Method for monitoring internet dissemination of image, video, and/or audio files

• US 6,647,128 B1
• Filed: 09/07/2000
• Issued: 11/11/2003
• Est. Priority Date: 11/18/1993
• Status: Expired due to Fees

• Current Assignee: Digimarc Corporation
• Original Assignee: Digimarc Corporation
• Inventors: Rhoads, Geoffrey B.
• Primary Examiner(s): Couso, Jose L.
• Application Number:
  US09/657,148
• Time in Patent Office: 1,160 Days
• Field of Search: 382/100, 382/112, 358/3.28, 358/448, 358/450, 380/54, 380/231-234, 380/287, 283/72, 283/73, 283/93, 283/94, 283/113, 283/901, 348/475.1, 235/494, 340/5.53, 340/5.6, 340/5.65, 340/5.8, 340/5.81, 340/5.83, 340/5.86, 356/71, 902/1, 902/4, 902/6, 713/176, 386/94, 705/1, 705/44
• US Class Current: 382/100
• CPC Class Codes: B42D 25/00 Information-bearing cards or sheet-like structures characterised by identification or security features; Manufacture thereof printing processes to produce identification or security features B41M3/14
• CPC Class Codes: G06F 16/955 using information identifiers, e.g. uniform resource locators [URL]
• CPC Class Codes: G06K 19/06037 multi-dimensional coding
• CPC Class Codes: G06K 19/06046 Constructional details
• CPC Class Codes: G06K 19/14 the marking being sensed by radiation
• CPC Class Codes: G06K 19/18 Constructional details
• CPC Class Codes: G06K 2019/06253 for a specific application
• CPC Class Codes: G06K 7/1417 2D bar codes
• CPC Class Codes: G06K 7/1447 extracting optical codes from image or text carrying said optical code
• CPC Class Codes: G06Q 20/1235 with control of digital rights management [DRM]
• CPC Class Codes: G06Q 20/341 Active cards, i.e. cards including their own processing means, e.g. including an IC or chip
• CPC Class Codes: G06Q 20/40145 Biometric identity checks
• CPC Class Codes: G06T 1/0021 Image watermarking
• CPC Class Codes: G06T 1/005 Robust watermarking, e.g. average attack or collusion attack resistant
• CPC Class Codes: G06T 1/0064 Geometric transfor invariant watermarking, e.g. affine transform invariant
• CPC Class Codes: G06T 2201/0052 Embedding of the watermark in the frequency domain
• CPC Class Codes: G06V 30/40 Document-oriented image-based pattern recognition
• CPC Class Codes: G07C 9/253 visually
• CPC Class Codes: G07D 7/0032 using holograms
• CPC Class Codes: G07D 7/0034 using watermarks
• CPC Class Codes: G07D 7/004 : using digital security elements, e.g. information coded on a magnetic thread or strip
• CPC Class Codes: G07F 17/0014 : for vending, access and use of specific services not covered anywhere else in G07F17/00 meter-controlled dispensing of liquid, gas or electricity G07F15/00
• CPC Class Codes: G07F 17/16 : for devices exhibiting advertisements, announcements, pictures or the like
• CPC Class Codes: G07F 17/26 : for printing, stamping, franking, typing or teleprinting apparatus ticket printing or the like apparatus G07F17/42
• CPC Class Codes: G07F 7/08 : by coded identity card or credit card or other personal identification means without personal verification means G07F7/02
• CPC Class Codes: G07F 7/086 : by passive credit-cards adapted therefor, e.g. constructive particularities to avoid counterfeiting, e.g. by inclusion of a physical or chemical security-layer for security documents G07D7/00; for the reading of record-carriers in general G06K7/00; for the design of coded credit-cards G06K19/10
• CPC Class Codes: G07F 7/1008 : Active credit-cards provided with means to personalise their use, e.g. with PIN-introduction/comparison system
• CPC Class Codes: G07F 7/1016 : Devices or methods for securing the PIN and other transaction-data, e.g. by encryption arrangements for secret communication, see H04L9/00
• CPC Class Codes: G07F 7/12 : Card verification
• CPC Class Codes: G10L 19/018 : Audio watermarking, i.e. embedding inaudible data in the audio signal
• CPC Class Codes: G11B 20/00086 : Circuits for prevention of unauthorised reproduction or copying, e.g. piracy indicating unauthorised use of record carriers in general G11B23/28; scrambling for television signal recording H04N5/913; network architectures or network protocols for network security H04L63/00; cryptographic mechanisms or cryptographic arrangements for secret or secure communication H04L9/00
• CPC Class Codes: G11B 20/00094 : involving measures which result in a restriction to authorised record carriers
