Abstract:
A payload recovery system includes a reference halftone image of a data-bearing halftone image and a reference map of the data-bearing halftone image. The system further includes a cell alignment system for receiving a scanned image of a hard copy of the data-bearing halftone image and for generating an aligned scan of the scanned image using the reference halftone image and the reference map. A raw payload recovery system determines possible shift positions of each carrier cell of the aligned scan using a shift rule and the reference map; and a reconstructed data-bearing halftone image is generated by the raw payload recovery system using the possible shift positions and the reference halftone. The system also includes a recovered raw payload generated by the raw payload recovery system using the shift rule and the reference map.
Abstract:
Red-eye correction on a region of a digital image includes adjusting luminance of the region by generating a statistical measure of the luminance in the region, and computing an adjusted luminance based on the statistical measure according to a viewing condition.
Abstract:
A method and apparatus to select from an image (30) of a first sample (28), at least one region (44) digitally captured at a first resolution based upon how a counterfeit identification performance attribute of each region (44) digitally captured at the first resolution correlate to the counterfeit identification performance attribute of the region (44) digitally captured at a second resolution higher than the first resolution. The selected region (44) is used to determine whether the image (30) on a second sample is a counterfeit.
Abstract:
Methods, and apparatus for performing methods, for classifying an image. Methods include determining a corresponding set of metrics for each region of two or more regions of a pattern of regions of an image, and classifying the image in response to at least the corresponding set of metrics for each of the two or more regions of the pattern of regions.
Abstract:
A forensic verification system (700) extracts a print signature via print signature extractor 710 from the boundary of a halftone contained in an image. The system (700) compares the print signature to a reference signature stored in a registry via comparator 720 to determine differences between the print signature and the reference signature. The system 700 performs a forensic-level statistical image analysis via forensic analyzer 730 on the print signature and the reference signature based on the comparison to authenticate the printed media.
Abstract:
According to one example, there is provided a method of generating a security feature that encodes data. The method comprises obtaining an n-bit code of data to encode, generating an arrangement of dots, designating a first portion of the dots as reference dots and a second portion of the dots as encoding dots, and moving a group of the designated encoding dots by a predetermined direction in a predetermined amount to encode the n-bit code of data.
Abstract:
According to one example, there is provided a method of generating a security feature that encodes data. The method comprises obtaining an n-bit code of data to encode, generating an arrangement of dots, designating a first portion of the dots as reference dots and a second portion of the dots as encoding dots, and moving a group of the designated encoding dots by a predetermined direction in a predetermined amount to encode the n-bit code of data.
Abstract:
A forensic verification system (900) extracts a print signature via a print signature extractor (910) from a captured image of a printed halftone. The system (900) utilizes a comparator (920) to compare the print signature to a reference signature stored in a registry to determine differences between the print signature and the reference signature. The system (900) utilizes a forensic analyzer (930) to perform a forensic analysis on the signatures based on the comparison to authenticate the printed halftone.
Abstract:
An example provides a system and method of robust alignment and payload recovery for data-bearing images. The method includes digitizing a printed version of a stegatone, computing the transformation parameters of the stegatone, and processing individual local regions of the stegatone to determine local transformation parameters. The method also includes performing an alignment evaluation to compute a metric value that represents the quality of a local alignment between a reference halftone and the stegatone. Further, the method includes selecting alignment parameters based on optimization of the metric value, mapping the shift of clustered-dots in each cell in comparison to the reference halftone, and recovering the payload by decoding the stegatone.
Abstract:
A blur resistant barcode is disclosed. The blur resistant barcode comprise a plurality of parallel lines and spaces where information is encoded in the barcode by variations in the thicknesses of the plurality of parallel lines and by variations in the spacing between the plurality of parallel lines. The blur resistant barcode has at least one blur resistant feature that has a thickness in an axis of motion greater than a maximum thickness of any one of the plurality of parallel lines. The axis of motion is perpendicular to the plurality of parallel lines.