PENERAPAN METODE PCA(PRINCIPAL COMPONENT ANALYSIS) DAN EUCLIDEAN DISTANCE UNTUK PENGENALAN WAJAH BERKELOMPOK

AZMI, MOH and Fachrurrozi, M. and Kanda Januar, Miraswan (2020) PENERAPAN METODE PCA(PRINCIPAL COMPONENT ANALYSIS) DAN EUCLIDEAN DISTANCE UNTUK PENGENALAN WAJAH BERKELOMPOK. Undergraduate thesis, Sriwijaya University.

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Abstract

The face is a unique part that every human individual has. For that face can be a reference to recognize someone. Maybe to recognize a person's face in small amounts can be said to be easy. However, it is difficult to recognize faces in large numbers and remember their names for a long time, given the limitations of each individual human being. The purpose of this study is to develop a group face recognition software. In this study group face recognition software uses the PCA method to extract features in face images and the Euclidean Distance method is used to measure the degree of similarity between two objects. The data used in this study amounted to 100 images, which are divided into 90 single face images as training data and 10 group face images as test data. The failure rate to slanted face of 8%. Group face recognition software using PCA and Euclidean Distance methods obtained an Accuracy result of 80%, a Precision of 100% and a Recall of 80%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Face Recognition, Image Processing, PCA, Euclidean Distance
Subjects:	Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation. T Technology > T Technology (General) > T58.4 Managerial control systems Information technology. Information systems (General)
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Users 8046 not found.
Date Deposited:	18 Sep 2020 03:58
Last Modified:	18 Sep 2020 03:58
URI:	http://repository.unsri.ac.id/id/eprint/35319

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