Blurring based content recognizer

• US 8,948,513 B2
• Filed: 01/27/2009
• Issued: 02/03/2015
• Est. Priority Date: 01/27/2009
• Status: Active Grant

• Current Assignee: Apple Inc.
• Original Assignee: Apple Inc.
• Inventors: van der Merwe, Rudolph, Crandall, Richard Eugene, Noble, Samuel Gordon, Serlet, Bertrand, Kounitski, Stanislav
• Primary Examiner(s): Park, Chan
• Assistant Examiner(s): Thomas, Mia M
• Application Number:
  US12/360,831
• Publication Number:
  US 20100187311A1
• Time in Patent Office: 2,198 Days
• Field of Search: 382/100, 382/140, 382/162, 382/167, 382/168, 382/170, 382/173, 382/201, 382/255, 382/278, 382/286, 382/289, 382/294, 382/312, 348/207.99, 348/222.1, 23546201-46207, 235/462.41, 235/454, 359/201.1, 358/474
• US Class Current: 382/182
• CPC Class Codes: G06T 2207/10004 Still image; Photographic image
• CPC Class Codes: G06T 2207/20076 Probabilistic image processing
• CPC Class Codes: G06T 7/11 Region-based segmentation
• CPC Class Codes: G06T 7/136 involving thresholding
• CPC Class Codes: G06T 7/143 involving probabilistic approaches, e.g. Markov random field [MRF] modelling
• CPC Class Codes: G06T 7/187 involving region growing; involving region merging; involving connected component labelling
• CPC Class Codes: G06V 30/2247 Characters composed of bars, e.g. CMC-7

Abstract

Methods, systems, and apparatus, including computer program products, for identifying regions of interest in an image and identifying a barcode in a degraded image are provided. A region of interest is identified by pre-processing an image, generating a binary image based on a metric calculated on the pre-processed image, and analyzing regions of the image identified using connected components and other analysis. A barcode is identified by searching a population of barcodes, degrading ideal image intensity profiles of candidate barcodes, and comparing the degraded ideal image intensity profiles to an image intensity profile of the degraded image.

Claims

1. A computer implemented method, comprising:

receiving a degraded image of a first barcode;

generating an image intensity profile of the degraded image, wherein the image intensity profile is generated by averaging or integrating a number of scan lines;

searching a population of barcodes, the searching including selecting a candidate barcode from the population of barcodes and comparing a degraded version of an ideal image intensity profile of the candidate barcode to the image intensity profile of the degraded image; and

selecting a final barcode from the population of barcodes based on the comparison.

2. The method of claim 1, further comprising:

identifying a region of interest containing the first barcode in the degraded image; and

wherein the image intensity profile of the degraded image is an image intensity profile of the region of interest.

3. The method of claim 1, further comprising:

receiving context information about the degraded image; and

wherein the searching is biased based on the context information.

4. The method of claim 3, wherein:

the context information includes an approximation of a physical location corresponding to where the degraded image was captured.

5. The method of claim 3, wherein:

the context information includes previous selections of one or more barcodes corresponding to one or more other degraded images captured at one or more physical locations that are approximately the same as a physical location where the degraded image was captured.

6. The method of claim 3, wherein:

the context information is received from a data processing apparatus associated with one or more objects in a vicinity of where the degraded image was captured.

7. The method of claim 1, further comprising:

receiving accelerometer data regarding a device used to capture the degraded image;

estimating a motion blur in the degraded image using the accelerometer data; and

wherein the degraded version of the ideal image intensity profile of the candidate barcode is generated using the estimated motion blur.

8. The method of claim 1, further comprising:

receiving accelerometer data regarding a device used to capture the degraded image;

using the accelerometer data to estimate a degree of variance from the horizontal or vertical axis of the device at the time the degraded image was captured; and

wherein the degraded version of the ideal image intensity profile of the candidate barcode is generated using the estimated degree of variance.

9. The method of claim 1, further comprising:

receiving calibration information; and

wherein the degraded version of the ideal image intensity profile of the candidate barcode is generated using the calibration information.

10. The method of claim 1, wherein:

searching the population of barcodes further includes repeating the selecting and comparing steps for each barcode in the population of barcodes.

11. The method of claim 1, wherein:

searching the population of barcodes further includes using a genetic algorithm to direct the search.

