Partial Fingerprint on Combined Evaluation using Deep Learning and Feature Descriptor

Chrisantonius, Tri Kuntoro Priyambodo, Farchan Hakim Raswa, Jia Ching Wang

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

Abstract

Partial fingerprint recognition has become crucial to identifying a user's authenticity in mobile device transactions. As a result, developments are increasing for more effective and accurate identification and authentication of a user using a scanner that captures a small fingerprint image. However, there is a reduction in the number of features from a full fingerprint to a partial fingerprint image during partial to partial fingerprint matching. Therefore, we propose a method combining deep learning and feature descriptors for partial fingerprint recognition. The matching score is obtained by the weighted combination of the scores from deep learning and feature descriptors. Experiments have been carried out with data variations such as the image size, epoch numbers and dataset types. The proposed method of combining deep learning and feature descriptors in the matching score evaluation process has obtained good results for the FVC2002 DB1, DB2 and DB3 datasets.

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.
Pages1611-1614
Number of pages4
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

  • combined matching evaluation
  • convolutional neural network
  • deep learning
  • feature descriptor
  • partial fingerprint

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