US 12,306,882 B2
Document matching using artificial intelligence
David A. Wyle, Corona Del Mar, CA (US); Alexander James Sadovsky, Denver, CO (US); and William W. Hosek, Laguna Niguel, CA (US)
Assigned to Sureprep, LLC, Irvine, CA (US)
Filed by Sureprep, LLC, Irvine, CA (US)
Filed on Nov. 10, 2023, as Appl. No. 18/506,695.
Application 18/506,695 is a continuation of application No. 17/217,917, filed on Mar. 30, 2021, granted, now 11,860,950.
Prior Publication US 2024/0086468 A1, Mar. 14, 2024
Int. Cl. G06F 16/93 (2019.01); G06N 3/08 (2023.01); G06V 30/412 (2022.01); G06V 30/416 (2022.01); G06V 30/418 (2022.01)
CPC G06F 16/93 (2019.01) [G06N 3/08 (2013.01); G06V 30/412 (2022.01); G06V 30/416 (2022.01); G06V 30/418 (2022.01)] 16 Claims
OG exemplary drawing
 
1. A method comprising:
storing, by a processor, cached metadata about a plurality of historical documents in a relational database to increase computation speed;
determining, by the processor, a mean square error (MSE) based on a difference between grayscale pixel intensities of each corresponding pixel of each image in a first content in one or more of a plurality of historical documents and a second content of a new document;
determining, by the processor, match metrics based on a percentage of the second content of the new document that matches the first content in one or more of the plurality of historical documents based on the cached metadata and;
extracting, by the processor, the second content from regions of interest in the new document based on the match metrics; and
automatically preparing, by the processor, documents using the second content.