• CPC Class Codes: G11B 20/00115 : wherein the record carrier stores a unique medium identifier
• CPC Class Codes: G11B 20/00166 : involving measures which result in a restriction to authorised contents recorded on or reproduced from a record carrier, e.g. music or software
• CPC Class Codes: G11B 20/00181 : using a content identifier, e.g. an international standard recording code [ISRC] or a digital object identifier [DOI]
• CPC Class Codes: G11B 20/0021 : involving encryption or decryption of contents recorded on or reproduced from a record carrier
• CPC Class Codes: G11B 20/00231 : wherein the key is obtained from a local external medium, e.g. a card
• CPC Class Codes: G11B 20/0071 : involving a purchase action
• CPC Class Codes: G11B 20/00884 : involving a watermark, i.e. a barely perceptible transformation of the original data which can nevertheless be recognised by an algorithm
• CPC Class Codes: G11B 20/00891 : embedded in audio data
• CPC Class Codes: H04B 1/665 : using psychoacoustic properties of the ear, e.g. masking effect
• CPC Class Codes: H04L 2463/103 : applying security measure for protecting copy right protecting software against unauthorised usage in a vending or licensing environment, e.g. protection the software providers copyright G06F21/10; data processing systems or methods, specially adapted for payment schemes, architectures or protocols G06Q20/00; secrecy systems or subscription systems H04N7/16
• CPC Class Codes: H04N 1/00005 : relating to image data
• CPC Class Codes: H04N 1/00037 : Detecting, i.e. determining the occurrence of a predetermined state H04N1/00031 takes precedence
• CPC Class Codes: H04N 1/00079 : remotely
• CPC Class Codes: H04N 1/32122 : in a separate device, e.g. in a memory or on a display separate from image data
• CPC Class Codes: H04N 1/32144 : embedded in the image data, i.e. enclosed or integrated in the image, e.g. watermark, super-imposed logo or stamp
• CPC Class Codes: H04N 1/3216 : using Fourier transforms
• CPC Class Codes: H04N 1/32203 : Spatial or amplitude domain methods H04N1/32309 takes precedence
• CPC Class Codes: H04N 1/32208 : involving changing the magnitude of selected pixels, e.g. overlay of information or super-imposition H04N1/32219, H04N1/32224 take precedence
• CPC Class Codes: H04N 1/32251 : in multilevel data, e.g. greyscale or continuous tone data
• CPC Class Codes: H04N 1/32288 : Multiple embedding, e.g. cocktail embedding, or redundant embedding, e.g. repeating the additional information at a plurality of locations in the image
• CPC Class Codes: H04N 1/32352 : Controlling detectability or arrangements to facilitate detection or retrieval of the embedded information, e.g. using markers for decoding, detection or retrieval operations H04N1/32149 and subgroups take precedence
• CPC Class Codes: H04N 2005/91321 : the copy protection signal being a copy protection control signal, e.g. a record inhibit signal
• CPC Class Codes: H04N 2005/91335 : the copy protection signal being a watermark
• CPC Class Codes: H04N 21/23892 : involving embedding information at multiplex stream level, e.g. embedding a watermark at packet level
• CPC Class Codes: H04N 21/8358 : involving watermark protecting executable software by watermarking G06F21/16; image watermarking in general G06T1/0021; watermarks inserted in still images for transmission purposes H04N1/32144; inserting watermarks during video coding H04N19/467
• CPC Class Codes: H04N 2201/3205 : of identification information, e.g. name or ID code H04N2201/3209 takes precedence
• CPC Class Codes: H04N 2201/3207 : of an address
• CPC Class Codes: H04N 2201/3225 : of data relating to an image, a page or a document
• CPC Class Codes: H04N 2201/3226 : of identification information or the like, e.g. ID code, index, title, part of an image, reduced-size image
• 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
• CPC Class Codes: H04N 2201/3271 : Printing or stamping
• CPC Class Codes: H04N 2201/3274 : Storage or retrieval of prestored additional information
• CPC Class Codes: H04N 2201/328 : Processing of the additional information
• CPC Class Codes: H04N 5/913 : for scrambling ; for copy protection
• CPC Class Codes: H04W 24/00 : Supervisory, monitoring or testing arrangements

