Large capacity steganography

• US 6,473,516 B1
• Filed: 05/21/1999
• Issued: 10/29/2002
• Est. Priority Date: 05/22/1998
• Status: Expired due to Term

• Current Assignee: ASA Systems, Inc.
• Original Assignee: ASA Systems, Inc.
• Inventors: Eason, Richard O., Kawaguchi, Eiji
• Primary Examiner(s): Johns, Andrew W.
• Assistant Examiner(s): NAKHJAVAN, SHERVIN K
• Application Number:
  US09/316,883
• Time in Patent Office: 1,257 Days
• Field of Search: 382/100, 382/164, 382/165, 382/171, 382/172, 382/173, 382/175, 382/180, 382/224, 382/228, 382/232, 382/276, 382/286, 382/291, 713/176, 713/179, 713/180, 713/181, 370/523, 370/527, 370/529
• US Class Current: 382/100
• CPC Class Codes: G06T 1/0028 Adaptive watermarking, e.g. Human Visual System [HVS]-based watermarking
• CPC Class Codes: G06T 2201/0051 Embedding of the watermark in the spatial domain
• CPC Class Codes: G06T 2201/0061 Embedding of the watermark in each block of the image, e.g. segmented watermarking
• CPC Class Codes: H04N 1/32235 in highly textured regions
• CPC Class Codes: H04N 1/32251 in multilevel data, e.g. greyscale or continuous tone data
• CPC Class Codes: H04N 2201/3233 of authentication information, e.g. digital signature, watermark
• CPC Class Codes: H04N 2201/327 which are undetectable to the naked eye, e.g. embedded codes

Abstract

A technique for hiding information in an image that is based a property of the human vision system. Because of its relation to human vision properties, the technique of the present invention provides an information hiding capacity is as large as 50% of the original image data. The method includes the steps of segmenting each region of a vessel image into informative and noise-like regions by using a threshold value, arranging the data into a series of data blocks, and embedding each data block into the noise-like regions of the image.

Claims

1. A method for embedding data within a vessel image having a plurality of bit planes said method comprising the steps of:

segmenting the vessel image into a plurality of informative regions and a plurality of noise-like regions based upon at least one statistical property of said regions of the vessel image;

arranging the data into a series of data blocks;

embedding each data block into at least one of said plurality of noise-like regions.

2. The method as claimed in claim 1 wherein said regions are bit-plane regions and said statistical property is a complexity of said region and wherein said step of segmenting each bit plane comprises the steps of:

measuring the complexity of each region; and

determining whether the complexity exceeds a region threshold complexity.

3. The method as claimed in claim 2 wherein said step of measuring a complexity of each of said regions comprises the step of measuring a length of a black and white border in said region.

4. The method as claimed in claim 2 further comprising the steps of:

measuring a complexity of each data block;

determining whether said complexity exceeds a data threshold complexity;

conjugating said data block if said complexity of said data block does not exceed said data threshold complexity; and

creating a conjugation map to indicate which of the data blocks have been conjugated.

5. The method as claimed in claim 4 further comprising the step of embedding the conjugation map into at least one of said plurality of noise-like regions.

6. The method as claimed in claim 5 wherein said conjugation map is disguised utilizing a method chosen from a group consisting of an exclusive-or with value method and an addition with value method.

7. The method as claimed in claim 2 wherein said vessel image is a non-gray coding system image and wherein said method further comprises the steps of:

transforming the vessel image into a gray coding system image prior to said step of segmenting each bit plane; and

transforming a resulting image from a gray coding system image back to a non-gray coding system image after said step of embedding the data.

8. The method as claimed in claim 1 wherein the vessel image includes a plurality of pixels, and wherein said pixels are arranged in an array selected from a group consisting of a triangular array, a rectangular array and a hexagonal array.

9. The method as claimed in claim 1 wherein said regions are image regions and wherein said step of segmenting said vessel image comprises the steps of:

determining a complexity of each image region based on a statistical property of the pixel values within said region; and

determining a number of noise-like bit planes within each image region based upon said complexity of each image region.

10. The method as claimed in claim 9 wherein said step of determining a complexity of each image region comprises the step of determining differences between a plurality of adjacent pixels within said region;

and

wherein said step of determining a number of noise-like bit planes within each image region is based upon a histogram of said differences.

11. The method as claimed in claim 10 wherein said step of determining a number of noise-like bit planes within each image region comprises the steps of:

selecting a threshold value, M, for said histogram of said differences; and

computing said number of planes based upon a value of a logarithm of the value of the Mth largest difference.

12. The method as claimed in claim 10 further comprising the step of:

fitting a plane to pixel data in each region; and

subtracting said plane from each pixel value before computing the pixel differences.

13. The method as claimed in claim 9 further comprising the step of creating a depth map of said noise-like bit planes within each region.

14. The method as claimed in claim 13 further comprising the step of embedding the depth map into at least one of said plurality of noise-like regions.

15. The method as claimed in claim 14 wherein said depth map is disguised utilizing a method chosen from a group consisting of an exclusive-or with value method and an addition with value method.

16. The method as claimed in claim 9 further comprising the step of adding or subtracting a value of 2ⁿ from selected pixels in a noise-like region.

17. The method as claimed in claim 1 wherein said vessel image is an RGB image and wherein said step of segmenting said image comprises the steps of:

segmenting a red component of said vessel image;

segmenting a green component of said vessel image; and

segmenting a blue component of said vessel image.

18. The method as claimed in claim 1 wherein at least one of said data blocks is disguised utilizing a method chosen from a group consisting of an exclusive-or with value method and an addition with value method.

19. A computer program product for controlling a computer for embedding data within a vessel image having a plurality of bit planes, said computer program product comprising:

a recording medium readable by the computer;

means recorded on said recording medium for segmenting the vessel image into a plurality of informative regions and a plurality of noise-like regions based upon at least one statistical property of each region of the vessel image;

means recorded on said recording medium for arranging the data into a series of data blocks; and

means recorded on said recording medium for embedding each data block into one of said plurality of noise-like regions.

20. The computer program product as claimed in claim 19 wherein said statistical property is a complexity of said region and wherein said means for segmenting each bit plane comprises:

a means for measuring the complexity of each region; and

a means for determining whether the complexity exceeds a region threshold complexity.

21. The computer program product as claimed in claim 20 wherein said means for measuring a complexity of each region comprises a means for measuring a length of a black and white border in each region of the vessel image.

22. The computer program product as claimed in claim 20 further comprising:

means recorded on said recording medium for measuring a complexity of each data block;

means recorded on said recording medium for determining whether said complexity exceeds a data threshold complexity;

means recorded on said recording medium for conjugating said data block if said complexity of said data block does not exceed said data threshold complexity; and

means recorded on said recording medium for creating a conjugation map to indicate which of the data blocks have been conjugated.

23. The computer program product as claimed in claim 19 wherein said means for segmenting comprises:

means for determining a complexity of each region of each bit plane by determining differences between a plurality of adjacent pixels within said region; and

means for determining a number of noise-like bit planes within each region based on a histogram of said differences.

24. The computer program product as claimed in claim 23 wherein said means for determining a number of noise-like bit planes within each region comprises a means for selecting a threshold value, M, for said histogram of said differences;

and a means for computing said number of planes based upon a value of a logarithm of the value of the Mth largest difference.

25. The computer program product as claimed in claim 19 wherein said vessel image is an RGB image and wherein said means for segmenting said image comprises:

means for segmenting a red component of said vessel image;

means for segmenting a green component of said vessel image; and

means for segmenting a blue component of said vessel image.