US 11,657,602 B2
Font identification from imagery
Sampo Juhani Kaasila, Portsmouth, NH (US); Jitendra Kumar Bansal, Rajasthan (IN); Anand Vijay, Bhopal (IN); Vishal Natani, Jaipur (IN); Chiranjeev Ghai, New Delhi (IN); Mayur G. Warialani, Gujarat (IN); and Prince Dhiman, Chandigarh (IN)
Assigned to Monotype Imaging Inc., Woburn, MA (US)
Filed by Monotype Imaging Inc., Woburn, MA (US)
Filed on Oct. 30, 2018, as Appl. No. 16/175,401.
Claims priority of provisional application 62/578,939, filed on Oct. 30, 2017.
Prior Publication US 2019/0130232 A1, May 2, 2019
Int. Cl. G06K 9/68 (2006.01); G06V 10/82 (2022.01); G06N 20/00 (2019.01); G06F 40/109 (2020.01); G06V 30/244 (2022.01); G06V 20/62 (2022.01); G06V 30/413 (2022.01); G06V 30/19 (2022.01)
CPC G06V 10/82 (2022.01) [G06F 40/109 (2020.01); G06N 20/00 (2019.01); G06V 20/62 (2022.01); G06V 30/19173 (2022.01); G06V 30/245 (2022.01); G06V 30/413 (2022.01)] 60 Claims
OG exemplary drawing
 
1. A computing device implemented method comprising:
receiving an image that includes textual content in at least one font; and
identifying the at least one font represented in the received image using a machine learning system, the machine learning system being trained using images representing a plurality of training fonts, wherein a portion of the training images includes synthetic text located in the foreground and being positioned over captured background imagery, and a portion of the training images is distorted when captured by at least one of image capture conditions and capture equipment, wherein the identified at least one font is represented by one element of a plurality of elements of a data vector provided by the machine learning system.