METHOD AND APPARATUS FOR PROVIDING IMAGE CLASSIFICATION BASED ON OPACITY

• US 20170109612A1
• Filed: 10/14/2015
• Published: 04/20/2017
• Est. Priority Date: 10/14/2015
• Status: Active Grant

• Current Assignee: HERE Global B.V. (Nokia Corporation)
• Original Assignee: HERE Global B.V. (Nokia Corporation)
• Inventors: MITTAL, Anish, MARKS, William
• Granted Patent: US 9,870,511 B2
• Time in Patent Office: Days
• CPC Class Codes: G06V 20/56 exterior to a vehicle by using sensors mounted on the vehicle

Abstract

An approach is provided for automated classification of an image based on the fogging attributes associated with the image. The approach involves processing and/or facilitating a processing of image data associated with at least one image to cause, at least in part, an extraction of one or more fogging attributes from the image data. The approach also involves causing, at least in part, a mapping of the one or more fogging attributes to one or more features of at least one classifier, wherein the at least one classifier is trained based, at least in part, on a co-registration of the one or more features to one or more records of previously made image judgements. The approach further involves causing, at least in part, a classification of the at least one image as either in a fogging-afflicted state or a non-fogging-afflicted state based, at least in part, on the at least one classifier.

Claims

1. A method comprising:

processing and/or facilitating a processing of image data associated with at least one image to cause, at least in part, an extraction of one or more fogging attributes from the image data;

causing, at least in part, a mapping of the one or more fogging attributes to one or more features of at least one classifier, wherein the at least one classifier is trained based, at least in part, on a co-registration of the one or more features to one or more records of previously made image judgements; and

causing, at least in part, a classification of the at least one image as either in a fogging-afflicted state or a non-fogging-afflicted state based, at least in part, on the at least one classifier.

2. A method of claim 1, further comprising:

determining the image data from one or more bounding boxes associated with one or more areas of the at least one image,

wherein the classification of the at least one image applies to the one or more areas of the at least one image.

3. A method of claim 2, wherein the one or more bounding boxes include, at least in part, one or more small bounding boxes, one or more medium bounding boxes, one or more large bounding boxes specified for one or more color channels of the at least one image.

4. A method of claim 3, further comprising:

determining at least one multi-dimensional feature attribute vector based, at least in part, on the one or more small bounding boxes, the one or more medium bounding boxes, the one or more large bounding boxes, the one or more bounding boxes, the one or more color channels, or a combination thereof.

5. A method of claim 2, further comprising:

causing, at least in part, a centering of the one or more bounding boxes with respect to at least one center point of the at least one image.

6. A method of claim 1, wherein the one or more features of the at least one classifier include, at least in part, one or more color-based localized contrast features.

7. A method of claim 6, further comprising:

determining the one or more color-based localized contrast features based, at least in part, on a Michelson contrast value.

8. A method of claim 7, further comprising:

determining that the one or more color-based localized contrast features are associated with the fogging-afflicted state if the Michelson contrast value is below a threshold value; and

determining that the one or more color-based localized contrast features are associated with the non-fogging-afflicted state if the Michelson contrast value is above a threshold value.

9. A method of claim 7, further comprising:

determining the Michelson contrast value for at least one pixel of the at least one image based, at least in part, on intensity information associated with one or more neighboring pixels.

10. A method of claim 1, wherein the fogging-afflicted state is associated with at least a fogging or a hazing at least one image, wherein the fogging or the hazing results from one or more conditions of at least one camera component used to capture the at least one image, one or more external conditions associated with at least one environment captured in the at least one image, or a combination thereof.

11. An apparatus comprising:

at least one processor; and

at least one memory including computer program code for one or more programs,

the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following,

process and/or facilitate a processing of image data associated with at least one image to cause, at least in part, an extraction of one or more fogging attributes from the image data;

cause, at least in part, a mapping of the one or more fogging attributes to one or more features of at least one classifier, wherein the at least one classifier is trained based, at least in part, on a co-registration of the one or more features to one or more records of previously made image judgements; and

cause, at least in part, a classification of the at least one image as either in a fogging-afflicted state or a non-fogging-afflicted state based, at least in part, on the at least one classifier.

12. An apparatus of claim 11, wherein the apparatus is further caused to:

determine the image data from one or more bounding boxes associated with one or more areas of the at least one image,

wherein the classification of the at least one image applies to the one or more areas of the at least one image.

13. An apparatus of claim 12, wherein the one or more bounding boxes include, at least in part, one or more small bounding boxes, one or more medium bounding boxes, one or more large bounding boxes specified for one or more color channels of the at least one image.

14. An apparatus of claim 13, wherein the apparatus is further caused to:

determine at least one multi-dimensional feature attribute vector based, at least in part, on the one or more small bounding boxes, the one or more medium bounding boxes, the one or more large bounding boxes, the one or more bounding boxes, the one or more color channels, or a combination thereof.

15. An apparatus of claim 12, wherein the apparatus is further caused to:

cause, at least in part, a centering of the one or more bounding boxes with respect to at least one center point of the at least one image.

16. An apparatus of claim 11, wherein the one or more features of the at least one classifier include, at least in part, one or more color-based localized contrast features.

17. An apparatus of claim 16, wherein the apparatus is further caused to:

determine the one or more color-based localized contrast features based, at least in part, on a Michelson contrast value.

18. A computer-readable storage medium carrying one or more sequences of one or more instructions which, when executed by one or more processors, cause an apparatus to at least perform the following steps:

processing and/or facilitating a processing of image data associated with at least one image to cause, at least in part, an extraction of one or more fogging attributes from the image data;

causing, at least in part, a mapping of the one or more fogging attributes to one or more features of at least one classifier, wherein the at least one classifier is trained based, at least in part, on a co-registration of the one or more features to one or more records of previously made image judgements; and

causing, at least in part, a classification of the at least one image as either in a fogging-afflicted state or a non-fogging-afflicted state based, at least in part, on the at least one classifier.

19. A computer-readable storage medium of claim 18, wherein the apparatus is further caused to:

determining the image data from one or more bounding boxes associated with one or more areas of the at least one image,

wherein the classification of the at least one image applies to the one or more areas of the at least one image.

20. A computer-readable storage medium of claim 19, wherein the one or more bounding boxes include, at least in part, one or more small bounding boxes, one or more medium bounding boxes, one or more large bounding boxes specified for one or more color channels of the at least one image.

21-48. -48. (canceled)