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Automated digital watermarking methods using neural networksRelated Patent Categories: Image Analysis, ApplicationsAutomated digital watermarking methods using neural networks description/claimsThe Patent Description & Claims data below is from USPTO Patent Application 20060239504, Automated digital watermarking methods using neural networks. Brief Patent Description - Full Patent Description - Patent Application Claims
CROSS-REFERENCE TO RELATED APPLICATIONS [0001] This non-provisional patent application claims the benefit of U.S. Provisional Patent Application No. 60/315,223, entitled "Maximum-Strength Multi-Resolution Watermarking of Digital Products Using Neural Networks," filed Aug. 28, 2001 and U.S. Non-Provisional patent application Ser. No. 10/134,255, entitled "Automated Digital Watermarking Methods Using Neural Networks," filed Apr. 29, 2002. FIELD OF THE INVENTION [0002] The present invention relates generally to the field of digital information security. Specifically, the present invention relates to copyright protection for digital products, or digital watermarking. More specifically, the present invention relates to automated digital watermarking methods using neural networks. The methods of the present invention may also be applied to non-digital applications. BACKGROUND OF THE INVENTION [0003] The explosive growth of globally-distributed computer networks, such as the Internet and broadband networks, the presence of relatively large storage devices and data archives, and the development of efficient compression standards have provided digital image producers and others with a variety of means for distributing their images and other productions. However, these advancements have also made it relatively simple for copyright violators and others to create illegal copies of these images and other productions. As a result, a variety of conventional digital watermarking methods have been proposed. A digital watermark encodes an owner's copyright and/or tracking information and embeds it into an image or other production. Preferably, this digital watermark is invisible to the human eye and may only be perceived by a computer or the like. Digital watermarking methods may be used to identify the owner of an image or other production, to track illegal copies of the image or other production, and to facilitate the licensing of the image or other production. For a digital watermarking method to be successful, the digital watermark must be unobtrusive and must not degrade the perceptual quality of the image or other production. The digital watermark must also be resistant to attacks from a variety of image and signal processing tools and techniques, both unintentional and intentional. Such attacks may include, for example, image compression, smoothing, low-pass filtering, cropping, geometric transformation (including translation, rotation, and scaling), noise addition, printing and scanning, and collusion. [0004] In general, a digital watermark may be applied in either the spatial (pixel) domain or the transform domain. Transform domain digital watermarking methods, such as discrete cosine transform (DCT) and discrete wavelet transform (DWT) digital watermarking methods, typically provide relatively high image fidelity and are resistant to image manipulations. Wavelet-based digital watermarking techniques have multi-resolution hierarchical characteristics that mimic human visual (and audio) perception and allow for the independent processing of the resulting components. With wavelet-based digital watermarking techniques, digital watermark detection may be achieved at relatively low image resolutions, saving computational load. In addition, the high-frequency sub-bands of a wavelet transform include the edges and textures of an image and the human eye is typically insensitive to changes in such sub-bands. This allows digital watermark to be added to the sub-bands without being perceived by the human eye. Wavelets are used in a variety of emerging image and video compression standards, such as JPEG2000 and MPEG4, encouraging the use of wavelet-based digital watermarking. Although embodiments and examples of the present invention deal with transform-based imperceptible digital watermarking methods, the principles and techniques of the present invention are also applicable to spatial (time)-based imperceptible digital watermarking methods as well. [0005] A variety of conventional wavelet-based digital watermarking methods have been proposed. All of these methods are designed to be resistant to a variety of attacks. Typically, these digital watermarking methods insert a digital watermark into the high-frequency contents of an image or other product. Although marginally effective with respect to some types of attacks, the conventional digital watermarking methods are vulnerable to attack if techniques such as low-pass filtering are used. In addition, the conventional digital watermarking methods tend to be labor-intensive, relatively slow, and lack the ability to be adequately automated. [0006] Thus, what is needed is a digital watermarking method that embeds a digital watermark in both the low and high frequencies of an image or other production, providing a digital watermark that is resistant to a variety of attacks. This digital watermarking method should optimize the strength of the embedded digital watermark such that it is as powerful as possible without being perceptible to the human eye. The digital watermarking method should do this relatively quickly, in real-time, and in an automated fashion using an intelligent system, such as a neural network. The watermarking method should also be able to be used in a variety of new applications, such as the watermarking of sensitive aircraft parts, military equipment, and machines. BRIEF SUMMARY OF THE INVENTION [0007] Embodiments of the present invention provide digital watermarking methods that embed a digital watermark in both the low and high frequencies of an image or other production, providing a digital watermark that is resistant to a variety of attacks. The digital watermarking methods of the present invention optimize the strength of the embedded digital watermark such that it is as powerful as possible without being