A system comprising: a document holder; an image sensor directed toward the document holder; a polarized filter between the image sensor and the document holder; a filter motor configured to rotate the polarized filter; one or more processors; and at least one memory having stored thereon computer program code that, when executed by the one or more processors, instructs the one or more processors to: control the filter motor to rotate the polarized filter; control the image sensors to capture a plurality of images of a document within the document holder, the plurality of images corresponding to a respective relative orientations of the polarized filter to the document; identify a feature of the document; and output, in response comparing respective visual characteristics of the feature of the document to corresponding expected visual characteristics of the first feature for the document, an indication of a verification of the document.

An identification device of the present invention determines authenticity of an article with an anti-counterfeiting medium varying in a pattern of observed light depending on changes in light characteristics of radiated light, using the anti-counterfeiting medium. The identification device includes a similarity calculation unit that determines the degrees of similarity between a plurality of captured image data of the anti-counterfeiting medium obtained with differences in the light characteristics of the radiated light and reference image data corresponding to the light characteristics; and an authenticity determination unit that determines whether the degrees of similarity determined for the individual light characteristics exceed thresholds set corresponding to the individual light characteristics to make an authenticity determination on whether the anti-counterfeiting medium is genuine.

An identification device of the present invention determines authenticity of an article with an anti-counterfeiting medium varying in a pattern of observed light depending on changes in light characteristics of radiated light, using the anti-counterfeiting medium. The identification device includes a similarity calculation unit that determines the degrees of similarity between a plurality of captured image data of the anti-counterfeiting medium obtained with differences in the light characteristics of the radiated light and reference image data corresponding to the light characteristics; and an authenticity determination unit that determines whether the degrees of similarity determined for the individual light characteristics exceed thresholds set corresponding to the individual light characteristics to make an authenticity determination on whether the anti-counterfeiting medium is genuine.

A method for detecting a document fraud is disclosed. A first image of a first document and a second image of a second document are obtained. A procedure of detection of zones sensitive to document frauds are applied in the regions of the first image and of the second image registered on the first image. Each sensitive zone detected is then divided into a plurality of subparts. A measurement of dissimilarity is calculated between corresponding subparts from the first image and the registered second image. It is then determined whether the first document is identical to the second document from measurements of dissimilarity. If the first document is different from the second document, a level of difference is determined between the first and second documents according to a value representing a proportion of different subparts; and a fraud is detected when the level of difference is below a third predetermined threshold.

A system for remote identification of users. The system uses deep learning techniques for authenticating a user from an identification document and using automated verification of identification documents. Identification documents may be authenticated by validating security features. The system may determine features expected in a valid identification document and determine whether those features are present, employing techniques, such as determining whether direction-sensitive features are present. Liveness of a user indicated by the identification document may be determined with a deep learning model trained for identification of facial spoofing attacks.

A system for remote identification of users. The system uses deep learning techniques for authenticating a user from an identification document, using automated verification of identification documents and detection that a live person identified by the document is present. Liveness of a user indicated by the identification document may be determined with a deep learning model trained for identification of facial spoofing attacks. The deep learning model may be trained using training data extracted from facial feature locations of training images.

A system comprising: a check Image Record (CIR) database configured to store, for each of a plurality of accounts, a CIR, wherein each CIR comprises feature information related to features extracted from a plurality of reference checks associated with the associated account of the plurality of accounts; memory configured to store instructions; and a processor coupled with the CIR database and the memory, the processor configured to run the instructions, which cause the processor to: receive an image of a test check associated with an account of the plurality of accounts, extract feature information from the image, compare the features with the feature information stored in the CIR database for the account associated with the test check, generate a fraud score, and update each CIR by determining.

A system comprising: a check Image Record (CIR) database configured to store, for each of a plurality of accounts, a CIR, wherein each CIR comprises feature information related to features extracted from a plurality of reference checks associated with the associated account of the plurality of accounts; memory configured to store instructions; and a processor coupled with the CIR database and the memory, the processor configured to run the instructions, which cause the processor to: receive an image of a test check associated with an account of the plurality of accounts, extract feature information from the image, compare the features with the feature information stored in the CIR database for the account associated with the test check, generate a fraud score, and update each CIR by determining.

Existing currency validation (CVAL) devices, systems, and methods are too slow, costly, intrusive, and/or bulky to be routinely used in common transaction locations (e.g., at checkout, at an automatic teller machine, etc.). Presented herein are devices, systems, and methods to facilitate optical validation of documents, merchandise, or currency at common transaction locations and to do so in an obtrusive and convenient way. More specifically, the present invention embraces a validation device that may be used alone or integrated within a larger system (e.g., point of sale system, kiosk, etc.). The present invention also embraces methods for currency validation using the validation device, as well as methods for improving the quality and consistency of data captured by the validation device for validation.

Existing currency validation (CVAL) devices, systems, and methods are too slow, costly, intrusive, and/or bulky to be routinely used in common transaction locations (e.g., at checkout, at an automatic teller machine, etc.). Presented herein are devices, systems, and methods to facilitate optical validation of documents, merchandise, or currency at common transaction locations and to do so in an obtrusive and convenient way. More specifically, the present invention embraces a validation device that may be used alone or integrated within a larger system (e.g., point of sale system, kiosk, etc.). The present invention also embraces methods for currency validation using the validation device, as well as methods for improving the quality and consistency of data captured by the validation device for validation.