12. The method of claim 1, further comprising:

retrieving information corresponding to the final barcode from a database.

13. The method of claim 1, wherein comparing the degraded version of the ideal image intensity profile of the candidate barcode to the image intensity profile of the degraded image further comprises:

pre-computing a degraded version of parts of ideal image intensity profiles of barcodes in the population of barcodes; and

generating the degraded version of the ideal image intensity profile of the candidate barcode by combining the identified degraded versions of parts of the ideal image intensity profile of the candidate barcode.

14. The method of claim 1, wherein comparing the degraded version of the ideal image intensity profile of the candidate barcode to the image intensity profile of the degraded image further comprises:

pre-computing a plurality of error signals for each of a plurality of regions in an image intensity profile space;

identifying an error signal corresponding to the degraded version of the ideal image intensity profile of the candidate barcode for each of the plurality of regions; and

combining the identified error signals.

15. A system comprising:

a processor; and

a computer-readable medium coupled to the processor and including instructions, which, when executed by the processor, cause the processor to perform operations comprising;

receiving a degraded image of a first barcode from a client;

generating an image intensity profile of the degraded image, wherein the image intensity profile is generated by averaging or integrating a number of scan lines;

searching a population of barcodes, the searching including selecting a candidate barcode from the population of barcodes and comparing a degraded version of an ideal image intensity profile of the candidate barcode to the image intensity profile of the degraded image;

selecting a final barcode from the population of barcodes based on the comparison; and

sending the final barcode to the client.

16. The system of claim 15, wherein the processor performs operations comprising:

receiving context information about the degraded image; and

wherein the searching is biased based on the context information.

17. The system of claim 15, wherein the processor performs operations comprising:

retrieving information corresponding to the final barcode from a database; and

sending the information to the client.

18. The system of claim 15, wherein comparing the degraded version of the ideal image intensity profile of the candidate barcode to the image intensity profile of the degraded image further comprises:

pre-computing a degraded version of parts of image intensity profiles of barcodes in the population of barcodes; and

generating the degraded version of the ideal image intensity profile of the candidate barcode by combining the identified degraded versions of the ideal image intensity profile of the candidate barcode.

19. The system of claim 15, wherein comparing the degraded version of the ideal image intensity profile of the candidate barcode to the image intensity profile of the degraded image further comprises:

pre-computing a plurality of error signals for each of a plurality of regions in an image intensity profile space;

identifying an error signal corresponding to the degraded version of the ideal image intensity profile of the candidate barcode for each of the plurality of regions; and

combining the identified error signals.

20. A computer-readable, non-transitory medium having instructions stored thereon, which, when executed by a processor, causes the processor to perform operations comprising:

receiving a degraded image of a first barcode;

generating an image intensity profile of the degraded image, wherein the image intensity profile is generated by averaging or integrating a number of scan lines;

searching a population of barcodes, the searching including selecting a candidate barcode from the population of barcodes and comparing a degraded version of an ideal image intensity profile of the candidate barcode to the image intensity profile of the degraded image; and

selecting a final barcode from the population of barcodes based on the comparison.

21. The computer-readable medium of claim 20, further having instructions stored thereon which, when executed by a processor, causes the processor to perform operations comprising:

receiving context information about the degraded image; and

wherein the searching is biased based on the context information.

22. The computer-readable medium of claim 20, further having instructions stored thereon which, when executed by a processor, causes the processor to perform operations comprising:

retrieving information corresponding to the final barcode from a database.

23. The computer-readable medium of claim 20, wherein comparing the degraded version of the ideal image intensity profile of the candidate barcode to the image intensity profile of the degraded image further comprises:

pre-computing a degraded version of parts of ideal image intensity profiles of barcodes the population of barcodes; and

generating the degraded version of the ideal image intensity profile of the candidate barcode by combining the identified degraded versions of parts of the ideal image intensity profile of the candidate barcode.

24. The computer-readable medium of claim 20, wherein comparing the degraded version of the ideal image intensity profile of the candidate barcode to the image intensity profile of the degraded image further comprises:

pre-computing a plurality of error signals for each of a plurality of regions in an image intensity profile space;

identifying an error signal corresponding to the degraded version of the ideal image intensity profile of the candidate barcode for each of the plurality of regions; and

combining the identified error signals.