Barcode recognition using data-driven classifier

US9396377B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-9396377-B2
Application numberUS-201414563949-A
CountryUS
Kind codeB2
Filing dateDec 8, 2014
Priority dateSep 30, 2010
Publication dateJul 19, 2016
Grant dateJul 19, 2016

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  1. Title

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  2. Abstract

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  3. Assignees and inventors

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  4. Key dates

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  5. First independent claim

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  6. CPC / IPC classifications

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Abstract

Official abstract text for this publication.

A barcode decoding system and method are disclosed that use a data-driven classifier for transforming a potentially degraded barcode signal into a digit sequence. The disclosed implementations are robust to signal degradation through incorporation of a noise model into the classifier construction phase. The run-time computational cost is low, allowing for efficient implementations on portable devices. Implementations are disclosed for intelligent preview scaling, barcode-aware autofocus augmentation and multi-scale signal feature extraction.

First claim

Opening claim text (preview).

What is claimed is: 1. A method comprising: capturing a digital image of an object using a sensor of a device; and scaling the captured digital image, using one or more processors of the device, to lie within a predefined image view area of a user interface presented on a display screen of the device, while a distance is maintained between the object and the sensor, wherein the scaling is based on mapping information of a real-world coordinate frame onto a sensor coordinate frame. 2. The method of claim 1 , wherein the object comprises a barcode. 3. The method of claim 1 , wherein the scaling uses a geometric model to map the real-world coordinate frame onto the sensor coordinate frame. 4. The method of claim 1 , further comprising: constraining a size of the predefined image view area of the user interface using the mapping information. 5. The method of claim 4 , wherein constraining the size of the predefined image view area of the user interface is based in part on at least one of an optical magnification of the object by the device or a constraint of the sensor. 6. The method of claim 3 , wherein the geometric model comprises a trigonometric model of a pinhole camera. 7. The method of claim 6 , wherein the object has a length h and the object's image on the sensor of the device has a dimension of length h′, and the pinhole camera model relates a distance d of the object from a camera lens of the device to a distance d′ of the sensor of the device from the camera lens of the device, and the relationship is given by h/d=h′/d′. 8. The method of claim 1 , wherein the mapping accounts for at least one of lens distortion, sensor characteristics, or photographic effects. 9. The method of claim 1 , wherein the scaling uses a model to map the real-world coordinate frame onto the sensor coordinate frame, with the method further comprising: estimating model parameters using a calibration process and an image of a calibration target taken from a number of positions of the sensor relative to the calibration target. 10. The method of claim 1 , wherein the scaling comprises using a scale factor that is determined relative to a target guide and that is contained entirely within the predefined image view area, and wherein the scale factor scales the image to substantially fill the predefined image view area while preserving an aspect ratio of the image. 11. A system comprising: one or more processors; memory configured for storing instructions, which, when executed by the one or more processors, causes the one or more processors to perform operations comprising: capturing a digital image of an object using a sensor of a device; and scaling the captured digital image to lie within a predefined image view area of a user interface presented on a display screen of the device, while a distance is maintained between the object and the sensor, wherein the scaling is based on mapping information of a real-world coordinate frame onto a sensor coordinate frame. 12. The system of claim 11 , wherein the object comprises a barcode. 13. The system of claim 11 , wherein the scaling uses a geometric model to map the real-world coordinate frame onto the sensor coordinate frame. 14. The system of claim 11 , further comprising: constraining a size of the predefined image view area of the user interface using the mapping information. 15. The system of claim 14 , where constraining the size of the predefined image view area of the user interface is based in part on at least one of an optical magnification of the object by the device or a constraint of the sensor. 16. The system of claim 13 , wherein the geometric model comprises a trigonometric model of a pinhole camera. 17. The system of claim 16 , wherein the object has a length h and the object's image on the sensor of the device has a dimension of length h′, and the pinhole camera model relates a distance d of the object from a camera lens of the device to a distance d′ of the sensor of the device from the camera lens of the device, and the relationship is given by h/d=h′/d′. 18. The system of claim 11 , wherein the mapping accounts for at least one of lens distortion, sensor characteristics, or photographic effects. 19. The system of claim 11 , wherein the scaling uses a model to map the real-world coordinate frame onto the sensor coordinate frame, with the system further comprising: estimating model parameters using a calibration process and an image of a calibration target taken from a number of positions of the sensor relative to the calibration target. 20. The system of claim 11 , wherein the scaling comprises using a scale factor that is determined relative to a target guide and that is contained entirely within the predefined image view area, and wherein the scale factor scales the image to substantially fill the predefined image view area while preserving an aspect ratio of the image. 21. A system comprising: one or more processors; memory configured for storing instructions, which, when executed by the one or more processors, causes the one or more processors to perform operations comprising: capturing a digital image of an object using a sensor of a device, while the sensor is at a distance from the object; and scaling the digital image to lie within a target guide of a user interface presented on a display area of the device, rather than scaling the target guide to fit a size of the digital image. 22. The system of claim 21 , wherein the scaling comprises using a scale factor determined relative to the target guide, where the target guide is entirely within the display area, and where the scale factor scales the digital image to substantially fill the display area while preserving an aspect ratio of the digital image.

Assignees

Inventors

Classifications

  • Focalisation · CPC title

  • locating of the code in an image · CPC title

  • G06K7/1447Primary

    extracting optical codes from image or text carrying said optical code · CPC title

Patent family

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Frequently asked questions

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What does patent US9396377B2 cover?
A barcode decoding system and method are disclosed that use a data-driven classifier for transforming a potentially degraded barcode signal into a digit sequence. The disclosed implementations are robust to signal degradation through incorporation of a noise model into the classifier construction phase. The run-time computational cost is low, allowing for efficient implementations on portable d…
Who is the assignee on this patent?
Apple Inc
What technology area does this patent fall under?
Primary CPC classification G06K7/1447. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue Jul 19 2016 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 8 related publications on this page (citations in our corpus or others sharing the same primary CPC).