Object based image processing

• US 10,740,885 B2
• Filed: 10/31/2018
• Issued: 08/11/2020
• 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:
  US16/175,929
• Publication Number:
  US 20190066289A1
• Time in Patent Office: 650 Days
• 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 represented in an image. The object quality values are based on portions of image data for the image. The object quality values include a blurriness value for each object and a color value for each object. The method includes accessing, via the image processing device, object category metrics associated with an object category. The object category metrics include a blurriness metric for each object and a color metric for each object. The method also includes performing, with the image processing device, a particular image processing operation 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, the object quality values based on portions of image data for the image, wherein the object quality values include a blurriness value for each object and a color value for each object;

accessing, via the image processing device, object category metrics associated with an object category, the object category metrics including a blurriness metric for each object and a color metric for each object; and

performing, with the image processing device, a particular image processing operation for the image based on comparisons of the object quality values for each object to corresponding object category metrics.

2. 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.

3. The method of claim 2, further comprising sending a notification to a display device, wherein the notification indicates that the image data has been altered.

4. The method of claim 1, wherein the performing the particular image processing operation includes generating modified image data.

5. The method of claim 4, further comprising sending the modified image data to a display device.

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

7. The method of claim 1, wherein the particular image processing operation includes modifying an image processing parameter of the image processing device.

8. The method of claim 7, wherein the image processing parameter includes an image resolution parameter, a frame rate parameter, an encoding parameter, a bandwidth parameter, a bitrate parameter, an image capture device mode parameter, or combinations thereof.

9. The method of claim 1, wherein the particular image processing operation includes modifying values of the image data corresponding to a particular object of the plurality of objects.

10. 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, the operations including;

receiving image data of an image;

determining object quality values for a plurality of objects represented in the image, the object quality values based on portions of the image data, wherein the object quality values include a blurriness value for each object and a color value for each object;

accessing object category metrics associated with an object category, the object category metrics including a blurriness metric for each object and a color metric for each object; and

performing a particular image processing operation for the image based on comparisons of the object quality values for each object to corresponding object category metrics.

11. The system of claim 10, further comprising an object category repository to store the object category metrics.

12. The system of claim 10, wherein the performing the particular image processing operation includes generating modified image data.

13. The system of claim 10, wherein the particular image processing operation includes modifying an image processing parameter of an image processing device.

14. The system of claim 13, wherein the image processing parameter includes an image resolution parameter, a frame rate parameter, an encoding parameter, a bandwidth parameter, a bitrate parameter, an image capture device mode parameter, or combinations thereof.

15. The system of claim 10, wherein the particular image processing operation includes modifying values of the image data corresponding to a particular object of the plurality of objects.

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

determining object quality values for a plurality of objects represented in an image, the object quality values based on portions of image data for the image, wherein the object quality values including a blurriness value for each object and a color value for each object;

accessing object category metrics associated with an object category, the object category metrics including a blurriness metric for each object and a color metric for each object; and

performing a particular image processing operation for the image based on comparisons of the object quality values for each object to corresponding object category metrics.

17. The computer-readable storage device of claim 16, wherein the performing the particular image processing operation includes generating modified image data.

18. The computer-readable storage device of claim 16, wherein the particular image processing operation includes modifying an image processing parameter of an image processing device.

19. The computer-readable storage device of claim 18, wherein the image processing parameter includes an image resolution parameter, a frame rate parameter, an encoding parameter, a bandwidth parameter, a bitrate parameter, an image capture device mode parameter, or combinations thereof.

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