Databases, data structures, and data processing systems for counterfeit physical document detection

A data processing system for counterfeit document detection, the data processing system comprising:

• one or more processors;
• and
• one or more storage devices, wherein the one or more storage devices includes instructions that, when executed by the one or more processors, cause the one or more processors to perform operations, the operations comprising:
• obtaining an image;
• providing the image as an input to a machine learning model that has been trained to determine whether data representing the image deviates from an anticounterfeiting architecture, wherein the anticounterfeiting architecture includes two or more security features, wherein the two or more security features includes two or more of (i) presence of a predetermined facial aspect ratio, (ii) presence of a predetermined head orientation, (iii) presence of a drop shadow, (iv) presence of guilloche lines over a facial image, or (v) presence of a predetermined graphic;
• generating output data based on the machine learning model processing the obtained image;
• determining, based on the generated output data, that the image does not adhere to the anticounterfeiting architecture, and;
• in response to determining that the image does not adhere to the anticounterfeiting architecture, generating an alert at a display of a computing device.

A method for counterfeit document detection, the method comprising:

• obtaining an image;
• providing the image as an input to a machine learning model that has been trained to determine whether data representing the image deviates from an anticounterfeiting architecture, wherein the anticounterfeiting architecture includes two or more security features, wherein the two or more security features includes two or more of (i) presence of a predetermined facial aspect ratio, (ii) presence of a predetermined head orientation, (iii) presence of a drop shadow, (iv) presence of guilloche lines over a facial image, or (v) presence of a predetermined graphic;
• generating output data based on the machine learning model processing the obtained image;
• determining, based on the generated output data, that the image does not adhere to the anticounterfeiting architecture, and;
• in response to determining that the image does not adhere to the anticounterfeiting architecture, generating an alert at a display of a computing device.

A computer-readable storage device having stored thereon instructions, which, when executed by data processing apparatus, cause the data processing apparatus to perform operations comprising:

• obtaining an image;
• providing the image as an input to a machine learning model that has been trained to determine whether data representing the image deviates from an anticounterfeiting architecture, wherein the anticounterfeiting architecture includes two or more security features, wherein the two or more security features includes two or more of (i) presence of a predetermined facial aspect ratio, (ii) presence of a predetermined head orientation, (iii) presence of a drop shadow, (iv) presence of guilloche lines over a facial image, or (v) presence of a predetermined graphic;
• generating output data based on the machine learning model processing the obtained image;
• determining, based on the generated output data, that the image does not adhere to the anticounterfeiting architecture, and;
• in response to determining that the image does not adhere to the anticounterfeiting architecture, generating an alert at a display of a computing device.