IP Library Granted Patent US 11,295,104
Granted Patent B2
US 11,295,104 · App. 16/898,184 · Granted Apr 5, 2022

Methods and apparatus to read barcodes on reflective surfaces

Inventors: Duanfeng He (South Setauket, NY); Eugene B. Joseph (Coram, NY)
Assignee: Zebra Technologies Corporation
G06K7/1465G06K7/1469G06K2007/10524
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Quick Facts
Patent No.
US 11,295,104
App. No.
16/898,184
Granted
Apr 5, 2022
Kind
B2
Abstract

Example methods and apparatus to read barcodes on reflective surfaces are disclosed herein. An example method for handling a reflective surface in an imaging reader includes capturing one or more images of a surface of an item; detecting whether a specular reflection is present in the one or more images; when a specular reflection is detected, processing one or more additional images of the surface using a predetermined pattern of first processing suitable to identify a barcode on a reflective surface and second processing suitable to identify a barcode on a non-reflective surface; and when a specular reflection is not detected, processing one or more additional images of the surface using the second processing suitable to identify a barcode on a non-reflective surface.

Claims (77)

1. A method for handling a reflective surface in an imaging reader, the method comprising:

capturing one or more images of a surface of an item;

detecting whether a specular reflection is present in the one or more images;

when a specular reflection is detected, processing one or more additional images of the surface using a predetermined pattern of first processing suitable to identify a barcode on a reflective surface and second processing suitable to identify a barcode on a non-reflective surface; and

when a specular reflection is not detected, processing one or more additional images of the surface using the second processing suitable to identify a barcode on a non-reflective surface.

2. The method of claim 1 , wherein the predetermined pattern includes processing an image with the first processing followed by processing a plurality of images with the second processing.

3. The method of claim 1 , wherein detecting the specular reflection includes:

computing a first histogram of brightnesses of the one or more images; and

identifying a gap in the first histogram between a first range of brightnesses associated with barcodes and a second range of brightnesses associated the specular reflection.

4. The method of claim 3 , wherein computing the first histogram includes:

computing a plurality of histograms for respective ones of the one or more images; and

combining the plurality of histograms to form the first histogram.

5. The method of claim 3 , wherein computing the first histogram includes:

computing a second histogram of one or more of the images; and

combining adjacent brightnesses of the second histogram to form the first histogram.

6. The method of claim 1 , wherein detecting the specular reflection includes:

computing a histogram of brightnesses of the one or more images;

identifying a first entry of the histogram having a largest value in a brightness range of the histogram associated with specular reflections; and

when the largest value satisfies a first predetermined threshold:

identifying a second entry of the histogram closest to the first entry and having a second value that exceeds a second threshold that is based on the largest value,

identifying a third entry of the histogram having a third value that is a maximum value of the histogram, and

detecting the specular reflection when a second brightness associated the second entry is less than a third predetermined threshold, and a third brightness associated with the third entry is less than a fourth predetermined threshold.

7. The method of claim 6 , wherein, when the largest value satisfies the first determined threshold and satisfies a fifth predetermined threshold:

identifying the second entry, identifying the third entry, and detecting the specular reflection.

8. The method of claim 1 , wherein the specular reflection is detected when the surface of the item includes a screen of at least one of a mobile phone, a tablet, a laptop, or a computer.

9. The method of claim 1 , further comprising reverting to the second processing when at least one of a barcode is decoded, or a specular reflection is no longer detected.

10. An apparatus comprising:

an imaging device configured to capture one or more images of a surface of an item;

a processing device; and

a non-transitory tangible computer-readable storage medium storing computer-readable instructions that, when executed by the processing device, cause the apparatus to:

detect whether a specular reflection is present in the one or more images;

when a specular reflection is detected, process one or more additional images of the surface using a predetermined pattern of first processing suitable to identify a barcode on a reflective surface and second processing suitable to identify a barcode on a non-reflective surface; and

when a specular reflection is not detected, process one or more additional images of the surface using the second processing suitable to identify a barcode on a non-reflective surface.

11. The apparatus of claim 10 , wherein the computer-readable instructions, when executed by a processing device, cause the apparatus to detect the specular reflection by:

computing a histogram of brightnesses of the one or more images; and

identifying a gap in the histogram between a first range of brightnesses associated with barcodes and a second range of brightnesses associated the specular reflection.

12. The apparatus of claim 10 , wherein the computer-readable instructions, when executed by a processing device, cause the apparatus to detect the specular reflection by:

computing a histogram of brightnesses of the one or more images;

identifying a first entry of the histogram having a largest value in a brightness range of the histogram associated with specular reflections; and

when the largest value satisfies a first predetermined threshold:

identifying a second entry of the histogram closest to the first entry and having a second value that exceeds a second threshold that is based on the largest value,

identifying a third entry of the histogram having a third value that is a maximum value of the histogram, and

detecting the specular reflection when a second brightness associated the second entry is less than a third predetermined threshold, and a third brightness associated with the third entry is less than a fourth predetermined threshold.

