US 12,450,801 B2
Text recognition method and apparatus based on hand interaction for AR glasses
Jong-Bae Lee, Daejeon (KR); Jeung-Chul Park, Daejeon (KR); Wook-Ho Son, Daejeon (KR); Beom-Ryeol Lee, Daejeon (KR); and Yong-Ho Lee, Daejeon (KR)
Assigned to ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE, Daejeon (KR)
Filed by ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE, Daejeon (KR)
Filed on Sep. 13, 2023, as Appl. No. 18/367,702.
Claims priority of application No. 10-2023-0007158 (KR), filed on Jan. 18, 2023.
Prior Publication US 2024/0242407 A1, Jul. 18, 2024
Int. Cl. G06T 11/60 (2006.01); G06F 3/04883 (2022.01); G06T 5/50 (2006.01); G06T 5/70 (2024.01); G06T 7/73 (2017.01); G06V 10/77 (2022.01); G06V 10/774 (2022.01); G06V 20/20 (2022.01); G06V 30/16 (2022.01)
CPC G06T 11/60 (2013.01) [G06F 3/04883 (2013.01); G06T 5/50 (2013.01); G06T 5/70 (2024.01); G06T 7/73 (2017.01); G06V 10/7715 (2022.01); G06V 10/774 (2022.01); G06V 20/20 (2022.01); G06V 30/1613 (2022.01); G06T 2200/24 (2013.01); G06T 2207/10024 (2013.01)] 16 Claims
OG exemplary drawing
 
1. A text recognition method, comprising:
collecting RGB images;
extracting hand joint information from the RGB images;
generating a text image based on the hand joint information;
recognizing text from the text image:
outputting the recognized text,
wherein recognizing the text comprises:
preprocessing the text image; and
inferring the text by inputting the preprocessed text image to a first machine-learning model,
wherein preprocessing the text image comprises:
converting the text image into a grayscale image;
adjusting a resolution of the grayscale image;
normalizing the image of which the resolution is adjusted so that pixel values of the image are 0 to 1; and
converting the normalized image into a tensor.