# US 11,308,303 B2 · Using barcodes to determine item dimensions

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- Number: US 11,308,303 B2
- Document ID: US11308303B2
- Status: Granted
- Kind: B2
- Application number: 16/888,387
- Filed: 2020-05-29
- Published: 2021-12-02
- Granted: 2022-04-19
- Earliest claimed: 2020-05-29
- Assignees: Zebra Technologies Corporation
- Applicants: Zebra Technologies Corporation
- Inventors: Charles Burton Swope; Edward Barkan; Mark Drzymala; Darran Michael Handshaw
- Web page: https://patentgrep.com/patent/US11308303B2

## CPC

- G06K 7/1456: {determining the orientation of the optical code with respect to the reader and correcting therefore}
- G06K 7/10722: {Photodetector array or CCD scanning}
- G06K 7/1404: {Methods for optical code recognition}
- G06K 7/1413: {1D bar codes}
- G06K 7/1417: {2D bar codes}
- G06K 7/1443: {locating of the code in an image}
- G07G 1/0054: {with control of supplementary check-parameters, e.g. weight or number of articles}
- G06K: GRAPHICAL DATA READING (image or video recognition or understanding G06V); PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G07G: REGISTERING THE RECEIPT OF CASH, VALUABLES, OR TOKENS

## Abstract

Methods and systems for using barcodes to determine item dimensions are disclosed herein. An example method includes a scanner identifying a barcode in an image of an object, and determining a datum associated with the barcode. A physical feature of the object located outside of the barcode is identified. A comparison of the datum associated with the barcode to the physical feature is made; and, in response, at least one dimension of the object is determined.

## Claims

### Claim 1

A method for improper object detection using a barcode reader, the method comprising:
identifying a barcode in an image of an object;
determining a datum associated with the barcode;
identifying a visual feature of the object located outside of the barcode;
comparing the datum associated with the barcode to the visual feature and, in response, determining at least one dimension characteristic of the object; and
in response to determining the at least one dimension characteristic, comparing the at least one dimension characteristic to at least one reference dimension characteristic of the object, and in response to a mismatch between the at least one dimension characteristic and the at least one reference dimension characteristic, determining an improper object detection event has occurred;
wherein the visual feature comprises one or more of a physical feature or a printed feature.

### Claim 2 (depends on 1)

The method of claim 1, wherein determining the datum comprises:
determining a dimension of the barcode as the datum.

### Claim 3 (depends on 2)

The method of claim 2, wherein the dimension of the barcode is a length of the barcode, a length of an element portion of the barcode, or a boundary dimension of the barcode.

### Claim 4 (depends on 2)

The method of claim 2, wherein determining the datum comprises:
identifying a boundary of the barcode in the image;
determining, from the boundary, if the barcode in the image is in a geometrically aligned position; and
in response to the boundary not being in a geometrically aligned position, performing a geometric transformation on the boundary and determining the datum from a geometrically transformed boundary.

### Claim 5 (depends on 4)

The method of claim 4, wherein the geometric transformation is a geometric rotation of the boundary, a geometric translation of the boundary, a geometric resizing of the boundary, and/or geometric tilt rectification on the boundary.

### Claim 6 (depends on 4)

The method of claim 4, further comprising determining, from the geometric transformation, a dimension of visual feature of the object located outside of the barcode.

### Claim 7 (depends on 1)

The method of claim 1, wherein determining the datum comprises:
determining a type of the barcode; and
determining a dimension of the barcode from the type of barcode, the dimension being the datum associated with the barcode.

### Claim 8 (depends on 7)

The method of claim 7, wherein the type of barcode is selected from the group consisting of 80% UPC, 100% UPC, a QR code, a 1D barcode, a 2D barcode, a Digimarc, and a 2D data matrix.

### Claim 9 (depends on 1)

The method of claim 1, wherein the visual feature is an edge of the object, an edge of a label containing at least a portion of the barcode, or a graphic on the object.

### Claim 10 (depends on 9)

The method of claim 9, wherein the datum is a dimension of the barcode, and wherein comparing the datum to the visual feature comprises:
determining a geometric distance between the datum and the visual feature.

### Claim 11 (depends on 9)

The method of claim 9, wherein the graphic on the object is text on the object.

### Claim 12 (depends on 1)

The method of claim 1, wherein the visual feature is a curvature of the object, and wherein comparing the datum to the visual feature comprises: comparing a dimension of the barcode to the curvature of the object.

### Claim 13 (depends on 1)

The method of claim 1, wherein determining the datum associated with the barcode comprises:
determining a density of the barcode; and
determining a dimension of the barcode from the barcode density.

### Claim 14 (depends on 1)

The method of claim 1, wherein determining the datum associated with the barcode comprises:
decoding a payload of the barcode; and
determining a dimension of the barcode from the payload.

