partial identifier;

determining a classification group of the imaged product label; and

compiling a product identifier output from the imaged partial identifier and the classification group of the imaged product label.

19. The non-transitory computer-readable medium of claim 18 , wherein the graphical machine-readable code is defined through an arrangement of graphical data elements in different states, and wherein each graphical data element is sized in the physical product label greater than one centimeter in one dimension.

20. The non-transitory computer-readable medium of claim 18 , wherein the graphical machine-readable code is defined through an arrangement of graphical data elements in different states, and wherein graphical data elements are each in one of a set of three or more color states.

21. The non-transitory computer-readable medium of claim 18 , wherein the classification group is based on location; wherein determining a classification group of the imaged product label comprises determining location of the imaged graphic machine readable code and selecting the classification group of the imaged product label based on the location of the imaged graphic machine readable code.

22. The non-transitory computer-readable medium of claim 18 , further comprising storing a data record in a product label management data system, where the data record associates the partial product identifier to the product identifier.

23. The non-transitory computer-readable medium of claim 22 , further comprising detecting, through processing of image data, the product satisfies an end of use condition and in response updating the product label management system to free usage of the partial product identifier for a new product identifier.

24. The non-transitory computer-readable medium of claim 18 , wherein the partial product identifier represents one of a price property or a weight property.

Assignments (4)
SECURITY INTEREST Recorded Sep 9, 2024
From: GRABANGO CO.
To: GLICKBERG, DANIEL
Reel/Frame 068901/0799 →
SECURITY INTEREST Recorded Jun 5, 2024
From: GRABANGO CO.
To: FIRST-CITIZEN BANK & TRUST COMPANY
Reel/Frame 067637/0231 →
SECURITY INTEREST Recorded Jun 4, 2024
From: GRABANGO CO.
To: GLICKBERG, DANIEL
Reel/Frame 067611/0150 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 28, 2023
From: GLASER, WILLIAM
To: GRABANGO CO.
Reel/Frame 065676/0418 →
Continuity (3)
Continuation 17322105 · May 17, 2021
Provisional Application 63025655 · May 15, 2020
Related Publication 20230004736A1 · Jan 5, 2023