Abstract

In this paper we collect 1210 global features of dynamics signature. All features are collected from previous research and we also add global features from FRESH framework. The purpose is to select relevant features from those features set. For doing that, we compute the importance score of each features using two methods: Information Gain Ratio and Correlation. Then each features will be ranked based on its score. After that, we divide 1210 features into 10, 20, 30, and so on until all 1210 features set are used in ascending order of the rank. Then, each features set is validated with Random Forrest, SVM, and Naïve Bayes classifier using 10 folds cross validation. The experiment was conducted in SVC2004 dataset task 1. The result show that, 120 first features from correlation method is the most relevant features. And therefore, those 120 global features is a good candidate for dynamic signature verification and will be used for the next research using dataset collected from mobile device.

Original languageEnglish
Title of host publication2018 International Conference on Information and Communications Technology, ICOIACT 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages348-354
Number of pages7
ISBN (Electronic)9781538609545
DOIs
Publication statusPublished - 26 Apr 2018
Event1st International Conference on Information and Communications Technology, ICOIACT 2018 - Yogyakarta, Indonesia
Duration: 6 Mar 20187 Mar 2018

Publication series

Name2018 International Conference on Information and Communications Technology, ICOIACT 2018
Volume2018-January

Conference

Conference1st International Conference on Information and Communications Technology, ICOIACT 2018
Country/TerritoryIndonesia
CityYogyakarta
Period6/03/187/03/18

Keywords

  • Correlation
  • Dynamic Signature
  • Features Selection
  • Global Features
  • Information Gain Ratio

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