A Fusion Methodology of AKAZE and Neural Network for Fingerprint Recognition

Farchan Hakim Raswa, Agus Harjoko, Chrisantonius, Jia Ching Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In recent years, biometric information has become essential to the maintenance of data confidentiality. In particular, fingerprints have become the most reliable biometrics system for individual human identification based on finger image characteristics. A good quality fingerprint should have at least 25 to 90 minutiae. An unclear image will result in poor recognition. In this work, we propose a novel methodology to improve fingerprint recognition. We represent the fingerprint feature using the AKAZE features. The KAZE features use nonlinear diffusion to perform local blurring on the image data while preserving the object boundaries and removing the noise. The heuristic method for calculating the matching rate is replaced with a neural network that distinguishes various data types with fewer rules. Experiments have been performed to validate the proposed method using an instance of the FVC2002 database. The proposed method has achieved adequate results for the biometric evaluation. The values of EER are less than 1.5%, with the highest success rate recorded in DB2 having an EER of 1.01%.

Original languageEnglish
Title of host publication2021 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2021 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1602-1606
Number of pages5
ISBN (Electronic)9789881476890
StatePublished - 2021
Event2021 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2021 - Tokyo, Japan
Duration: 14 Dec 202117 Dec 2021

Publication series

Name2021 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2021 - Proceedings

Conference

Conference2021 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2021
Country/TerritoryJapan
CityTokyo
Period14/12/2117/12/21

Keywords

  • AKAZE feature
  • fingerprint recognition
  • neural network

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