Managing Models Representing Different Expected Distortions Associated with a Plurality of Data Captures

Abstract

The present disclosure relates generally to managing models representing different expected distortions associated with a plurality of data captures. One claim recites a method comprising: obtaining a plurality of models each representing a different expected distortion associated with a plurality of data captures, the plurality of data captures each resulting in distortion of a machine-readable signal; indexing the plurality of models; upon receiving a request, selecting a model associated with the request; and providing the selected model. Of course, other methods and combinations are provided as well.

Description

RELATED APPLICATION DATA[0001]This application is a division of U.S. patent application Ser. No. 12 / 109,573, filed Apr. 25, 2008 (published as US 2008-0298632 A1), which claims the benefit of U.S. Patent Application No. 60 / 913,987, filed Apr. 25, 2007. Each of the above applications is hereby incorporated by reference in its entirety.TECHNICAL FIELD[0002]The present disclosure relates generally to data hiding and digital watermarking. In some implementations the present disclosure relates to correcting optical scan or other capture distortion, e.g., such as lens blurring, focus errors and other scanning anomalies. In other implementations the present disclosure relates to managing models representing different expected distortions associated with a plurality of data captures.BACKGROUND AND SUMMARY[0003]Digital watermarking—a form of steganography—is a process for modifying media content to embed a machine-readable code into the content. The content may be modified such that the embe...

AI Technical Summary

Benefits of technology

[0006]In some cases digital watermarking and other machine-readable indicia (e.g., barcodes, data glyphs, etc.) may be detected from optical scan data, examples of which are disclosed in, e.g., U.S. Pat. Nos. 5,978,773, 6,522,770, 6,681,028, 6,947,571 and 7,174,031, which are each hereby incorporated by reference. Today's camera phones and other handheld readers present expanded decoding opportunities—and challenges.

Problems solved by technology

One challenge is providing handheld cameras (e.g., in a cell phone or other mobile device) to an army of users, with nearly each user having a different idea on proper focal length for image and video capture.

In some cases a user may want to be close to a marked image or video to, e.g., capture high spatial frequency content (see FIG. 1); but the close positioning often results in a captured image that is slightly out of focus (or blurred)—which may hamper detection of a machine-readable code contained or represented in the image.

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