COUNTRY OF ORIGIN ESTIMATION FROM COMPOSITE FACES USING KERNEL PRINCIPAL COMPENENT ANALYSIS

Catalbas M. C., YÜKSEKKAYA B.

22nd IEEE Signal Processing and Communications Applications Conference (SIU), Trabzon, Türkiye, 23 - 25 Nisan 2014, ss.1207-1210 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/siu.2014.6830452
  • Basıldığı Şehir: Trabzon
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.1207-1210
  • Anahtar Kelimeler: Composite faces, kernel principal compenent analysis, feature extraction, muli support vector machine, parallel analysis, z-score, local standart deviation
  • Ankara Üniversitesi Adresli: Hayır

Özet

In this work, an algorithm is introduced that classifies test images into their originated countries using composite faces generated according to different countries. Also aim to increase success rate at implementation process using three color channel (R-G-B), color feature vector and local standard deviation matrix. Algorithm used Kernel Principal Component Analysis with gauss kernel structure for dimension reduction process. And optimal component number for dimension reduction process is determined via Horn's parallel analysis method. At the end of process these obtained features are classified via Multi Support Vector Machines.