Feature Analysis of Blind and Visual Signature Data Collection Protocols based on the identification performance

Ibrahem R., ERBİLEK M.

9th International Conference on Computational Intelligence and Communication Networks (CICN), Girne, Kıbrıs (Kktc), 16 - 17 Eylül 2017, ss.127-130, (Tam Metin Bildiri) identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/cicn.2017.29
  • Basıldığı Şehir: Girne
  • Basıldığı Ülke: Kıbrıs (Kktc)
  • Sayfa Sayıları: ss.127-130
  • Orta Doğu Teknik Üniversitesi Kuzey Kıbrıs Kampüsü Adresli: Hayır

Özet

In this paper, we analyse the differences and similarities of features in the context of blind and visual signing data collection protocols with respect to the signature biometrics identification performance. As a result of this performed experimental analysis, powerful features which maximises system accuracy while minimising the performance differential across different signature data collection protocols (visual and blind signing) is extensively tested and documented.