US 12,424,013 B2
Image enhancement in a genealogy system
Michael Benjamin Brodie, Highland, UT (US); Gopalkrishna Balkrishna Veni, Lehi, UT (US); Jack Reese, Lindon, UT (US); Azadeh Moghtaderi, Kentfield, CA (US); and Randon Morford, Saratoga Springs, UT (US)
Assigned to Ancestry.com Operations Inc., Lehi, UT (US)
Filed by Ancestry.com Operations Inc., Lehi, UT (US)
Filed on Nov. 10, 2022, as Appl. No. 17/985,070.
Claims priority of provisional application 63/278,004, filed on Nov. 10, 2021.
Claims priority of provisional application 63/308,579, filed on Feb. 10, 2022.
Prior Publication US 2023/0142630 A1, May 11, 2023
Int. Cl. G06T 5/00 (2024.01); G06T 5/50 (2006.01); G06V 10/26 (2022.01); G06V 30/148 (2022.01); G06V 30/414 (2022.01)
CPC G06V 30/414 (2022.01) [G06T 5/50 (2013.01); G06V 10/267 (2022.01); G06V 30/15 (2022.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method, comprising:
receiving, by a genealogy server, an image that is digitalized from a physical record, the image associated with a genealogy record or an individual profile of the genealogy server;
identifying a sub-region of the image as a target region for image enhancement;
classifying that the sub-region includes a type of image component;
enhancing the sub-region based on the classified type of the image component to generate an enhanced sub-region, enhancing the sub-region comprising restoring or colorizing the image component, wherein enhancing the sub-region is performed at least partially by a machine learning model and the machine learning model comprises a generative adversarial network that is trained using a plurality of image records stored in the genealogy server and faux-real images generated by randomly oversaturating real images; and
merging the enhanced sub-region with one or more other sub-regions or an original version of the image.