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title

Fraud detection in the fingerprint based on data mining combination techniques

Credit to Download: 1 | Page Numbers 7 | Abstract Views: 221
Year: 2018
COI code: IDS03_043
Paper Language: English

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Authors Fraud detection in the fingerprint based on data mining combination techniques

  Mansourehsadat Mousavi - Mousavi
  Hosein Jafarkarimi - Department of Computer ، Damavand Branch ،Islamic Azad University، Damavand ، Iran

Abstract:

In this paper, we make an effort to present a method based on Data Mining techniques to distinguish fake and live fingerprints in highly accurate authentication systems. In addition, the types of fraud material that are used in the manufacture of fingerprints was considered so that Based on the type of material, be assessed to discover knowledge about the sensitivity of the sensors based on materials. The material used in this study include gelatin, Eco-Flex, wood glue and latex. The reviewed steps in this research are as followed: First, in the feature extraction stage, we have used methods based on statistical formulae in image histogram. In the next step, the Hybrid algorithm based on support vector machine and decision tree were used. According to the results of this study, fake fingerprints which was made with gelatin, with the lowest errorand latex, with the maximum error was recognized.

Keywords:

Biometric, fingerprint, support vector machine, decision tree

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https://www.civilica.com/Paper-IDS03-IDS03_043.html
COI code: IDS03_043

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Mousavi, Mansourehsadat & Hosein Jafarkarimi, 2018, Fraud detection in the fingerprint based on data mining combination techniques, The Third International Conference on Intelligent Decision Science, تهران, انجمن سيستم هاي فازي ايران - دانشگاه آزاداسلامي واحد علوم تحقيقات, https://www.civilica.com/Paper-IDS03-IDS03_043.htmlInside the text, wherever referred to or an achievement of this article is mentioned, after mentioning the article, inside the parental, the following specifications are written.
First Time: (Mousavi, Mansourehsadat & Hosein Jafarkarimi, 2018)
Second and more: (Mousavi & Jafarkarimi, 2018)
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