US 11,995,906 B2
Techniques for generation of synthetic data with simulated handwriting
David Saul, Richmond, VA (US); Neeraj Sharma, Glen Allen, VA (US); Andrew Joyner, Henrico, VA (US); Kenneth B. Brewer, Vienna, VA (US); and Ratnakar Krishnama, Glen Allen, VA (US)
Assigned to Capital One Services, LLC, McLean, VA (US)
Filed by Capital One Services, LLC, McLean, VA (US)
Filed on Mar. 2, 2022, as Appl. No. 17/685,023.
Prior Publication US 2023/0282015 A1, Sep. 7, 2023
Int. Cl. G06V 30/19 (2022.01); G06T 3/60 (2006.01); G06T 11/40 (2006.01); G06V 30/32 (2022.01)
CPC G06V 30/19147 (2022.01) [G06T 3/60 (2013.01); G06T 11/40 (2013.01); G06V 30/32 (2022.01)] 20 Claims
OG exemplary drawing
 
1. An apparatus, the apparatus comprising:
a processor; and
memory comprising instructions that when executed by the processor cause the processor to:
identify a set of typefaces, each typeface in the set of typefaces comprising a collection of glyphs, and each glyph in the collection of glyphs stored in a vector graphics format with a set of vector attributes;
identify a set of randomization parameters, the set of randomization parameters comprising a plurality of randomization factors;
select a randomized typeface from the set of typefaces based on a first randomization factor of the plurality of randomization factors;
identify an input text comprising a first character;
determine an exchange glyph, from the collection of glyphs included in the randomized typeface, that corresponds to the first character of the input text;
generate a randomized set of vector attribute values for the exchange glyph based on the set of vector attributes corresponding to the exchange glyph and a second randomization factor of the plurality of randomization factors;
randomize the exchange glyph with the randomized set of vector attribute values to produce a randomized glyph;
generate simulated handwriting comprising the randomized glyph; and
utilize the simulated handwriting to train a computer vision process.