IP Library › Granted Patent US 12711794
Granted Patent B1
US 12711794 · App. 18/408,036 · Granted Aug 18, 2026

Label capture using optical pattern recognition and barcode semantics

Inventors: Christian Kündig (Zürich, CH); Oliver Akermann (Zürich, CH); Bernd Schoner (New York, NY); Luc Humair (Zürich, CH); Luis Haug (Zürich, CH); Marco Maggipinto (Zürich, CH)
Assignee: Scandit AG
G06V30/148G06V30/1801G06K19/06028
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Quick Facts
Patent No.
US 12711794
App. No.
18/408,036
Granted
Aug 18, 2026
Kind
B1
Abstract

One or more images of a real scene are analyzed to identify a plurality of text fields and one or more barcodes. A plurality of edges are defined, wherein each edge of the plurality of edges links a text field of the plurality of text fields with a barcode of the one or more barcodes. The plurality of edges are used to match a text field with a barcode to classify the barcode.

Claims (47)

1 . A system for image analysis of optical patterns in a real scene, the system comprising:

a camera; and

one or more computer-readable media comprising instructions that, when executed by one or more processors, perform the following steps:

receiving one or more images of a scene acquired by the camera;

performing image processing on an image of the one or more images to computationally identify boundaries for a plurality of text fields within the

image and for one or more barcodes within the image;

constructing a data graph that represents spatial relationships between the plurality of text fields and the one or more barcodes, wherein the data graph comprises a plurality of edges, wherein each edge of the plurality of edges links a text field node associated with a text field of the plurality of text fields with a barcode node associated with a barcode of the one or more barcodes, and wherein the data graph is constructed based on the boundaries; and

analyzing the data graph to identify a correct match between a text field of the plurality of text fields and a corresponding barcode of the one or more barcodes, and in response to identifying the correct match, automatically decoding the corresponding barcode to extract its data.

2 . The system of claim 1 , wherein analyzing the data graph comprises analyzing the plurality of edges.

3 . The system of claim 2 , wherein the correct match is identified without decoding any text field of the plurality of text fields or any barcode of the one or more barcodes.

4 . The system of claim 1 , wherein analyzing the data graph comprises ascertaining that an edge of the plurality of edges fails to define a one-to-one match between a text field of the plurality of text fields and a barcode of the one or more barcodes.

5 . A method for image analysis of optical patterns in a real scene, the method comprising:

receiving one or more images of a scene acquired by a camera;

performing image processing on an image of the one or more images to computationally identify boundaries for a plurality of text fields within the

image and for one or more barcodes within the image; and

constructing a data graph that represents spatial relationships between the plurality of text fields and the one or more barcodes, wherein the data graph comprises a plurality of edges, wherein each edge of the plurality of edges links a text field node associated with a text field of the plurality of text fields with a barcode node associated with a barcode of the one or more barcodes, and wherein the data graph is constructed based on the boundaries; and

analyzing the data graph to identify a correct match between a text field of the plurality of text fields and a corresponding barcode of the one or more barcodes, and in response to identifying the correct match, automatically decoding the corresponding barcode to extract its data.

6 . The method of claim 5 , wherein analyzing the data graph comprises analyzing the plurality of edges.

7 . The method of claim 6 , wherein the correct match is identified without decoding any text field of the plurality of text fields or any barcode of the one or more barcodes.

8 . The method of claim 5 , wherein analyzing the data graph comprises ascertaining that an edge of the plurality of edges defines a one-to-one match between a text field of the plurality of text fields and a barcode of the one or more barcodes.

9 . The method of claim 5 , wherein analyzing the data graph comprises ascertaining that an edge of the plurality of edges fails to define a one-to-one match between a text field of the plurality of text fields and a barcode of the one or more barcodes.

10 . The method of claim 9 , further comprising:

comparing nodes of the plurality of edges to a predefined threshold, based on ascertaining that an edge of the plurality of edges fails to define the one-to-one match between the text field of the plurality of text fields and a barcode of the one or more barcodes; and

deleting edges that fail to meet the predefined threshold.

11 . The method of claim 9 , further comprising:

decoding one or more of the plurality of text fields, based on the ascertaining that the edge of the plurality of edges fails to define the one-to-one match between the text field of the plurality of text fields and a barcode of the one or more barcodes;

decoding the one or more barcodes to develop one or more character strings, based on the ascertaining that the edge of the plurality of edges fails to define the one-to-one match between the text field of the plurality of text fields and a barcode of the one or more barcodes; and

matching a barcode of the one or more barcodes to a text field of the one or more of the plurality of text fields based on text and/or format of a character string of the barcode matching a text and/or expected format of the text field.

12 . The method of claim 9 , further comprising mapping one barcode to multiple text fields.

13 . A non-transitory computer-readable storage medium comprising instructions that, when executed by one or more processors, perform the following steps for image analysis of optical patterns in a real scene:

receiving one or more images of a scene acquired by a camera;

performing image processing on an image of the one or more images to computationally identify boundaries for a plurality of text fields within the

image and for one or more barcodes within the image;

constructing a data graph that represents spatial relationships between the plurality of text fields and the one or more barcodes, wherein the data graph comprises a plurality of edges, wherein each edge of the plurality of edges links a text field node associated with a text field of the plurality of text fields with a barcode node associated with a barcode of the one or more barcodes, and wherein the data graph is constructed based on the boundaries; and

analyzing the data graph to identify a correct match between a text field of the plurality of text fields and a corresponding barcode of the one or more barcodes, and in response to identifying the correct match, automatically decoding the corresponding barcode to extract its data.

14 . The non-transitory computer-readable storage medium of claim 13 , wherein analyzing the data graph comprises analyzing the plurality of edges.

15 . The non-transitory computer-readable storage medium of claim 14 , wherein the correct match is identified without decoding any text field of the plurality of text fields or any barcode of the one or more barcodes.

16 . The non-transitory computer-readable storage medium of claim 13 , wherein analyzing the data graph comprises ascertaining that an edge of the plurality of edges defines a one-to-one match between a text field of the plurality of text fields and a barcode of the one or more barcodes.

17 . The non-transitory computer-readable storage medium of claim 13 , wherein analyzing the data graph comprises ascertaining that an edge of the plurality of edges fails to define a one-to-one match between a text field of the plurality of text fields and a barcode of the one or more barcodes.

18 . The non-transitory computer-readable storage medium of claim 17 , wherein the instructions, when executed by the one or more processors, further perform the following steps:

comparing nodes of the plurality of edges to a predefined threshold, based on ascertaining that an edge of the plurality of edges fails to define the one-to-one match between the text field of the plurality of text fields and a barcode of the one or more barcodes; and

deleting edges that fail to meet the predefined threshold.

19 . The non-transitory computer-readable storage medium of claim 17 , wherein the instructions, when executed by the one or more processors, further perform the following steps:

decoding one or more of the plurality of text fields, based on the ascertaining that the edge of the plurality of edges fails to define the one-to-one match between the text field of the plurality of text fields and a barcode of the one or more barcodes;

decoding the one or more barcodes to develop one or more character strings, based on the ascertaining that the edge of the plurality of edges fails to define the one-to-one match between the text field of the plurality of text fields and a barcode of the one or more barcodes; and

matching a barcode of the one or more barcodes to a text field of the one or more of the plurality of text fields based on text and/or format of a character string of the barcode matching a text and/or expected format of the text field.

20 . The non-transitory computer-readable storage medium of claim 17 , wherein the instructions, when executed by the one or more processors, further perform the following step of mapping one barcode to multiple text fields.