Feature-based watermark localization in digital capture systems
AssigneeDigimarc Corporation
InventorsVojtech Holub, Tomas Filler
Life of this patent
Estimating the term…
Abstract
The present disclosures relates generally to digital watermarking and data hiding. One claim recites a method comprising: obtaining data representing captured imagery, the captured imagery depicting packaging including digital watermarking, the digital watermarking including an orientation signal that is detectable in a transform domain; generating a n-dimensional feature set of the data representing captured imagery, the n-dimensional feature set representing the captured imagery in a spatial domain, where n is an integer great than 13; using a trained classifier to predict the presence of the orientation signal in a transform domain from the feature set in the spatial domain. Of course, other claims and combinations are provided too.
Claims18
A method comprising:
- decomposing data representing an image into subcomponents;
- extracting predetermined features from each of the subcomponents;
- providing the features to a trained logistic regressor for estimating a probability associated with digital watermarking for each the subcomponents;
- generating a probability map relative to the image based on probabilities generated by the trained logistic regressor;
- and
- selecting n subcomponents from the probability map, where each of the selected n subcomponents has a probability exceeding a predetermined threshold, where n is a positive integer greater than 1.
An apparatus comprising:
- memory for storing data representing an image;
- one or more processors for:
- decomposing the data representing an image into subcomponents;
- extracting predetermined features from each of the subcomponents;
- and
- providing the features to a trained logistic regressor for estimating a signal characteristic associated with digital watermarking contained in each the subcomponents;
- means for constructing a probability map relative to the image based on estimated signal characteristics generated by the trained logistic regressor;
- and
- means for selecting n subcomponents based on estimated signal characteristics, in which each of the selected n subcomponents has a signal characteristic exceeding a predetermined threshold, where n is a positive integer greater than 1.
Dependencies are inferred from the claim text.