Abstract:
Examples disclosed herein relate to determining peak distances between an origin, point in the frequency domain and peak points of a discrete Fourier transform magnitude of an image of a periodic or quasi-periodic target. In some implementations, a range distance between the target and the imaging lens is determined based on the peak distances.
Abstract:
An example method of recovering a planar projection in a captured image. The example method includes selecting displaced points in the captured image. The example method also includes recovering an affine transform of a quasi-periodic object for each of the displaced points based on peak locations of Discrete Fourier Transform (DFT) of the captured image. The example method also includes combining each of the affine transforms for the displaced points to recover the planar projection and correct for perspective distortion in the captured image.
Abstract:
A forensic verification system extracts a print signature via a print signature extractor from an interior of a halftone contained in an image. The system utilizes a comparator 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 utilizes a forensic analyzer to perform a forensic analysis on the signatures based on the comparison to authenticate the image.
Abstract:
An example method of rapid image registration includes recovering an affine transform of a quasi-periodic object based on peak locations of Discrete Fourier Transform (DFT) in a captured image. The example method also includes filtering a region of the captured image to match a filtered version of a reference image including the quasi periodic object. The example method also includes recovering translation parameters to reduce image differences between the reference image and the captured image for a subset of the image locations of the filtered image and outputting an approximate transform including translation.
Abstract:
A forensic verification system extracts a print signature via a print signature extractor from an interior of a halftone contained in an image. The system utilizes a comparator 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 utilizes a forensic analyzer to perform a forensic analysis on the signatures based on the comparison to authenticate the image.
Abstract:
In some examples, a method for recovering an alignment grid comprising multiple fiducial dots, the alignment grid for resolving multiple data dots, comprises determining a respective local structure within a local region around each fiducial dot and each data dot, and generating a connected subset of local structures to form a candidate alignment grid.
Abstract:
A method for recovering perspective distortion of a coded dot pattern on a surface, comprises generating a stereo-pair of images of a portion of the coded dot pattern, the stereo-pair of images comprising an overlap region comprising a subset of dots of the coded dot pattern that are common to the stereo-pair of images, selecting, in one image of the stereo-pair of images, a focus pattern from the subset of dots, determining a set of potential matches for the focus pattern in the other image of the stereo-pair of images, for each potential match, determining a set of additional dots of the coded dot pattern consistent with a single plane, and selecting a single plane with the highest number of consistent matched dots.
Abstract:
An example system includes a feature extraction engine. The feature extraction engine is to determine a plurality of scale-dependent features for a portion of a target. The system also includes a signature-generation engine to select a subset of the plurality of scale-dependent features based on a strength of each feature. The signature-generation engine also is to store a numeric representation of the portion of the target and the subset of the plurality of scale-dependent features.
Abstract:
Examples disclosed herein relate to determining image capture position information based on a quasi-periodic pattern. For example, a processor may determine whether a target area is within a captured image based on the detection of a quasi-periodic pattern in a first detection area and in a second detection area of the captured image.
Abstract:
A data-bearing medium is disclosed. The data-bearing medium includes a section of cells having a set of opposite-shifted clusters. The cells include a combination of opposite shifts of the set of opposite-shifted clusters, which represent a single value.