Object based image processing

• US 9,569,832 B2
• Filed: 06/13/2016
• Issued: 02/14/2017
• Est. Priority Date: 09/29/2014
• Status: Active Grant

• Current Assignee: AT&T Intellectual Property I LP (AT&T, Inc.)
• Original Assignee: AT&T Intellectual Property I LP (AT&T, Inc.)
• Inventors: Zavesky, Eric, Gibbon, David Crawford, Begeja, Lee, Reibman, Amy Ruth
• Primary Examiner(s): Kassa, Yosef
• Application Number:
  US15/181,045
• Publication Number:
  US 20160292843A1
• Time in Patent Office: 246 Days
• Field of Search: 382/171, 382/209, 382/260, 382/278, 382/282, 382/307, 358/537, 358/538, 358/452, 358/453
• US Class Current: 1/1
• CPC Class Codes: G06F 18/2136 based on sparsity criteria, e.g. with an overcomplete basis
• CPC Class Codes: G06F 18/23 Clustering techniques
• CPC Class Codes: G06F 18/23213 with fixed number of clusters, e.g. K-means clustering
• CPC Class Codes: G06T 2207/20004 Adaptive image processing
• CPC Class Codes: G06T 2207/20012 Locally adaptive
• CPC Class Codes: G06T 2207/20021 Dividing image into blocks, subimages or windows
• CPC Class Codes: G06T 2207/30168 Image quality inspection
• CPC Class Codes: G06T 2207/30196 Human being; Person
• CPC Class Codes: G06T 2207/30201 Face
• CPC Class Codes: G06T 7/0002 Inspection of images, e.g. flaw detection
• CPC Class Codes: G06T 7/11 Region-based segmentation
• CPC Class Codes: G06T 7/12 Edge-based segmentation
• CPC Class Codes: G06T 7/194 involving foreground-background segmentation
• CPC Class Codes: G06T 7/40 Analysis of texture depth or shape recovery from texture G06T7/529
• CPC Class Codes: G06T 7/90 Determination of colour characteristics
• CPC Class Codes: G06V 10/464 using a plurality of salient features, e.g. bag-of-words [BoW] representations
• CPC Class Codes: G06V 10/763 Non-hierarchical techniques, e.g. based on statistics of modelling distributions
• CPC Class Codes: G06V 10/7715 Feature extraction, e.g. by transforming the feature space, e.g. multi-dimensional scaling [MDS]; Mappings, e.g. subspace methods

Abstract

A method includes receiving image data corresponding to an image and determining object quality values based on a portion of the image data. The portion corresponds to an object represented in the image. The method also includes accessing object category metrics associated with an object category corresponding to the object. The method includes generating a notification indicating that the image data has been altered in response to a result of a comparison of the object quality values to the object category metrics. The result indicates alteration of the portion of the image data.

Claims

1. A method comprising:

receiving, at an image processing device, image data corresponding to an image;

determining object quality values based on a portion of the image data, the portion corresponding to an object represented in the image;

accessing object category metrics associated with an object category corresponding to the object; and

generating a notification indicating that the image data has been altered in response to a result of a comparison of the object quality values to the object category metrics, the result indicating alteration of the portion of the image data.

2. The method of claim 1, further comprising:

selecting a second portion of the image data corresponding to a second object represented in the image;

determining second object quality values based on the second portion;

accessing second object category metrics associated with a second object category corresponding to the second object; and

performing a second comparison of the second object quality values to the second object category metrics, wherein generating the notification is further responsive to a second result of the second comparison indicating alteration of the second portion of the image data.

3. The method of claim 1, further comprising:

detecting the object represented in the image based on the image data;

selecting the portion of the image; and

determining the object category corresponding to the object.

4. The method of claim 3, further comprising comparing the object quality values to basis representations in an object category repository.

5. The method of claim 1, wherein the result indicates the alteration of the portion in response to a determination that a transform residual error for a particular object quality metric of the object for a quality condition associated with the image is greater than a tamper threshold.

6. The method of claim 1, wherein the object comprises a representation of a portion of a person.

7. The method of claim 6, wherein the portion of the person comprises a face of the person or hair of the person.

8. The method of claim 1, further comprising modifying an image processing parameter of an image processing device based on the result, the image processing parameters comprising an image resolution parameter, a frame rate parameter, an encoding parameter, a bandwidth parameter, a bitrate parameter, or an image capture device mode parameter.

9. The method of claim 1, further comprising:

modifying values of the image data corresponding to the object based on the comparison to generate modified image data; and

initiating output of a second image based on the modified image data.

10. The method of claim 1, wherein the image comprises a frame of a video stream.

11. A system comprising:

a processor; and

a memory accessible to the processor, the memory comprising instructions that, when executed by the processor, cause the processor to execute operations including;

receiving image data corresponding to an image;

determining object quality values based on a portion of the image data, wherein the portion corresponds to an object represented in the image;

accessing object category metrics associated with an object category corresponding to the object;

performing a comparison of the object quality values to the object category metrics; and

generating a notification indicating that the image data has been altered based on a result of the comparison.

12. The system of claim 11, wherein the processer and the memory are included in a mobile device.

13. The system of claim 11 wherein the processor and the memory are included in a media device.

14. The system of claim 11, wherein the result of the comparison indicates alteration of the portion in response to a determination that a transform residual error for a particular object quality metric of the object for a quality condition associated with the image is greater than a tamper threshold.

15. The system of claim 11, wherein the operations further include:

selecting a second portion of the image data corresponding to a second object represented in the image;

determining second object quality values based on the second portion;

accessing second object quality category metrics associated with a second object category corresponding to the second object; and

performing a second comparison of the second object quality values to the second object quality category metrics, wherein generating the notification is further responsive to a second result of the second comparison indicating alteration of the second portion of the image data.

16. A computer-readable storage device comprising instructions executable by a processor to perform operations comprising:

receiving image data corresponding to an image;

selecting a portion of the image data corresponding to an object represented in the image;

determining object quality values based on a portion of the image data, wherein the portion corresponds to an object represented in the image;

accessing object category metrics associated with an object category corresponding to the object; and

generating a notification indicating that the image data has been altered based on a result of a comparison of the object quality values to the object category metrics.

17. The computer-readable storage device of claim 16, wherein the operations further include:

selecting a second portion of the image data corresponding to a second object represented in the image;

determining second object quality values based on the second portion;

accessing second object category metrics associated with a second object category corresponding to the second object; and

performing a second comparison of the second object quality values to the second object category metrics.

18. The computer-readable storage device of claim 16, wherein the operations further include performing the comparison, wherein the comparison indicates alteration of the portion in response to a determination that a transform residual error for a particular object quality metric of the object for a quality condition associated with the image is greater than a tamper threshold.

19. The computer-readable storage device of claim 16, wherein the object category metrics include a sharpness metric, a blurriness metric, a low-lighting metric, a texture metric, a color metric, or a combination thereof.

20. The computer-readable storage device of claim 16, wherein the operations further comprise:

detecting the object represented in the image based on the image data;

selecting the portion of the image based on the object; and

determining the object category corresponding to the object.