Digimarc Corporation

The present disclosure relates generally to signal encoding for printed objects such as product packaging, labels and hangtags. One implementation obtains a color image representing CMY color channels, and alters the color image to include an encoded signal by altering values representing CIELAB a* and b*, all the while keeping L* on or within a predetermined tolerance of a contour representing a constant value. Other implementations are provided.

An image processing method determines a geometric transform of a suspect image by efficiently evaluating a large number of geometric transform candidates in environments with limited processing resources. Processing resources are conserved by using complementary methods for determining a geometric transform of an embedded signal. One method excels at higher geometric distortion, and specifically, distortion caused by greater tilt angle of a camera. Another method excels at lower geometric distortion, for weaker signals. Together, the methods provide a more reliable detector of an embedded data signal in image across a larger range of distortion while making efficient use of limited processing resources in mobile devices.

The disclosure relates to image processing and embedding machine-readable codes into image data. One combination estimates embedded signal strength from embedded image data transformed according to anticipated color space, printer data and/or substrate data. Other combinations are also provided.

This disclosure relates to advanced image signal processing technology including encoded signals and digital watermarking. The technology may be applied to retail packages and other printed objects, e.g., such as hang tags, labels and receipts.

Differential modulation schemes encode a data channel within host signal or noisy environment in a manner that is robust, flexible to achieve perceptual quality constraints, and provides improved data capacity. Differential arrangements enable a decoder to suppress host signal or other background signal interference when detecting, synchronizing and extracting an encoded data channel. They also enable the incorporation of implicit or explicit synchronization components, which are either formed from the data signal or are complementary to it.

Content is identified using watermarking and/or other content recognition combined with contextual metadata, which facilitates identification and correlation with other content and metadata when it is posted to a network.

Various image processing arrangements are detailed for detecting mis-marking of product packaging artwork with two conflicting steganographically-encoded product identifiers. Some embodiments concern detection in a pre-press or test-print quality assurance stage. Others concern detection post-press. All help serve to assure accurate product identification by point of sale scanners. A great number of other features and arrangements are also detailed.

Optical code signal components are generated and then transformed into signal bearing art that conveys machine readable data. The components of an optical code are optimized to achieve improved signal robustness, reliability, capacity and/or visual quality. An optimization program can determine spatial density, dot distance, dot size and signal component priority to optimize robustness. An optical code generator transforms tiles of an optical code or image embedded with the optical code into signal-bearing art using stipple, Voronoi, Delaunay or other graphic drawing methods so as to retain prioritized components of the optical code. The optical code is merged into a host image, such as imagery, text and graphics of a package or label, or it may be printed by itself, e.g., on an otherwise blank label or carton. A great number of other features and arrangements are also detailed.

Mobile phones and other portable devices are equipped with a variety of technologies by which existing functionality can be improved, and new functionality can be provided. Some aspects relate to visual search capabilities, and determining appropriate actions responsive to different image inputs. Others relate to processing of image data. Still others concern metadata generation, processing, and representation. Yet others concern user interface improvements. Other aspects relate to imaging architectures, in which a mobile phone's image sensor is one in a chain of stages that successively act on packetized instructions/data, to capture and later process imagery. Still other aspects relate to distribution of processing tasks between the mobile device and remote resources (“the cloud”). Elemental image processing (e.g., simple filtering and edge detection) can be performed on the mobile phone, while other operations can be referred out to remote service providers. The remote service providers can be selected using techniques such as reverse auctions, through which they compete for processing tasks. A great number of other features and arrangements are also detailed.

This disclosure relates to advanced signal processing technology including signal encoding. One combination includes an apparatus comprising: memory for storing image data, the image data comprising a plurality of color separations or channels, in which the image data comprises at least a first type of machine-readable symbology comprising a 1D barcode represented therein and a second type of machine-readable symbology comprising a first signal represented therein, in which the second type of machine-readable symbology comprises a different type of machine-readable symbology relative to the first type of machine-readable symbology, the 1D barcode comprising a first plural-bit code and the first signal comprising a second plural-bit code; a barcode reader configured to analyze the image data to decode the 1D barcode to obtain the first plural-bit code; a signal decoder configured to analyze one or more color separations or channels of the plurality of color separations or channels to decode the first signal to obtain the second plural-bit code; one or more processors configured to determine whether the second plural-bit code and the first plural-bit code conflict; and to identify a conflict based on a conflict determination. Of course, other features and combinations are described as well.