US 11,741,600 B2
Identifying follicular units
Santosh Sharad Katekari, Orlando, FL (US)
Filed by Santosh Sharad Katekari, Orlando, FL (US)
Filed on Apr. 21, 2021, as Appl. No. 17/237,014.
Prior Publication US 2022/0343493 A1, Oct. 27, 2022
Int. Cl. G06T 7/00 (2017.01); G02B 27/01 (2006.01); A61B 34/37 (2016.01); A61B 90/00 (2016.01)
CPC G06T 7/0012 (2013.01) [A61B 34/37 (2016.02); A61B 90/36 (2016.02); G02B 27/017 (2013.01); A61B 2090/365 (2016.02); G02B 2027/0178 (2013.01); G06T 2207/10028 (2013.01); G06T 2207/20021 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30004 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method comprising the steps of:
a) receiving a first image of a body surface having a plurality of hair follicles for harvesting;
b) classifying pixels of the image into hair pixels and non-hair pixels types, based on a partitioning of category values of said hair pixels from category values of said non-hair pixels, the category values being representative of statistical properties of the hair and non-hair pixels;
c) grouping, responsive to the classifying, a collection of proximal classified hair pixels together to form a cluster of hair pixels that is indicative of a follicular unit;
d) categorizing the follicular unit, responsive to the grouping and based on area parameters of pixels related to the cluster of hair pixels, into a type that is indicative of the number of hair follicles in the follicular unit.