US 12,131,440 B2
Method and apparatus for generating training data of deep learning model for lane classification
S Vinuchackravarthy, Pyeongtaek-si (KR); Shubham Jain, Pyeongtaek-si (KR); Arpit Awasthi, Pyeongtaek-si (KR); and Jitesh Kumar Singh, Pyeongtaek-si (KR)
Assigned to HL Klemove Corp., Incheon (KR)
Filed by HL Klemove Corp., Incheon (KR)
Filed on Apr. 14, 2022, as Appl. No. 17/720,740.
Claims priority of application No. 10-2021-0049717 (KR), filed on Apr. 16, 2021.
Prior Publication US 2022/0335584 A1, Oct. 20, 2022
Int. Cl. G06T 5/50 (2006.01); G06N 3/08 (2023.01); G06T 3/40 (2006.01)
CPC G06T 5/50 (2013.01) [G06N 3/08 (2013.01); G06T 3/40 (2013.01); G06T 2207/10024 (2013.01); G06T 2207/20216 (2013.01); G06T 2207/30256 (2013.01)] 16 Claims
OG exemplary drawing
 
1. A method for generating training data of a deep learning model for lane classification by generating a composite image of the other color lane using images of a white lane and the other color lane, the method performed by an electronic apparatus or an in-vehicle system and comprising:
determining a ratio of other two channels based on one channel (reference color channel) for three color channels of red (R), green (G) and blue (B) of the other color lane in the image of the other color lane; and
generating a composite image of the other color lane by scaling the image of the white lane by applying the determined ratio to the other two channels with respect to the reference color channel of the white lane.