Digital watermarking employing noise model

• US 20030021440A1
• Filed: 04/17/2002
• Published: 01/30/2003
• Est. Priority Date: 11/18/1993
• Status: Abandoned Application

• Current Assignee: Digimarc Corporation
• Original Assignee: Digimarc Corporation
• Inventors: Rhoads, Geoffrey B.
• Application Number:
  US10/125,053
• Publication Number:
  US 20030021440A1
• Time in Patent Office: Days
• US Class Current: 382/100
• CPC Class Codes: G06F 12/1408 by using cryptography for digital transmission H04L9/00
• 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 1/005 Robust watermarking, e.g. average attack or collusion attack resistant
• CPC Class Codes: G06T 1/0057 Compression invariant watermarking
• CPC Class Codes: G06T 2201/0052 Embedding of the watermark in the frequency domain
• CPC Class Codes: G07C 9/253 visually
• CPC Class Codes: G07D 7/0032 using holograms
• CPC Class Codes: G07D 7/004 using digital security elements, e.g. information coded on a magnetic thread or strip
• CPC Class Codes: G07F 17/16 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 20/00007 Time or data compression or expansion audio compression based on psychoacoustics G10L19/00; data processing for reproducing audio data at different playback speeds G10L21/04; video compression H04N19/00; data compression per se H03M7/30
• 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 20/00884 : 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: G11B 20/10037 : A/D conversion, D/A conversion, sampling, slicing and digital quantisation or adjusting parameters thereof
• CPC Class Codes: G11B 20/10527 : Audio or video recording; Data buffering arrangements G11B20/12 - G11B20/18 take precedence
• CPC Class Codes: G11B 2020/00014 : the compressed signal being an audio signal
• CPC Class Codes: G11B 2020/10546 : specifically adapted for audio data
• CPC Class Codes: G11B 2020/10555 : wherein the frequency, the amplitude, or other characteristics of the audio signal is taken into account
• CPC Class Codes: H04B 1/665 : using psychoacoustic properties of the ear, e.g. masking effect
• 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 1/32144 : 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 1/32149 : Methods relating to embedding, encoding, decoding, detection or retrieval operations
• 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 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 2005/91342 : the copy protection signal being an authentication signal
• CPC Class Codes: H04N 2005/9135 : by superimposing the spectrally spread copy protection signal onto the video signal
• 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 2201/3226 : 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 2201/328 : Processing of the additional information
• CPC Class Codes: H04N 5/89 : using holographic recording H04N5/91 takes precedence
• CPC Class Codes: H04N 5/90 : on discs or drums
• CPC Class Codes: H04N 5/913 : for scrambling ; for copy protection
• CPC Class Codes: H04N 9/8042 : involving data reduction
• CPC Class Codes: H04N 9/8047 : using transform coding
• CPC Class Codes: H04N 9/8205 : involving the multiplexing of an additional signal and the colour video signal
• CPC Class Codes: Y10S 283/901 : Concealed data

Abstract

A noise model is applied to digital signals, such as digital image and audio signals, to determine a tolerable noise level for embedding an auxiliary data carrying signal into the digital signals.

Claims

1. A method for determining a maximum imperceptible amount of noise which can be added to a digitized analog signal, the method comprising:

producing noise thresholds according to a psycho-sensory model;

determining a continuously differentiable function which approximates a quantization error permissible by the noise thresholds;

estimating a preferred gain for each one of the noise thresholds according to the continuously differentiable function, wherein the preferred gains for the respective noise thresholds collectively represent the maximum imperceptible amount of noise.

2. The method of claim 1 wherein the psycho-sensory model is a psycho-acoustic model.

3. The method of claim 1 wherein the psycho-sensory model is a psycho-visual model.

4. The method of claim 1 wherein determining the continuously differentiable function comprises:

determining a local quantization step-size function.

5. A method for encoding embedded data in a digitized analog signal, the method comprising:

determining a maximum imperceptible amount of noise which can be added to a digitized analog signal by;

producing noise thresholds according to a psycho-sensory model;

determining a continuously differentiable function which approximates a quantization error permissible by the noise thresholds;

estimating a preferred gain for each one of the noise thresholds according to the continuously differentiable function, wherein the preferred gains for the respective noise thresholds collectively represent the maximum imperceptible amount of noise;

forming a basis signal from the digitized analog signal such that the basis signal is no greater than the maximum imperceptible amount of noise;

encoding the embedded data into the basis signal to form an encoded basis signal; and

adding the encoded basis signal to the digitized analog signal to form an encoded digitized analog signal.

6. The method of claim 5 wherein the psycho-sensory model is a psycho-acoustic model.

7. The method of claim 5 wherein the psycho-sensory model is a psycho-visual model.

8. The method of claim 5 wherein determining the continuously differentiable function comprises:

determining a local quantization step-size function.

