Down syndrome recognition using local binary patterns and statistical evaluation of the system

Burcin K., Vasif N. V.

EXPERT SYSTEMS WITH APPLICATIONS, cilt.38, sa.7, ss.8690-8695, 2011 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 38 Sayı: 7
  • Basım Tarihi: 2011
  • Doi Numarası: 10.1016/j.eswa.2011.01.076
  • Dergi Adı: EXPERT SYSTEMS WITH APPLICATIONS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.8690-8695
  • Anahtar Kelimeler: Down syndrome recognition, Local binary pattern, Feature extraction, Classification, CLASSIFICATION
  • Karadeniz Teknik Üniversitesi Adresli: Evet

Özet

Down syndrome has a private facial view, thus it can be recognized by using facial features. But this is a very challenging problem when the similarity between the faces of people with Down syndrome and not Down syndrome people are considered. Therefore, we used the local binary pattern (LBP) approach for feature extraction which is a very effective feature descriptor. For classification Euclidean distance and Changed Manhattan distance methods are used. In this way, we improved an efficient system to recognize Down syndrome. (C) 2011 Elsevier Ltd. All rights reserved.