Using classification techniques in digital watermarking
First Claim
1. A method for reading a digital watermark in a media signal comprising:
- assigning sets of media signal samples into classes;
computing a statistical distribution of the classes; and
using the statistical distribution to detect or read a watermark in the media signal.
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Accused Products
Abstract
A classification scheme assigns samples of the watermarked media to classes based on a classification criteria indicating a likely presence of a watermarked signal. Once classified, the scheme models a statistical distribution of the samples in each class. It then assigns a figure of merit to the samples in each class. A watermark detector and reader use the figure of merit to give greater weight to samples that are more likely to contain a watermark signal. Alternatively, the statistical distributions of the classes may be used to derive an estimate of a watermark signal in a pre-filtering stage of a watermark decoder. The watermark decoder then extracts a message from the estimate of the watermark signal.
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Citations
20 Claims
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1. A method for reading a digital watermark in a media signal comprising:
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assigning sets of media signal samples into classes; computing a statistical distribution of the classes; and using the statistical distribution to detect or read a watermark in the media signal. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A method for reading a digital watermark in an image comprising:
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assigning transformed samples of the image into classes using characteristics computed from the samples to group the samples into the classes; modeling a statistical distribution of the samples in each of the classes to compute models of the statistical distributions of the classes; and using the models of the statistical distributions to decode a watermark from the samples. - View Dependent Claims (13, 14)
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15. A method for reading a digital watermark in a watermarked signal comprising:
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assigning samples of the watermarked signal into classes using characteristics computed from the samples to group the samples into the classes; computing a statistical distribution of the samples in each of the classes; and using the statistical distribution to decode a watermark from the watermarked signal. - View Dependent Claims (16, 17, 18)
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19. A method for estimating a watermark signal from a media signal suspected of containing the watermark signal, the method comprising:
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assigning samples of the suspect signal into classes based on a signal characteristic of the samples; modeling distributions of the classes; and estimating the watermark signal based on the suspect signal, the distributions of the classes, and a distribution of the watermark signal. - View Dependent Claims (20)
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Specification