1. Field of Invention
The present invention is related to a watermarking method, and more specifically, to a blind wavelet-based watermarking method.
2. Description of Related Art
In recent years, due to the growth and improvement in technology of communication network, many enterprises, corporations and academic organizations have applied the Internet to commercial or academic activities for business or research promotion. The activities include, for example, electronic document transmitting, digital image sharing, on-line filming, and on-line radio broadcast. A great convenience has been obtained for the users. However, problems regarding information security such as embezzlement, interpolation and allonym transaction occur. Although many of these problems can be resolved by encryption/decryption technique, copyright approval and verification for the network transmission of valuable medium (such as image, film and music) have become a significant issue for the medium owners. Moreover, as digital cameras and scanners have become popular, digital photographs have become widely distributed over the network. Such a broad distribution results in interpolation and appropriation problems for the photographs, and a copyright protection issue thus occurs. Watermarking is one of the methods to resolve such problems.
The watermarking technique is categorized into spatial domain and frequency domain. In the spatial domain, digital data value is directly changed to embed the watermark. For example, Nikolaidis et al. published their research work “Robust image watermarking in the spatial domain” on “Signal Process”, Vol. 66, No. 3, pp. 385-403, 1998, and Schyndel et al. published another research work “A digital watermark” on “IEEE International Conference on Image Processing”, Vol. 2, pp. 86-90, 1994. Such methods in the spatial domain have the advantage of fast operation speed, but it is hard to resist damage caused by various types of signal processes, i.e. attacks.
In the frequency domain, the digital data is transformed into frequency domain, using Fourier transform, discrete cosine transform (DCT), or wavelet transform. For example, Cox et al. published a research work “Secure spread spectrum watermarking for multimedia” on “IEEE Transactions on Image Processing”, Vol. 6, No. 12, pp. 1673-1687, December 1997. Zhu et al. published a research work “Multiresolution watermarking for images and video” on “IEEE Transactions on Circuits Systems for Video Technology”, Vol. 9, No. 4, pp. 545-550, June 1999. Huo et al. published a research work “A wavelet based image watermarking scheme” on “IEEE International Conference on Image Processing”, pp. 2573-2576, October 2006. Solachidis et al. published a research work “Circularly symmetric watermark embedding in 2-D DFT domain” on “IEEE Transactions on Image Processing”, Vol. 6, No. 11, pp. 1741-1753, November 2001. Yen et al. published a research work “Blind watermarking based on the wavelet transform” on “Proceeding of Seventh International Conference on Parallel and Distributed Computing, Applications and Technologies”, pp. 474-478, December 2006. Li et al. published a research work “Adaptive watermarking algorithm using SVR in wavelet domain” on “IEEE of International Conference on Computer and Information Science”, pp. 207-211, July 2007.
After transformation in the frequency domain, coefficients of specific subbands for the transformation are obtained and used to embed the watermark. The digital data with embedded watermark then is converted to the previous spatial domain by executing inverse Fourier transform, inverse DCT or inverse wavelet transform such that the watermarked data resembling the original data is obtained. The methods performed in the frequency domain require a huge operation, but have a better capability to resist various attacks. Nevertheless, the methods of Cox et al. and Zhu et al. must compare the watermarked data with the original data to obtain the embedded watermark such that the transmission load of data cannot be reduced to achieve the purpose for effective transmission. Additionally, although the methods of Huo et al. and Solachidis et al. can extract the embedded watermark without using the original data, the original watermark or other additive information is still required. Further, even though the methods of Yen et al. and Li et al. are capable of extracting the embedded watermark merely according to the watermarked data, the capacity for hiding the watermark is extremely limited. Through an accurate calculation based on the methods of Yen et al. and Li et al., a ratio of the data amount of the embedded watermark to the data amount of the original data is 1.5625%, i.e.
  1      4    3  for a 3-level wavelet transform.
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