An additively manufactured three-dimensional article includes layers successively built up from a metal powder by an additive manufacturing process by scanning a selected portion of the metal powder with electromagnetic radiation, and an anti-counterfeiting mark formed in at least one layer of the layers during the additive manufacturing process.

The invention relates to a security device and an authentication method, in which a security element (1) is provided. The security element comprises a support material (6), in which a three-dimensional pattern with structures (4) such as cracks, grooves, flaking, pits, scales, elevations, and/or shrinkages are embedded as static or dynamic security features. Additionally, a material, which is detectable by a scanning device, or a material composition is deposited or incorporated at least partly onto or into the three-dimensional pattern embedded in the support material (6) and is, if necessary, new applicable onto or removable from the security element, whereby the color, intensity, structure, layer thickness, individual pigments or another physical property of the support material (6) and/or the three-dimensional security element (1) pattern embedded into the support material is changed such that an at least partly altered appearance is produced which is detectable by the scanning device at authentication point of time and is storable in the storage device.

An anti-counterfeiting method involves dividing a barcode image into a plurality of modules; extracting a respective inertia of a gray level co-occurrence matrix for each of the plurality of modules; acquiring an image of a printed candidate bar code; generating a sorted list (using extracted intertias) for the plurality of modules of the image of the printed candidate barcode; in a first range of magnitudes, comparing the sorted list for the image of the printed genuine barcode with an equivalent sorted list for the image of the printed candidate barcode; and in a second range of magnitudes, comparing the sorted list for the image of the printed genuine barcode with the sorted list for the image of the printed candidate barcode, wherein the second range is different from the first range.

The present invention is a method for analyzing an imprint configured on a surface of an object at a source location and verifying at a destination location to determine the object's authenticity. The method includes capturing at least one image at a source location and examining and analyzing the captured image. The analysis is performed by dividing the captured image into multiple layers. For each layer area, size, threshold points, distance between threshold points and angle of lines are determined and then stored in the first database. Afterwards this data is encrypted by a source user and uploaded to a blockchain. When the object reaches the destination location the destination user performs the same operation of capturing, examining and analyzing by dividing the captured image into multiple layers in the same fashion as performed by the source user and then stored in a second database. The destination user also decrypts the encrypted data of the first database and compares the data of first database with the data of the second database. The results of the comparison help to determine an object's authenticity.

A method for determining whether a candidate barcode is genuine involves acquiring an image of an original barcode; determining, from the image of the original barcode, a deviation of a continuous edge of the original barcode from a nominal shape; encoding the deviation as signature data for the original barcode; storing the signature data for the original barcode on a storage device; acquiring an image of the candidate barcode; determining, from the image of the candidate barcode, a deviation of a continuous edge of the candidate barcode from the nominal shape; retrieving the signature data for the original barcode from the storage device; comparing the signature data for the original barcode with the signature data for the candidate barcode; and making a determination that the candidate barcode is genuine or not genuine based on a result of the comparison.

An individual identifier extraction device has: an acquisition part configured to acquire an image of a layer formed on an object, containing fine particles, and having an irregular planar shape; and an extraction part configured to extract a feature quantity dependent on the planar shape of the layer and the distribution of the particles as an individual identifier of the object from the image.

In one implementation, a processor: (1) receives an image of a candidate mark from an image acquisition device, (2) uses the image to measure one or more characteristics at a plurality of locations on the candidate mark, resulting in a first set of metrics, (3) removes, from the first set of metrics, a metric having a dominant amplitude, resulting in a trimmed first set of metrics, (4) retrieves, from a computer-readable memory, a second set of metrics that represents one or more characteristics measured at a plurality of locations on an original mark, (5) removes, from the second set of metrics, a metric corresponding to the metric removed from the first set of metrics, resulting in a trimmed second set of metrics, (6) compares the trimmed first set of metrics with the trimmed second set of metrics, and (7) determines whether the candidate mark is genuine based on the comparison.

Disclosed herein is an authenticating mark formed on the surface of a product or package. The said mark comprising: at least an overt portion of visible 3D random image in the form of physically unclonable function (PUF) characterized in that the said PUF is random cracks or colors. Additionally, phosphor particles might be added to this pattern as covert features. It further disclose a system and method for identifying genuine or counterfeited products by analyzing the image of a 3D-PUF and its encrypted image using a commonly held scanning device.

A method for determining whether a candidate barcode is genuine involves acquiring an image of an original barcode, wherein the original barcode includes a plurality of modules; determining, from the image of the original barcode, a deviation of a position of at least one of the plurality of modules of the original barcode from an idealized grid; encoding the deviation as signature data for the original barcode; storing the signature data for the original barcode on a storage device; acquiring an image of the candidate barcode, wherein the candidate barcode includes a plurality of modules; determining, from the image of the candidate barcode, a deviation of a position of at least one of the plurality of modules of the candidate barcode from the idealized grid; retrieving the signature data for the original barcode from the storage device; comparing the signature data for the original barcode with signature data for the candidate barcode; and making a determination that the candidate barcode is genuine or not genuine based on a result of the comparison.

An anti-counterfeiting method involves carrying out an image processing operation on an image of the printed genuine barcode including superimposing a best-fit grid on the image and extracting edge linearities of a plurality of modules of the image with respect to the best-fit grid; generating a list of the plurality of modules of the image of the printed genuine barcode (sorted based at least in part on the magnitudes of their respective extracted linearities); carrying out the image processing operation on an image of a printed candidate barcode; generating a list for the plurality of modules of the image of the printed candidate barcode (sorted based at least in part on the magnitudes of their respective extracted linearities); in first and second ranges of magnitudes, comparing the sorted list for the image of the printed genuine barcode with the sorted list for the image of the printed candidate barcode.