Online Signature Recognition

TOKER K. G., KÜÇÜK S., Catalbas M. C.

22nd IEEE Signal Processing and Communications Applications Conference (SIU), Trabzon, Turkey, 23 - 25 April 2014, pp.1754-1757 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • Doi Number: 10.1109/siu.2014.6830589
  • City: Trabzon
  • Country: Turkey
  • Page Numbers: pp.1754-1757
  • Hacettepe University Affiliated: Yes

Abstract

In this paper, online signature recognition is examined by using K Nearest Neighborhood (KNN) method. The signatures are collected by an Android application which can extract the dynamic and spatial information of the signatures. In this frame, a signature database is consisting of a total of 120 signatures taken from 12 different person. The purpose of this paper, is to obtain high performance with a few training signatures. Also, the performance of signature recognition is investigated by different distance measurement methods in K Nearest Neighborhood.