Skripsi

PENGENALAN CITRA WAJAH MENGGUNAKAN MINIMUM DISTANCE CLASSIFIER BERDASARKAN PRINCIPAL COMPONENT ANALYSIS

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Penilaian

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The combination of Principal Component Analysis (PCA) and Minimum Distance Classifier methods in face recognition can work well on more than one standard datasets. The addition of pre-processing stages in the form of image enhancement in this studyis very important in improving the quality of the input image so that it can provide better accuracy than previous studies without slowing down the system. However, to achieve this goal, it is necessary to conduct a literature study to understand the concepts and theoretical basis in order to strengthen the assumptions of image enhancement techniques, Principal Component Analysis as feature extraction method, and Minimum Distance Classifier as recognition method. Recognition result with ORL database get an accuracy of 97%, while recognition result with YALE database get an accuracy of 94.6%. So it can be concluded that the addition of image enhancement techniques in the combination of the Principal Component Analysis and Minimum Distance Classifier methods can provide a fast and simple solution by increasing or without reducing its standard accuracy.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2107004732	T57345	T573452021	Central Library (REFERENCES)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T573452021

Publisher

Inderalaya : Prodi Magister Ilmu Komputer, Fakultas Ilmu Komputer., 2021

Collation

xi, 57 hlm. : ilus. ; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

006.307

Content Type

Text

Media Type

unmediated

Carrier Type

-

Edition

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Subject(s)

Prodi Magister Ilmu Komputer
Kecerdasan Buatan-Minimum Distance Classifier

Specific Detail Info

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Statement of Responsibility

DS

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