## A dual Fourier-wavelet domain authentication-identification watermark

Optics Express, Vol. 15, Issue 8, pp. 4804-4813 (2007)

http://dx.doi.org/10.1364/OE.15.004804

Acrobat PDF (198 KB)

### Abstract

A dual Fourier-Wavelet domain watermarking technique for authentication and identity verification is proposed. Discrete wavelet transform (DWT) domain spread spectrum is used for embedding identity (such as registration number, transaction ID etc.) information. While a blind detector detects an ID, it is important to validate with other ancillary data. To satisfy that requirement, we embed a robust signature and hide it in a mid-band wavelet subband using Fourier domain bit-embedding algorithm. Results are furnished to show the compression tolerance of the method.

© 2007 Optical Society of America

## 1. Introduction

## 2. Proposed Fourier-Wavelet domain watermark

### 2.1 Embedding authentication signature

3. F. Ahmed and I. S. Moskowitz, “Correlation-based watermarking
method for image authentication applications,”
Opt. Eng. **43**1833–1838
(2004). [CrossRef]

8. J. L. Horner and J. R. Leger, “Pattern recognition with Binary
phase-only filters,” Appl. Opt. **24**, 609–611
(1985). [CrossRef] [PubMed]

4. F. Ahmed and I. S. Moskowitz, “Phase Signature-based Image
Authentication watermark robust to compression and
coding,” Proc. SPIE **5561**, 133–144
(2004). [CrossRef]

*x(m,n)*. During the signature generation phase

*x(m,n)*represents the A1 image. The DFT of

*x(m,n)*can be represented in polar form with its magnitude and phase as following,

*X(u,v)*is the

*magnitude*part of the frequency component given by |

*H(u,v)*|, and

*ϕ(u,v)*is the phase part of frequency

*H(u,v)*given by

### 2.2 Embedding Identity info

*m*. This could be a unique identification number of an image, or a registration or serial number, or any other tracking number.

*W*which is made the same size as the subband under consideration. The key,

_{m,}*k*is used as a seed in pseudorandom number generator, to come up with the pattern

*W*, which is also the same size as the subband image. These two binary patterns (

_{k}*W*and

_{k}*W*) are then combined, which can take as simple as an XOR operation as follows.

_{m}### 2.3 Detection: authentication and identification

^{2}norm, in this paper). Specifically, our selection is based on the fact that, authentication is a 1-bit decision, while identification involves the extraction of multiple bits of embedded information. Hence, identification needs a better embeddable subband. And we argue that the subband with more energy (or entropy in this case) will be better embeddable.

*ϕ*, of the Fourier transform of the approximate subband (A1 or A2), we then compute phase-only-filter (POF) as

_{A}(u,v)## 3. Simulation and results

### 3.1 Which Wavelet?

### 3.2 Image Database

9. USC-SIPI Image Database, http://sipi.usc.edu/services/database/Database.html

### 3.3 Detection metrics

^{A}

_{POF}(u, v)] of the approximate band and the extracted BPOF. Figure 4(b) shows the result. While both metrics yield in similar performance, it turns out that the correlation-based metric offers better discrimination between a marked and unmarked image. For the rest of the simulation, we therefore use the PSR metric.

### 3.4 Quality of the watermarked image

*PSNR (peak signal to noise ratio)*as the quality indicator, which is defined as follows. The

*PSNR*of a watermarked image I

_{w}, with respect to the original image I

_{o}(both represented in 8-bit gray scale with peak intensity of 255), is given by,

### 3.5 Compression performance

## 4. Conclusion

## Acknowledgments

## References and links

1. | I. Cox, J. Bloom, and M. Miller, |

2. | T. Liu and Z.-D. Qiu, “The survey of digital
watermarking-based image authentication
techniques,” 6th International Conference on Signal
Processing, |

3. | F. Ahmed and I. S. Moskowitz, “Correlation-based watermarking
method for image authentication applications,”
Opt. Eng. |

4. | F. Ahmed and I. S. Moskowitz, “Phase Signature-based Image
Authentication watermark robust to compression and
coding,” Proc. SPIE |

5. | P. Meerwald and A. Uhl, “A survey of wavelet domain
watermarking algorithms,” Proc. SPIE |

6. | S. Mallat, |

7. | J. Fridrich and M. Goljan, “Robust hash functions for digital watermarking,” IEEE Proc. Int. Conf. on Information Technology: Coding and Computing,” 178 – 183 (2000). |

8. | J. L. Horner and J. R. Leger, “Pattern recognition with Binary
phase-only filters,” Appl. Opt. |

9. | USC-SIPI Image Database, http://sipi.usc.edu/services/database/Database.html |

**OCIS Codes**

(070.4550) Fourier optics and signal processing : Correlators

(100.7410) Image processing : Wavelets

**ToC Category:**

Fourier Optics and Optical Signal Processing

**History**

Original Manuscript: January 2, 2007

Revised Manuscript: March 12, 2007

Manuscript Accepted: March 13, 2007

Published: April 5, 2007

**Citation**

Farid Ahmed, "A dual Fourier-wavelet domain authentication-identification watermark," Opt. Express **15**, 4804-4813 (2007)

http://www.opticsinfobase.org/oe/abstract.cfm?URI=oe-15-8-4804

Sort: Year | Journal | Reset

### References

- I. Cox, J. Bloom, and M. Miller, Digital watermarking: Principles & Practice (Morgan Kauffman Publishers, 2001).
- T. Liu and Z.-D. Qiu, "The survey of digital watermarking-based image authentication techniques," 6th International Conference on Signal Processing 2, 1556 - 1559 (2002).
- F. Ahmed and I. S. Moskowitz, "Correlation-based watermarking method for image authentication applications," Opt. Eng. 43, 1833-1838 (2004). [CrossRef]
- F. Ahmed and I. S. Moskowitz, "Phase Signature-based Image Authentication watermark robust to compression and coding," Proc. SPIE 5561, 133-144 (2004). [CrossRef]
- P. Meerwald and A. Uhl, "A survey of wavelet domain watermarking algorithms," Proc. SPIE 4314, 505-516 (2001). [CrossRef]
- S. Mallat, A Wavelet Tour of Signal Processing (Academic Press, NY, 1998).
- J. Fridrich and M. Goljan, "Robust hash functions for digital watermarking," IEEE Proc. Int. Conf. on Information Technology: Coding and Computing," 178 - 183 (2000).
- J. L. Horner and J. R. Leger, "Pattern recognition with Binary phase-only filters," Appl. Opt. 24, 609-611 (1985). [CrossRef] [PubMed]
- USC-SIPI Image Database, http://sipi.usc.edu/services/database/Database.html

## Cited By |
Alert me when this paper is cited |

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.

« Previous Article | Next Article »

OSA is a member of CrossRef.