Aspects described herein may provide detection of a physical characteristic of a credential, thereby allowing for authentication of the credential. According to some aspects, these and other benefits may be achieved by detecting the physical characteristic with the credential. An image of a credential may be received. An optical characteristic of a secure feature of the credential may be determined. An expected optical characteristic of the secure feature may be determined based on known properties of the secure feature. A determination as to whether the credential is authentic may be based on a comparison of the determined optical characteristic of the secure feature to the expected optical characteristic of the secure feature.

A hologram detection method according to an aspect of the disclosure, includes: inputting a first image, obtained by capturing a detection object on the basis of first flash intensity, to a neural network model to obtain a first detection result value representing the detection or not of a hologram for each of predetermined at least one detection unit regions; and comparing a threshold value with the first detection result value obtained for each detection unit region to determine the detection or not of a hologram in the first image and a first detection unit region where a hologram is detected.

Machine-executable instructions arranged to be executed by a processor of an authenticating apparatus, and the instructions configured to read a machine-readable security feature provided on or which is part of the optical authentication structure, and to thereby cause a display of the apparatus to show at least part of the optical authentication structure and augmented reality imagery, which augmented reality imagery at least in part allows the optical authentication structure to be authenticated.

A hologram detection method according to an aspect of the disclosure, includes: inputting a first image, obtained by capturing a detection object on the basis of first flash intensity, to a neural network model to obtain a first detection result value representing the detection or not of a hologram for each of predetermined at least one detection unit regions; and comparing a threshold value with the first detection result value obtained for each detection unit region to determine the detection or not of a hologram in the first image and a first detection unit region where a hologram is detected.

Using software to process images and/or digital representations of paper currency to determine if currency has a value greater than the face value of the currency to any person or persons. Software that can determine from images and/or digital representations (known or unknown) numismatic value, or value greater than the face value of the currency to any person or persons and indicia of numismatic value, or increased value, including, but not limited to: ink smearing, misaligned serial numbers, misaligned seals on currency, non-matching serial numbers, off center printing, off-center cutting, paper currency of small or limited print runs, fancy serial numbers, missing or off-center watermarks, errors in security features, holograms, ultra-violet features, magnetic features, microprinting, etc. to determine a numismatic value.

A method for authenticating a security document by means of at least one device includes: a) providing the security document having at least one first security element and at least one second security element; b) providing the at least one device, wherein the at least one device includes at least one sensor; c) capturing first items of optical information of the at least one first security element by means of the at least one sensor of the at least one device during a first illumination, wherein at least one first dataset specifying these items of information is generated therefrom; d) capturing second items of optical information of the at least one second security element by means of the at least one sensor of the at least one device during a second illumination, wherein at least one second dataset specifying these items of information is generated therefrom; e) capturing third items of optical information of the at least one second security element by means of the at least one sensor of the at least one device during a third illumination, wherein at least one third dataset specifying these items of information is generated therefrom, wherein the second illumination differs from the third illumination; f) checking the genuineness of the security document and/or the second security element at least on the basis of the at least one second dataset and the at least one third dataset.

A hologram that includes a formation layer and a reflection layer that are laminated. The formation layer has an optical phase modulation structure on a first interface in contact with the reflection layer. When reference light emitted from a point light source enters through a second interface different from the first interface of the formation layer, the entirety or part of an image to be reconstructed by the optical phase modulation structure is reconstructed as spatial information on the point light source side relative to the second interface.

Embodiments relate to a non-fungible physical (NFP) item. The non-fungible physical (NFP) item comprises an identifier. The identifier is embedded and layered within the non-fungible physical item in an unplanned pattern. The identifier in the unplanned pattern is configured to provide high security against counterfeiting of the non-fungible physical (NFP) item. The identifier comprises at least one of a random marker and a unique marker. The unplanned pattern comprises at least one of a random pattern and a unique pattern. Further the non-fungible physical (NFP) item is registered as a non-fungible token on a blockchain. The NFP item is then paired with the non-fungible token for enabling two-way mutual authentication and enhanced authenticity. The pairing of the NFP item with the non-fungible token enables tracking condition, provenance, and grading of the NFP item.

A hologram detection method according to an aspect of the disclosure, includes: inputting a first image, obtained by capturing a detection object on the basis of first flash intensity, to a neural network model to obtain a first detection result value representing the detection or not of a hologram for each of predetermined at least one detection unit regions; and comparing a threshold value with the first detection result value obtained for each detection unit region to determine the detection or not of a hologram in the first image and a first detection unit region where a hologram is detected.

An identification device includes: an observation object shape frame display configured to display, on a display screen, an observation object shape image indicating a shape of an anti-counterfeit medium observed at an observation angle, and display image data that is an image of an imaging object of an image-capturing device, the anti-counterfeit medium being designed such that an observed pattern of light varies as the observation angle varies; a shape similarity calculator configured to calculate a shape similarity between the observation object shape image and an outer shape of the anti-counterfeit medium; and an imaging determinator configured to perform imaging determination as to whether the observation angle and an observation position of the image-capturing device are correct based on whether the shape similarity is equal to or greater than a shape similarity threshold.