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GENDER CLASSIFICATION FROM FACE IMAGES

Journal Name:

  • Journal of Naval Sciences And Engineering

Publication Year:

  • 2017

Key Words:

Keywords (Original Language):

Author NameUniversity of Author
Abstract (2. Language): 
In this article, we study on gender classification which is one of the important issue in security, statistics and related commercial areas. In the study, FEI face data set has been used that has 200 female and 200 male frontal face images. Principal component analysis (PCA) has been used for feature extraction process. We use all part of the face images instead of taking some part of them. Support Vector Machine (SVM) and k-nearest neighbor algorithms used for classification test phases. We compare the results which obtained in our experiments and give them in tables and graphs. According to the experiments, defined as hybrid method principal component analysis with k-nearest neighbor method gives better recognition accuracy then defined as hybrid method principal component analysis with support vector machine method.
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Abstract (Original Language): 
Bu makalede, günümüzde güvenlik, istatistik ve ilgili ticari alanlarda önemli yer tutan konulardan biri olan, yüz resimlerinden cinsiyet sınıflandırma üzerine bir araştırma yapılmıştır. Çalışmada, 200 bayan ve 200 bay olmak üzere 400 adet ön yüz resmi bulunan FEI yüz veri kümesi, resimlerden özellik çıkarımı için ise temel bileşen analizi (TBA) kullanılmıştır. Özellik (feature) çıkarımında yüzün belirli bölümleri yerine tamamı alınmıştır. Sınıflandırma ve test için destek vektör makineleri (DVM) ve en yakın k-en yakın komşu (k-nearest neighbor k-nn) algoritmaları kullanılmıştır. Deneysel çalışmalarda elde edilen sınıflandırma doğruluk oranları karşılaştırılmış ve sonuçlar analiz edilerek tablolar ve grafikler şeklinde sunulmuştur. Buna göre, elde edilen sonuçlara göre, temel bileşen analiziyle hibrit metot olarak kullanılan k-nn algoritmasının, destek vektör makineleri yöntemine göre cinsiyet sınıflandırmada daha iyi sonuçlar verdiği tespit edilmiştir.
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