Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/116098
Title: Signature down-sampling for finger input online signature verification
Authors: Saleem, Mohammad
Kovari, Bence
UNESCO Clasification: 5701 Lingüística aplicada
110501 Método Científico
Keywords: Online signature verification
Sampling frequency
Classification
Issue Date: 2022
Conference: 20th Conference of the International Graphonomics Society (IGS 2021) 
Abstract: Online signatures are widely accepted and used for authentication purposes. They are acquired using special devices with different sampling frequencies. A stylus or finger can be used as an input method. This paper studied the minimum sampling frequency required to achieve the best accuracy in online signature verification systems. Three different dynamic time warping-based verifiers were applied on the finger input signatures set of the DeepSignDB database. The results show that we can achieve a highly accurate online signature verification system for finger input signatures using lower sampling frequency, reducing time and computation costs.
URI: http://hdl.handle.net/10553/116098
Source: The 20th Conference of the International Graphonomics Society (IGS2021). Conference proceedings for short papers not published in the LNCS – Springer
Appears in Collections:Actas de congresos
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