Abstract

An automated monitoring service downloads image files (including, e.g., graphic and video files) and audio files from various Internet sites, and checks these files for the presence of embedded digital watermark data. When found, such data is decoded and used to identify the proprietor of each watermarked file. The proprietors are alerted to the results of the monitoring operation, often apprising such proprietors of unknown distribution of their image/video/audio properties.

Claims

1. An image processing method comprising:

(i) obtaining a modified image, the modified image being a version of an original image and additionally having embedded signals therein not included in the original image;

the embedded signals having predetermined geometric relationships with respect to each other;

(ii) determining the predetermined geometric relationships of the embedded signals in the modified image;

(iii) operating the processor to compute geometric differences between the modified image and the original image using the predetermined geometric relationships of the embedded signals in the modified image; and

(iv) operating the processor to transform geometric properties of a modified image version of an original image to match geometric properties of the original image using the geometric differences computed between the modified and original images.

2. The method of claim 1 further comprising operating the processor to convert the modified image into at least one of a plurality of individual color representations.

3. The method of claim 2 wherein the plurality of individual color representations include a black white image and a red green image.

4. The method of claim 1 wherein the embedded signals in the modified image are embedded periodic signals.

5. The method of claim 4 wherein the embedded periodic signals include at least two embedded signals.

6. The method of claim 1 wherein the embedded signals form a grid in the modified image.

7. The method of claim 4 wherein determining the geometric relationships of the embedded signals in the modified image comprises:

producing power spectrum image of the modified image;

determining locations in the power spectrum image of local peak power concentrations representing the embedded periodic signals in the modified image; and

computing the geometric relationships among the embedded periodic signals using the locations of the local peak power concentrations.

8. The method of claim 7 wherein the geometric relationships among the embedded periodic signals include phase differences.

9. The method of claim 1,

wherein the geometric differences computed between the modified image and the original image include an image size difference;

the modified image being scaled to a different size than the original image; and

wherein transforming the geometric properties of the modified image includes scaling the size of the modified image to match the size of the original image.

10. The method of claim 1,

wherein the geometric differences computed between the modified image and the original image include an image orientation difference;

the modified image having a different spatial orientation than the original image; and

wherein transforming the geometric properties of the modified image includes rotating the modified image to match the spatial orientation of the original image.

11. The method of claim 1 wherein the modified image further comprises a header.

12. An image processing method for decoding periodic signals embedded in an image,

the method comprising:

(i) operating a processor to obtain an image, the image including a set of n periodic signals embedded therein, having geometric relationships with respect to each other;

(ii) operating the processor to identify a plurality of local peak power concentrations in a two dimensional spatial frequency power spectrum of the image;

(iii) operating the processor to eliminate a subset of the local peak power concentrations below a threshold;

a remaining subset of the local peak power concentrations being determined to be candidate local peak power concentrations corresponding to the set of n periodic signals; and

(iv) operating the processor to compute a best mapping between sets of n candidate local peak power concentrations in the image;

the best mapping identifying the spatial frequencies of the set of n periodic signals embedded in the image.

13. The method of claim 12, wherein the set of n periodic signals embedded in the image is a set of n graticules.

14. The method of claim 12 wherein the set of n signals includes at least two signals having different phases.

15. The method of claim 12, wherein the image is a color image;

wherein the set of n periodic signals embedded in the color image are embedded in at least one of a plurality of image representations of the color image.

16. The method of claim 15 wherein the image representations include an RGB format.

17. An article of manufacture, the article comprising:

a data storage medium that can be accessed by a storage medium access device when the article is used in a machine; and

instructions stored in the data storage medium so that the storage medium access device can provide the instructions to a processor when the article is used;

the processor, in executing the instructions, obtaining a modified image;

the modified image being a version of an original image and additionally having embedded signals therein not included in the original image;

the embedded signals having geometric relationships with respect to each other;

the processor, further in executing the instructions, determining the geometric relationships of the embedded signals in the modified image;

the processor, further in executing the instructions, computing geometric differences between the modified image and the original image using the geometric relationships of the embedded signals in the modified image; and

the processor, still further in executing the instructions, transforming geometric properties of a modified image version of an original image to match geometric properties of the original image using the geometric differences computed between the modified and original images.

