PENGEKSTRAKSIAN FITUR PADA WAJAH MANUSIA DENGAN MENGGUNAKAN METODE EKSTRAKSI FITUR EIGENFACES

AZRIANSYAH, MUHAMMAD and Erwin, Erwin (2020) PENGEKSTRAKSIAN FITUR PADA WAJAH MANUSIA DENGAN MENGGUNAKAN METODE EKSTRAKSI FITUR EIGENFACES. Undergraduate thesis, Sriwijaya University.

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Abstract

The human face plays an important role in self-identification. Most computer programs for facial recognition are based on finding and measuring selected facial features which are then compared with the corresponding measurements of known faces. Feature extraction is the processing of a desired feature in an image that is detected and represented for advanced processing. It is the most critical step in most computer vision and image processing solutions because it marks the transition form of data representation from pictorial to nonpictorial. The use of eigenface provides an advantage in improving the face recognition process because it creates a pattern of faces from a collection of faces or against each of the existing faces, eigenface is able to reduce the dimensions of the input image and then project it on the subspace obtained during the training phase. The advantage of Eigenface is that it can reduce the size of the image because it removes information that is not needed to recognize faces by reducing each image to its middle value. In other words, the value of ordinary elements appearing in the matrix will be replaced by 0. So that the image carries distinguishing information between them. The Eigenface method is able to process hundreds of input images from a variety of people, here 20 objects that can be used for later classification here with the slope of the face looking forward, half-profile or half tilted and profile.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Ekstraksi Fitur Eigenfaces, Pengolahan Citra Digital
Subjects:	T Technology > TA Engineering (General). Civil engineering (General) > TA1501-1820 Applied optics. Photonics > TA1632.A48 Image processing.
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Users 7636 not found.
Date Deposited:	26 Aug 2020 07:13
Last Modified:	26 Aug 2020 07:13
URI:	http://repository.unsri.ac.id/id/eprint/33760

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