perceptible to the human eye. The digital watermarking methods of the present invention do this relatively quickly, in real-time, and in an automated fashion using an intelligent system, such as a neural network. The watermarking methods of the present invention may also be used in a variety of new applications, such as the watermarking of sensitive aircraft parts, military equipment, and machines such that the destruction of a watermark associated with a given machine compromises the function of the machine. [0008] In one embodiment of the present invention, a digital watermarking method includes calculating a discrete transform including a plurality of frequency bands and inserting a plurality of digital watermarks into the plurality of frequency bands, wherein each of the plurality of digital watermarks has a predetermined weight. [0009] In another embodiment of the present invention, a computer-readable medium having executable commands operable for digitally watermarking a production includes executable commands operable for calculating a discrete transform including a plurality of frequency bands and inserting a plurality of digital watermarks into the plurality of frequency bands, wherein each of the plurality of digital watermarks has a predetermined weight. [0010] In a further embodiment of the present invention, an automated watermarking method includes creating a database including a first plurality of productions and receiving a first plurality of scores associated with the quality of the first plurality of productions from a plurality of human subjects. The automated watermarking method also includes providing information associated with the first plurality of productions and the first plurality of scores to an intelligent system and training the intelligent system to generate a second plurality of scores associated with the quality of the first plurality of productions, wherein the second plurality of scores is substantially the same as the first plurality of scores. The automated watermarking method further includes providing information associated with a second plurality of productions to the intelligent system, receiving a third plurality of scores associated with the quality of the second plurality of productions from the intelligent system, and optimizing the strength of a watermark using the third plurality of scores. [0011] In a further embodiment of the present invention, a computer-readable medium having executable commands operable for digitally watermarking a production in an automated fashion includes executable commands operable for creating a database including a first plurality of productions and receiving a first plurality of scores associated with the quality of the first plurality of productions from a plurality of human subjects. The executable commands are also operable for providing information associated with the first plurality of productions and the first plurality of scores to an intelligent system and training the intelligent system to generate a second plurality of scores associated with the quality of the first plurality of productions, wherein the second plurality of scores is substantially the same as the first plurality of scores. The executable commands are further operable for providing information associated with a second plurality of productions to the intelligent system, receiving a third plurality of scores associated with the quality of the second plurality of productions from the intelligent system, and optimizing the strength of a digital watermark using the third plurality of scores. BRIEF DESCRIPTION OF THE DRAWINGS [0012] FIG. 1 is a representation of a photograph illustrating the decomposition of an image using an automated digital watermarking method of the present invention; [0013] FIG. 2 is a flow chart of one embodiment of the automated digital watermarking method of the present invention, the digital watermarking method using a neural network; [0014] FIG. 3 is a plot of a training curve for the neural network used in accordance with the automated digital watermarking method of the present invention; [0015] FIG. 4 is a functional block diagram of one embodiment of an automated digital watermarking system of the present invention; and [0016] FIG. 5 is a functional block diagram of another embodiment of the automated watermarking system of the present invention. DETAILED DESCRIPTION OF THE INVENTION [0017] In a variety of embodiments and examples, the present invention provides automated methods, systems, and computer-readable media for digital watermarking using neural networks. In the description that follows, specific details are set forth in order to provide a thorough understanding of the present invention. It will be obvious, however, to one of ordinary skill in the art that the methods, systems, and computer-readable media of the present invention may be practiced with or without the inclusion of some or all of these specific details. For example, although the description that follows focuses on using a discrete wavelet transform (DWT) for the space-frequency decomposition of an image or other production, any other suitable frequency transformation may be used, including a discrete Fourier transform (DFT) or a discrete cosine transform (DCT). Likewise, although the description that follows focuses on the digital watermarking of "images," any other suitable production may be digitally watermarked, including audio and video productions. Familiar tools and techniques have not been described in detail in order to avoid obscuring the novel features of the present invention. [0018] A DWT divides a signal into low and high scales (bands). The high-scale component is split again into low and high frequencies. This process is repeated a plurality of times. The original signal may be reconstructed using an inverse discrete wavelet transform (IDWT). The DWT and IDWT are defined for one-dimensional (1-D) and two-dimensional (2-D) signals, such as images. The DWT (or IDWT) for a 2-D image x[m,n] is implemented by applying the 1-D DWT (or IDWT) separately for each dimension, as follows: DWT(x[m,n])=DWT.sub.n[DWT.sub.m(x[m,n]) ]. (1) Continue reading about Automated digital watermarking methods using neural networks... 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