13. An imaging reader comprising:

an imaging device configured to capture one or more images of a surface of an item;

a computing device configured to detect when a specular reflection is present in the one or more images, and determine the surface is reflective when a specular reflection is detected; and

a barcode reader configured to:

when a specular reflection is detected, process one or more additional images of the surface using a predetermined pattern of first processing suitable to identify a barcode on a reflective surface and second processing suitable to identify a barcode on a non-reflective surface; and

when a specular reflection is not detected, process one or more additional images of the surface using the second processing suitable to identify a barcode on a non-reflective surface.

14. The imaging reader of claim 13 , wherein the computing device is to detect the specular reflection by:

computing a first histogram of brightnesses of the one or more images; and

identifying a gap in the first histogram between a first range of brightnesses associated with barcodes and a second range of brightnesses associated the specular reflection.

15. The imaging reader of claim 13 , wherein the computing device is to detect the specular reflection by:

computing a histogram of brightnesses of the one or more images;

identifying a first entry of the histogram having a largest value in a brightness range of the histogram associated with specular reflections; and

when the largest value satisfies a first predetermined threshold:

identifying a second entry of the histogram closest to the first entry and having a second value that exceeds a second threshold that is based on the largest value,

identifying a third entry of the histogram having a third value that is a maximum value of the histogram, and

detecting the specular reflection when a second brightness associated the second entry is less than a third predetermined threshold, and a third brightness associated with the third entry is less than a fourth predetermined threshold.

16. The imaging reader of claim 13 , wherein the computing device is at least one of an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or a programmable processor.

17. The imaging reader of claim 13 , further comprising a trigger configured to initiate capture of the one or more images of the surface of the item when activated by a user.

18. A non-transitory tangible computer-readable storage medium storing computer-readable instructions that, when executed by a processing device, cause an imaging reader to:

detecting whether a specular reflection is present in one or more images of a surface of an item;

determining the surface is reflective when a specular reflection is detected;

when a specular reflection is detected, process one or more additional images of the surface using a predetermined pattern of first processing suitable to identify a barcode on a reflective surface and second processing suitable to identify a barcode on a non-reflective surface; and

when a specular reflection is not detected, process one or more additional images of the surface using the second processing suitable to identify a barcode on a non-reflective surface.

19. The non-transitory tangible computer-readable storage medium of claim 18 , wherein the predetermined pattern includes processing an image with the first processing followed by processing a plurality of images with the second processing.

20. The non-transitory tangible computer-readable storage medium of claim 18 , wherein the computer-readable instructions, when executed by a processing device, cause the imaging reader to detect the specular reflection by:

computing a histogram of brightnesses of the one or more images; and

identifying a gap in the histogram between a first range of brightnesses associated with barcodes and a second range of brightnesses associated the specular reflection.

21. The non-transitory tangible computer-readable storage medium of claim 18 , wherein the computer-readable instructions, when executed by a processing device, cause the imaging reader to detect the specular reflection by:

computing a histogram of brightnesses of the one or more images;

identifying a first entry of the histogram having a largest value in a brightness range of the histogram associated with specular reflections; and

when the largest value satisfies a first predetermined threshold:

identifying a second entry of the histogram closest to the first entry and having a second value that exceeds a second threshold that is based on the largest value,

identifying a third entry of the histogram having a third value that is a maximum value of the histogram, and

detecting the specular reflection when a second brightness associated the second entry is less than a third predetermined threshold, and a third brightness associated with the third entry is less than a fourth predetermined threshold.

Assignments (4)
SECURITY INTEREST Recorded Apr 12, 2021
From: ZEBRA TECHNOLOGIES CORPORATION
To: JPMORGAN CHASE BANK, N.A.
Reel/Frame 056471/0868 →
RELEASE OF SECURITY INTEREST - 364 - DAY Recorded Mar 5, 2021
From: JPMORGAN CHASE BANK, N.A.
To: ZEBRA TECHNOLOGIES CORPORATION; LASER BAND, LLC; TEMPTIME CORPORATION
Reel/Frame 056036/0590 →
SECURITY INTEREST Recorded Sep 1, 2020
From: ZEBRA TECHNOLOGIES CORPORATION; LASER BAND, LLC; TEMPTIME CORPORATION
To: JPMORGAN CHASE BANK, N.A.
Reel/Frame 053841/0212 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 12, 2020
From: HE, DUANFENG; JOSEPH, EUGENE B.
To: ZEBRA TECHNOLOGIES CORPORATION
Reel/Frame 052925/0130 →
Continuity (1)
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