Open AccessFace Detection Based On Eye-Mouth Triangular Approach
Author(s) -
Deni Kartika,
Suprijadi Suprijadi
Publication year - 2020
Publication title -
kontribusi fisika indonesia
Language(s) - English
Resource type - Journals
ISSN - 0854-6878
DOI - 10.5614/itb.ijp.2020.31.2.1
Subject(s) - artificial intelligence , computer vision , computer science , eigenface , face detection , face (sociological concept) , facial recognition system , three dimensional face recognition , principal component analysis , pattern recognition (psychology) , face hallucination , digital image , object class detection , image processing , image (mathematics) , social science , sociology
Human face is a complex and dynamic structure. It is a challenge to be able to make a face recognition system like humans. At the beginning of its development, many facial recognition studies only focused on facial features. In 1991, Turk and Pentland developed a face recognition system based on Principal Component Analysis named eigenface. This system is very efficient because it only focuses on components that most affect facial image. However, this system has weaknesses, which cannot be used to determine the position of the face. In this final project, image processing methods will be carried out to detect faces in digital images. The method used is eye mouth triangular approach with the steps being taken are skin detection, eye detection, mouth detection, and facial confirmation. From the results of a hundred digital color images tested, there were 82 images that were successfully detected. The main system failure is caused by failure in skin detection. Further development is needed so that the system can work optimally.