### Claim 15 (depends on 1)

The method of claim 1, further comprising:
in response to determining the improper object detection event has occurred, communicating an alarm signal.

### Claim 16 (depends on 1)

The method of claim 1, further comprising:
in response to determining the at least one dimension characteristic, determining if there is at least one reference dimension characteristic of the object to compare with the at least one dimension characteristic, and in response to determining that there is not at least one reference dimension characteristic to compare, storing the at least one dimension characteristic in a reference dimension characteristic model for the object.

### Claim 17 (depends on 1)

The method of claim 1, further comprising, prior to the comparing the at least one dimension characteristic to at least one reference dimension characteristic of the object:
identifying and decoding a payload of the barcode;
identifying the at least one reference dimension characteristic from the decoded payload; and
determining that the at least one dimension characteristic corresponds to the at least one reference dimension characteristic.

### Claim 18 (depends on 1)

The method of claim 1, wherein the at least one dimension characteristic includes at least one of:
an outer dimension of the object;
a position of a label on the object;
a position of text on the object; and
an internal dimension of the object.

### Claim 19 (depends on 1)

The method of claim 1, further comprising:
recognizing a character in proximity to the barcode;
determining a position of the character based on the datum; and
using an optical character recognition (OCR) technique to at least one of:
store the character and position in a reference model; and
compare the character data to similarly positioned character data stored in a reference model.

### Claim 20 (depends on 1)

The method of claim 1, wherein the at least one reference dimension characteristic is part of a reference model, and wherein the method further comprises:
checking the reference model for a visual feature of the reference model;
examining the image of the object for the visual feature, and not finding the visual feature of the reference model in the examined image; and
in response to not finding the visual feature of the reference model in the examined image, generating an alarm.

### Claim 21 (depends on 1)

The method of claim 1, wherein each of the steps are performed by a barcode reader.

### Claim 22

A method for improper object detection, and developing a reference dimension model for an object, the method comprising:
a) identifying a barcode in an image of an object;
b) determining at least one datum associated with the barcode;
c) identifying a plurality of visual features of the object, each visual feature located outside of the barcode, wherein the plurality of visual features comprises physical features or printed features;
d) comparing the at least one datum associated with the barcode to the visual features and determining a plurality of dimension characteristics for the object;
e) storing the plurality of dimension characteristics as the reference dimension model; and
f) determining that an improper object detection event has occurred by: (i) comparing a dimension characteristic of the plurality of dimension characteristics to a dimension characteristic of a detected object, and (ii) determining a mismatch between the dimension characteristic of the plurality of dimensions characteristics and the dimension characteristic of the detected object.

### Claim 23 (depends on 22)

The method of claim 22, wherein the at least one datum comprises a length of the barcode, a length of an element portion of the barcode, or a boundary dimension of the barcode.

### Claim 24 (depends on 22)

The method of claim 22, wherein determining the at least one datum comprises:
identifying a boundary of the barcode in the image;
determining, from the boundary, if the barcode in the image is in a geometrically aligned position; and
in response to the boundary not being in a geometrically aligned position, performing a geometric transformation on the boundary and determining the datum from a geometrically transformed boundary.

### Claim 25 (depends on 24)

The method of claim 24, wherein the geometric transformation is a geometric rotation of the boundary, a geometric translation of the boundary, a geometric resizing of the boundary, and/or geometric tilt rectification on the boundary.

### Claim 26 (depends on 24)

The method of claim 24, wherein the plurality of visual features are selected from the group consisting of an edge of the object, an edge of a label containing at least a portion of the barcode, and a graphic on the object.

### Claim 27 (depends on 24)

The method of claim 24, further comprising performing a), b), and c) for a subsequent image of the object or of another object, the method further comprising:
determining subsequent values for any of the plurality of dimensions;
determining variation tolerances for any of the plurality of dimensions; and
storing the variation tolerances in the reference dimension model.

### Claim 28 (depends on 22)

The method of claim 22, wherein the steps are performed by a barcode reader.

### Claim 29

An electronic device for improper object detection using a barcode reader, electronic device comprising a housing including a controller, wherein the controller is configured to:
identify a barcode in an image of an object;
determine a datum associated with the barcode;
identify a visual feature of the object located outside of the barcode;
compare the datum associated with the barcode to the visual feature and, in response, determine at least one dimension characteristic of the object; and
in response to the determination that the at least one dimension characteristic, compare the at least one dimension characteristic to at least one reference dimension characteristic of the object, and in response to a mismatch between the at least one dimension characteristic and the at least one reference dimension characteristic, determine that an improper object detection event has occurred;
wherein the visual feature comprises one or more of a physical feature and/or a printed feature.

### Claim 30 (depends on 29)

The electronic device of claim 29, wherein the device comprises a barcode reader.