18. An image processing method, the method comprising:

(i) obtaining a modified image, the modified image being a version of an original image and additionally having embedded signals therein not included in the original image;

the embedded signals having predetermined mathematical relationships with respect to each other;

(ii) determining the predetermined mathematical relationships of the embedded signals in the modified image;

(iii) operating the processor to compute mathematical differences between the modified image and the original image using the predetermined mathematical relationships of the embedded signals in the modified image; and

(iv) operating the processor to transform mathematical properties of a modified image version of an original image to match mathematical properties of the original image using the mathematical differences computed between the modified and original images.

19. The method of claim 18 further comprising operating the processor to convert the modified image into at least one of a plurality of individual color representations.

20. The method of claim 19 wherein the plurality of individual color representations include a black-white image and a red-green-image.

21. The method of claim 18 wherein the embedded signals in the modified image are embedded periodic signals.

22. The method of claim 21 wherein the embedded periodic signals include at least two embedded signals.

23. The method of claim 18 wherein the embedded signals form a grid in the modified image.

24. The method of claim 21 wherein determining the mathematical relationships of the embedded signals in the modified image using the mathematical constraint data includes

producing power spectrum image of the modified image;

determining locations in the power spectrum image of local peak power concentrations representing the embedded periodic signals in the modified image; and

computing the mathematical relationships among the embedded periodic signals using the locations of the local peak power concentrations.

25. The method of claim 24 wherein the mathematical relationships among the embedded periodic signals include phase differences.

26. The method of claim 18,

wherein the mathematical differences computed between the modified image and the original image include an image size difference;

the modified image being scaled to a different size than the original image; and

wherein transforming the mathematical properties of the modified image includes scaling the size of the modified image to match the size of the original image.

27. The method of claim 18,

wherein the mathematical differences computed between the modified image and the original image include an image orientation difference;

the modified image having a different spatial orientation than the original image; and

wherein transforming the mathematical properties of the modified image includes rotating the modified image to match the spatial orientation of the original image.

28. The method of claim 18 wherein the modified image further comprises a header.

29. An image processing method for decoding periodic signals embedded in an image, the method comprising:

(i) operating a processor to obtain an image, the image including a set of n periodic signals embedded therein, having mathematical relationships with respect to each other;

(ii) operating the processor to identify a plurality of local peak power concentrations in a two-dimensional spatial frequency power spectrum of the image;

(iii) operating the processor to eliminate a subset of the local peak power concentrations below a threshold;

a remaining subset of the local peak power concentrations being determined to be candidate local peak power concentrations corresponding to the set of n periodic signals; and

(iv) operating the processor to compute a best mapping between sets of n candidate local peak power concentrations in the image and a set of n periodic signals indicated by the mathematical constraint data;

the best mapping identifying the spatial frequencies of the set of n periodic signals embedded in the image.

30. The method of claim 29, wherein the set of n periodic signals embedded in the image is a set of n graticules.

31. The method of claim 29 wherein the set of n signals includes at least two signals having different phases.

32. The method of claim 29, wherein the image is a color image;

wherein the set of n periodic signals embedded in the color image are embedded in at least one of a plurality of image representations of the color image.

33. The method of claim 32, wherein the image representations include an RGB format.

34. An article of manufacture,

the article comprising:

a data storage medium that can be accessed by a storage medium access device when the article is used in a machine; and

instructions stored in the data storage medium so that the storage medium access device can provide the instructions to a processor when the article is used;

the processor, in executing the instructions, obtaining a modified image;

the modified image being a version of an original image and additionally having embedded signals therein not included in the original image;

the embedded signals having mathematical relationships with respect to each other;

the processor, further in executing the instructions, determining the mathematical relationships of the embedded signals in the modified image;

the processor, further in executing the instructions, computing mathematical differences between the modified image and the original image using the mathematical relationships of the embedded signals in the modified image; and

the processor, still further in executing the instructions, transforming mathematical properties of a modified image version of an original image to match mathematical properties of the original image using the mathematical differences computed between the modified and original images.