9. The method of claim 5 wherein forming the basis signal comprises:

spread-spectrum chipping a noise threshold spectrum representing the noise thresholds in accordance with a stream of pseudo-random bits.

10. A computer readable medium useful in association with a computer which includes a processor and a memory, the computer readable medium including computer instructions which are configured to cause the computer to determine a maximum imperceptible amount of noise which can be added to a digitized analog signal by:

producing noise thresholds according to a psycho-sensory model;

determining a continuously differentiable function which approximates a quantization error permissible by the noise thresholds;

estimating a preferred gain for each one of the noise thresholds according to the continuously differentiable function, wherein the preferred gains for the respective noise thresholds collectively represent the maximum imperceptible amount of noise.

11. The computer readable medium of claim 10 wherein the psycho-sensory model is a psycho-acoustic model.

12. The computer readable medium of claim 10 wherein the psycho-sensory model is a psycho-visual model.

13. The computer readable medium of claim 10 wherein determining the continuously differentiable function comprises:

determining a local quantization step-size function.

14. A computer readable medium useful in association with a computer which includes a processor and a memory, the computer readable medium including computer instructions which are configured to cause the computer to encode embedded data in a digitized analog signal by:

determining a maximum imperceptible amount of noise which can be added to a digitized analog signal by;

producing noise thresholds according to a psycho-sensory model;

determining a continuously differentiable function which approximates a quantization error permissible by the noise thresholds;

estimating a preferred gain for each one of the noise thresholds according to the continuously differentiable function, wherein the preferred gains for the respective noise thresholds collectively represent the maximum imperceptible amount of noise;

forming a basis signal from the digitized analog signal such that the basis signal is no greater than the maximum imperceptible amount of noise;

encoding the embedded data into the basis signal to form an encoded basis signal; and

adding the encoded basis signal to the digitized analog signal to form an encoded digitized analog signal.

15. The computer readable medium of claim 14 wherein the psycho-sensory model is a psycho-acoustic model.

16. The computer readable medium of claim 14 wherein the psycho-sensory model is a psycho-visual model.

17. The computer readable medium of claim 14 wherein determining the continuously differentiable function comprises:

determining a local quantization step-size function.

18. The computer readable medium of claim 14 wherein forming the basis signal comprises:

spread-spectrum chipping a noise threshold spectrum representing the noise thresholds in accordance with a stream of pseudo-random bits.

19. A computer system comprising:

a processor;

a memory operatively coupled to the processor; and

a noise threshold generator (i) which executes in the processor from the memory and (ii) which, when executed by the processor, causes the computer to determine a maximum imperceptible amount of noise which can be added to a digitized analog signal by;

producing noise thresholds according to a psycho-sensory model;

determining a continuously differentiable function which approximates a quantization error permissible by the noise thresholds;

estimating a preferred gain for each one of the noise thresholds according to the continuously differentiable function, wherein the preferred gains for the respective noise thresholds collectively represent the maximum imperceptible amount of noise.

20. The computer system of claim 19 wherein the psycho-sensory model is a psycho-acoustic model.

21. The computer system of claim 19 wherein the psycho-sensory model is a psycho-visual model.

22. The computer system of claim 19 wherein determining the continuously differentiable function comprises:

determining a local quantization step-size function.

23. A computer system comprising:

a processor;

a memory operatively coupled to the processor; and

an encoder module (i) which executes in the processor from the memory and (ii) which, when executed by the processor, causes the computer to encode embedded data in a digitized analog signal by;

determining a maximum imperceptible amount of noise which can be added to a digitized analog signal by;

producing noise thresholds according to a psycho-sensory model;

determining a continuously differentiable function which approximates a quantization error permissible by the noise thresholds;

estimating a preferred gain for each one of the noise thresholds according to the continuously differentiable function, wherein the preferred gains for the respective noise thresholds collectively represent the maximum imperceptible amount of noise;

forming a basis signal from the digitized analog signal such that the basis signal is no greater than the maximum imperceptible amount of noise;

encoding the embedded data into the basis signal to form an encoded basis signal; and

adding the encoded basis signal to the digitized analog signal to form an encoded digitized analog signal.

24. The computer system of claim 23 wherein the psycho-sensory model is a psycho-acoustic model.

25. The computer system of claim 23 wherein the psycho-sensory model is a psycho-visual model.

26. The computer system of claim 23 wherein determining the continuously differentiable function comprises:

determining a local quantization step-size function.

27. The computer system of claim 23 wherein forming the basis signal comprises:

spread-spectrum chipping a noise threshold spectrum representing the noise thresholds in accordance with a stream of pseudo-random bits.