Object based image processing

• US 10,140,696 B2
• Filed: 01/11/2017
• Issued: 11/27/2018
• 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:
  US15/403,999
• Publication Number:
  US 20170124691A1
• Time in Patent Office: 685 Days
• Field of Search: 382170, 382171, 382190, 382205, 382209, 382260, 382274, 382275, 358 326, 358 327, 358537, 358538
• 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 determining, at an image processing device, object quality values for a plurality of objects based on portions of image data corresponding to an image. Each portion corresponds to an object of the plurality of objects represented in the image. The method includes accessing, via the image processing device, object category metrics associated with an object category corresponding to each object of the plurality of objects. The method also includes determining, with the image processing device, image processing for the image based on comparisons of the object quality values for each object to corresponding object category metrics.

Claims

1. A method comprising:

determining, at an image processing device, object quality values for a plurality of objects represented in an image based on portions of image data corresponding to the image, each portion corresponding to an object of the plurality of objects represented in the image;

accessing, via the image processing device, object category metrics associated with an object category corresponding to each object of the plurality of objects represented in the image; and

determining, with the image processing device, image processing for the image based on comparisons of the object quality values for each object to corresponding object category metrics, wherein the image processing includes modifying at least two image processing parameters of the image processing device, the image processing parameters including a frame rate parameter, an encoding parameter, a bandwidth parameter, and a bitrate parameter.

2. The method of claim 1, further comprising implementing the image processing to generate modified image data for the image.

3. The method of claim 2, further comprising sending the modified image data to a display device to display the image.

4. The method of claim 1, further comprising determining, based on the comparisons of the object quality values for each object to corresponding object category metrics, whether the image data has been altered.

5. The method of claim 4, further comprising sending a notification to a display device, wherein the notification indicates that the image data has been altered.

6. The method of claim 1, wherein an object category repository stores the object category metrics.

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

8. The method of claim 1, wherein the object category metrics include a sharpness metric, a blurriness metric, a low-lighting metric, or combinations thereof.

9. The method of claim 8, wherein a particular object quality metric includes quality coefficients associated with a particular object category.

10. The method of claim 1, wherein the image processing for the image includes modifying values of the image data corresponding to a particular object.

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;

determining object quality values for a plurality of objects represented in an image based on portions of image data corresponding to the image, each portion corresponding to an object of the plurality of objects represented in the image;

accessing object category metrics associated with an object category corresponding to each object of the plurality of objects represented in the image; and

determining image processing for the image based on comparisons of the object quality values for each object to corresponding object category metrics, wherein the image processing includes modifying at least two image processing parameters of an image processing device, the image processing parameters including a frame rate parameter, an encoding parameter, a bandwidth parameter, and a bitrate parameter.

12. The system of claim 11, wherein the operations further include implementing the image processing to generate modified image data for the image.

13. The system of claim 11, wherein the object category metrics include a texture metric, a color metric, a smoothness metric, or combinations thereof.

14. The system of claim 13, wherein a particular object quality metric includes quality coefficients associated with a particular object category.

15. The system of claim 11, wherein the image processing for the image includes modifying values of the image data corresponding to a particular object.

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

determining object quality values for a plurality of objects represented in an image based on portions of image data corresponding to the image, each portion corresponding to an object of the plurality of objects represented in the image;

accessing object category metrics associated with an object category corresponding to each object of the plurality of objects represented in the image; and

determining image processing for the image based on comparisons of the object quality values for each object to corresponding object category metrics, wherein the image processing includes modifying at least two image processing parameters of an image processing device, the image processing parameters including a frame rate parameter, an encoding parameter, a bandwidth parameter, and a bitrate parameter.

17. The computer-readable storage device of claim 16, wherein the operations further comprise implementing the image processing to generate modified image data for the image.

18. The computer-readable storage device of claim 16, wherein the image the operations further comprise receiving the image from an integrated camera system coupled to the processor.

19. The computer-readable storage device of claim 16, wherein the operations further comprise receiving the image via a network.

20. The computer-readable storage device of claim 16, wherein the image processing for the image includes modifying values of the image data corresponding to a particular object.