Automatically producing an image of a portion of a photographic image

• US 6,654,507 B2
• Filed: 12/14/2000
• Issued: 11/25/2003
• Est. Priority Date: 12/14/2000
• Status: Expired due to Term

• Current Assignee: Monument Peak Ventures, LLC (Dominion Harbor Enterprises, LLC)
• Original Assignee: Eastman Kodak Company
• Inventors: Luo, Jiebo
• Primary Examiner(s): Mehta, Bhavesh M.
• Assistant Examiner(s): CARTER, AARON W
• Application Number:
  US09/736,825
• Publication Number:
  US 20020114535A1
• Time in Patent Office: 1,076 Days
• Field of Search: 382/291, 382/173, 382/180, 382/225, 382/282, 345/620-628, 358/453
• US Class Current: 382/282
• CPC Class Codes: G06T 7/66 of image moments or centre of gravity
• CPC Class Codes: G06V 10/25 Determination of region of interest [ROI] or a volume of interest [VOI]
• CPC Class Codes: H04N 1/3875 combined with enlarging or reducing enlarging or reducing per se H04N1/393

Abstract

A method of producing an image of at least a portion of a digital image that includes pixels includes

computing a belief map of the digital image, by using the pixels of the digital image to determine a series of features and using such features to assign the probability of the location of a main subject of the digital image in the belief map determining a crop window having a shape and a zoom factor, which determine a size of the crop window and cropping the digital image to include a portion of the image of high subject content in response to the belief map and the crop window.

Claims

1. A method of producing an image of at least a portion of a digital image, comprising:

a) providing a digital image having pixels;

b) computing a belief map of the digital image by using the pixels of the digital image to determine a series of features and using such features to assign a probability of a location of a main subject of the digital image in the belief map;

c) determining a crop window having a shape factor and a zoom factor, the shape and the zoom factors determining a size of the crop window; and

d) cropping the digital image to include a portion of the image of high subject content in response to the belief map and the crop window.

2. The method of claim 1 wherein determining the crop window includes

i) computing a weighted center-of-mass of the belief map, weighted by belief values of the belief map;

ii) computing weighted central moments of the belief map relative to the center-of-mass and weighted by a weighting function of each belief value of the belief map;

iii) computing an effective rectangular bounding box according to the central moments; and

iv) determining a crop window having a shape and a zoom factor, the shape and the zoom factors determining a size of the crop window.

3. The method of claim 1 wherein cropping the digital image includes

i) selecting an initial position of the crop window at a location which includes a center of mass;

ii) using belief values corresponding to the crop window to select the position of the crop window to include a portion of the image of high subject content in response to the belief map; and

iii) cropping the digital image according to the position of the crop window.

4. The method of claim 2 wherein cropping the digital image includes

i) selecting a crop window of a rectangular shape and of a similar aspect ratio to the digital image;

and

ii) selecting a zoom factor to determine the size of the crop window such that the crop window encompasses the effective bounding box.

5. The method of claim 2 wherein the weighting function of computing a belief map is a linear weighting function.

6. The method of claim 2 wherein the weighting function of computing a belief map is a constant function.

7. The method of claim 3 wherein computing a belief map includes

i) calculating a subject content index value for the crop window derived from the belief values;

ii) following a positioning procedure of repeating selecting an initial position of the crop window for at least two positions of the crop window; and

iii) using the subject content index values to select the crop window position.

8. The method of claim 1 wherein the crop window is completely within the digital image.

9. The method of claim 2 wherein computing a belief map includes clustering of the belief map to identify at least a cluster of highest belief values corresponding to the main subject, a cluster of intermediate belief values corresponding to secondary subjects, and a cluster of lowest belief values corresponding to background.

10. The method of claim 9 wherein clustering includes setting background portions to a zero belief value.

11. The method of claim 5 further comprising positioning the crop window such that the subject content index of the crop window is at an optimum.

12. The method of claim 3 further comprising positioning the crop window such that the crop window includes all of the main subject cluster.

13. The method of claim 12 further comprising positioning the crop window to include a buffer around the main subject cluster.

14. A computer storage product having at least one computer storage medium having instructions stored therein causing one or more computers to perform the method of claim 1.

15. A method of producing an image of a portion of at least a portion of a photographic image onto a photographic receiver, comprising:

a) receiving a digital image corresponding to the photographic image, the digital image including pixels;

b) computing a belief map of the digital image by using the pixels of the digital image to determine a series of features and using such features to assign a probability of a location of a main subject of the digital image in the belief map;

c) determining a crop window having a shape factor and a zoom factor, the shape and the zoom factors determining a size of the crop window; and

d) locating a relative optical position of a photographic image, a lens assembly, and a photographic receiver in response to the belief map and illuminating a portion of the photographic image of high subject content to produce an image of such portion on the photographic receiver.

16. The method of claim 15 wherein determining a crop window includes

i) computing a weighted center-of-mass of the belief map, the weighted center-of-mass weighted by the belief values of the belief map;

ii) computing weighted central moments of the belief map, relative to the center-of-mass and weighted by a weighting function of each belief value of the belief map;

iii) computing an effective rectangular bounding box according to the central moments; and

iv) determining a crop window having a shape factor and a zoom factor, the shape and the zoom factors determining a size of the crop window.

17. The method of claim 15 wherein locating the relative optical position of a photographic image, a lens assembly, and a photographic receiver includes

i) selecting an initial position of the crop window at a location which includes the center-of-mass;

ii) using the belief values corresponding to the crop window to select the position of the crop window to include a portion of the image of high subject content in response to the belief map; and

iii) cropping the digital image according to the position of the crop window.

18. The method of claim 16 wherein locating the relative optical position of a photographic image, a lens assembly, and a photographic receiver includes

i) selecting a crop window of a rectangular shape and of an identical aspect ratio to the digital image;

and

ii) selecting a zoom factor to determine the size of the crop window such that the crop window encompasses the effective bounding box.

19. The method of claim 16 wherein the weighting function of computing weighted central moments of the belief map is a linear weighting function.

20. The method of claim 16 wherein the weighting function of computing weighted central moments of the belief map is a constant function.

21. The method of claim 17 wherein computing a belief map of the digital image includes

i) calculating a subject content index value for the crop window derived from the belief values;

ii) following a positioning process of repeating selecting an initial position of the crop window at a location which includes the center of the mass for at least two positions of the crop window; and

iii) using the subject content index values to select the crop window position.

22. The method of claim 15 wherein the crop window is completely within the digital image.

23. The method of claim 16 wherein computing a belief map of the digital image includes clustering of the belief map to identify at least a cluster of highest belief values corresponding to the main subject, a cluster of intermediate belief values corresponding to secondary subjects, and a cluster of lowest belief values corresponding to background.

24. The method of claim 23 wherein clustering includes setting background portions to a zero belief value.

25. The method of claim 19 further comprising positioning the crop window such that the subject content index value of the crop window is at an optimum.

26. The method of claim 17 further comprising positioning the crop window such that the crop window includes all of main subject cluster.

27. The method of claim 26 further comprising positioning the crop window to include a buffer around main subject cluster.

28. A computer storage product having at least one computer storage medium having instructions stored therein causing one or more computers to perform the method of claim 15.