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Development and evaluation of an automated palpebral fissure length measurement method and implementation system
Author(s) -
Arisaka Naoya,
Mamorita Noritaka,
Inaoka Hidenori
Publication year - 2021
Publication title -
electronics and communications in japan
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.131
H-Index - 13
eISSN - 1942-9541
pISSN - 1942-9533
DOI - 10.1002/ecj.12316
Subject(s) - eyelid , calipers , palpebral fissure , computer science , margin (machine learning) , measure (data warehouse) , computer vision , artificial intelligence , mathematics , medicine , anatomy , ophthalmology , data mining , geometry , machine learning
Eyelid dysfunction results in symptoms of ptosis and eyelid retraction. Indicators of eyelid function include the corneal reflection distance at the eyelid margin and eyelid fissure (PF). There is currently no system in Japan that automatically measures the PF, which is a comprehensive measure of eyelid function. We devised a method to measure PF automatically from frontal images using ArUco markers and facial landmark estimation, and developed an implementation of the method using OpenCV and dlib. The system was shown to be significantly smaller than the digital calipers.