Bulut Doğrulama Temelli Yüz Tanıma Tekniği

Yıl 2019, Cilt: 3 Sayı: 1, 79 - 96, 30.07.2019

Anfal Thaer Alrahlawee , Adil Deniz Duru , Oğuz Bayat Osman Nuri Uçan

Öz

Öz

Tek bir yüz için tanıma süreci nispeten daha kısa sürede tamamlanabilir. Bununla birlikte, birkaç yüzün

tanınmasını içeren büyük ölçekli uygulama, prosedürü uzun bir hale getirecektir. Bulut bilişim hizmeti, daha

fazla veri işleneceği zaman bulut bilişimin temel kaynakları artırdığı bir ölçeklenebilirlik çözümü sağlaması

için bu araştırmada kullanılmıştır. Geliştirilen sistemin programlanması ve eğitimi, bulut bilişim yoluyla yüzleri

tespit etmek ve tanımak için yapılmıştır. İntegral görüntü, basamaklı sınıflandırıcılar, beş çeşit Haar benzeri

özellikler ve Adaboost öğrenme yöntemi kullanılan yüzleri tespit etmek için Viola ve Jones algoritması kullanılır.

Yüz tanıma, Temel Bileşen Analizi (PCA) algoritmasına göre daha verimli olduğu için Doğrusal Diskriminant

Analizi (LDA) kullanılarak yapılmıştır. Sistemin performansını değerlendirmek için çeşitli MUCT veritabanı

görüntüleri kullanılmıştır.

Anahtar Kelimeler

Histogram eşitleme, Bulut bilgi işlem, Yüz algılama, Viola ve Jones algoritması, Doğrusal Diskriminant Analizi

Cloud Authentication Based Face Recognition Technique

Öz

Abstract

The recognition process for a single face can be completed in relatively less time. However, large scale

implementation that involves recognition of several faces would make the procedure a lengthy one. Cloud

computing service has been employed in this paper to provide a solution for scalability, where cloud computing

increases the essential resources when larger data is to be processed. The programming and training of the

developed system has been done in order to detect and recognize faces through cloud computing. Viola and

Jones algorithm is employed for detecting faces that used integral image, cascaded classifiers, five sorts of

Haar-like features, and Adaboost learning method. Face recognition has been done using Linear Discriminant

Analysis (LDA), as it is more efficient compared to Principal Component Analysis (PCA) algorithm. Several

MUCT database images have been used for assessing the performance of system.

Anahtar Kelimeler

Histogram equalization, Cloud computing, Face detection, Viola and Jones algorithm, Linear Discriminant Analysis

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