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PATTERN RECOGNITION FROM FACE IMAGES

Journal Name:

  • Journal of Naval Sciences And Engineering

Publication Year:

  • 2017

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Keywords (Original Language):

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Abstract (2. Language): 
In this article, we use projected gradient descent nonnegative matrix factorization (NMF-PGD) method and make pattern recognition analysis on ORL face data set. Face recognition is one of the critical issues in our life and some security, daily activities and operations use this well known application area. NMF-PGD is a type of nonnegative matrix factorization (NMF) which defined in the literature. In the study, derived NMF-PGD definition and algorithm has been used in order to classify the ORL face images. We give the experimental results in a table and graph. According to experiments, face recognition accuracy rates have different accuracy values because of the k - lower rank value. We change k-values between 25 and 144 to see the performance of NMF-PGD. At the end, we make some analysis and comments on the recognition rates. Additionally, NMF-PGD can also be used for different kind of pattern recognition problems.
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Abstract (Original Language): 
Bu makalede, iz düşüm eğimli azatlım negatif olmayan matris ayrıştırma (NMF-PGD) yöntemi kullanılmış ve ORL yüz veri kümesi üzerinde örüntü tanıma analizleri yapılmıştır. Yüz tanıma, güvenlik ve günlük aktivitelerde kullandığımız hayatımızdaki önemli ve iyi bilinen alanlardan bir tanesidir. NMF-PGD, literatürde tanımlanmış bir negatif olmayan matris ayrıştırma yöntemidir. Bu çalışmada, elde edilmiş NMF-PGD tanımı ve algoritması, ORL yüz veri imgelerini sınıflandırmak için kullanılmıştır. Deneysel analiz ve sonuçlar tablo ve grafik halinde sunulmuştur. Deneysel sonuçlara göre, yüz tanıma doğruluk oranları k-düşük rank değeri nedeniyle farklı değerlere sahip olmaktadır. k-düşük rank değerlerini 25 ve 144 arasında olacak şekilde değiştirip seçerek, NMF-PGD yönteminin performansını test ettik. Son kısımda, bu oranlar hakkında çeşitli analizler ve yorumlarda bulunduk. Ek olarak, NMF-PGD diğer çeşitli örüntü tanıma problemlerinde de kullanılabilir.
FULL TEXT (PDF): 
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  • Turkish

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