A Fusion Methodology of AKAZE and Neural Network for Fingerprint Recognition

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

研究成果: 書貢獻/報告類型會議論文篇章同行評審

摘要

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%.

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主出版物標題2021 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2021 - Proceedings
發行者Institute of Electrical and Electronics Engineers Inc.
頁面1602-1606
頁數5
ISBN(電子)9789881476890
出版狀態已出版 - 2021
事件2021 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2021 - Tokyo, Japan
持續時間: 14 12月 202117 12月 2021

出版系列

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

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???event.eventtypes.event.conference???2021 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2021
國家/地區Japan
城市Tokyo
期間14/12/2117/12/21

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