Measuring the Correlation of Personal Identity Documents in Structured Format
This addresses the need for automated validation of identity documents for authorities, but it appears incremental as it applies existing methods to new data in the digital document domain.
The paper tackles the problem of manually cross-checking personal identity documents by proposing a technique to extract identity data from structured formats and calculate a normalized correlation score, with experimental results showing it effectively computes this score.
Personal identity documents play a major role in every citizen's life and the authorities responsible for validating them typically require human intervention to manually cross-check multiple documents belonging to an individual. The world is rapidly replacing physical documents with digital documents where every piece of data is stored digitally in a machine-readable and structured format. In this paper, we describe a technique to extract identity data from a structured data format and calculate a normalized correlation score for personal identity documents. Experimental results show that the proposed technique effectively calculates the correlation score for personal identity documents.