Fingernail analysis management system using microscopy sensor and blockchain technology

Shih Hsiung Lee, Chu-Sing Yang

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

In traditional Chinese medicine, the growth situation of the surface of nails reflects the physiological condition of the human body. Diagnosis by nail can effectively predict and prevent disease. Human nails have a high degree of uniqueness, and it can be used for biometric recognition. In this work, microscope sensor was used to capture the clear image and segment the lunula and nail plate effectively through image preprocessing. Fingernails’ image is managed as the identity authentication. Histogram of oriented gradients and local binary patterns are used to capture the characteristic value. It uses support vector machine and random forest tree for classification. The performance of each feature extraction algorithm was analyzed for the two classifiers and the deep neural network algorithm was used comparatively. Furthermore, the security and privacy of the Internet of Things is still a challenge. This work uses the highly anonymous blockchain technology to effectively protect data privacy and manage each user’s data through the blockchain, in which any change or manipulation can be recorded and tracked, and the data security is improved. Therefore, this article presents a nail analysis management system with the use of microscopy sensor and blockchain.

Original languageEnglish
JournalInternational Journal of Distributed Sensor Networks
Volume14
Issue number3
DOIs
Publication statusPublished - 2018 Mar 1

Fingerprint

Nails
Microscopic examination
Sensors
Data privacy
Biometrics
Security of data
Authentication
Medicine
Support vector machines
Feature extraction
Microscopes
Classifiers

All Science Journal Classification (ASJC) codes

  • Engineering(all)
  • Computer Networks and Communications

Cite this

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abstract = "In traditional Chinese medicine, the growth situation of the surface of nails reflects the physiological condition of the human body. Diagnosis by nail can effectively predict and prevent disease. Human nails have a high degree of uniqueness, and it can be used for biometric recognition. In this work, microscope sensor was used to capture the clear image and segment the lunula and nail plate effectively through image preprocessing. Fingernails’ image is managed as the identity authentication. Histogram of oriented gradients and local binary patterns are used to capture the characteristic value. It uses support vector machine and random forest tree for classification. The performance of each feature extraction algorithm was analyzed for the two classifiers and the deep neural network algorithm was used comparatively. Furthermore, the security and privacy of the Internet of Things is still a challenge. This work uses the highly anonymous blockchain technology to effectively protect data privacy and manage each user’s data through the blockchain, in which any change or manipulation can be recorded and tracked, and the data security is improved. Therefore, this article presents a nail analysis management system with the use of microscopy sensor and blockchain.",
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Fingernail analysis management system using microscopy sensor and blockchain technology. / Lee, Shih Hsiung; Yang, Chu-Sing.

In: International Journal of Distributed Sensor Networks, Vol. 14, No. 3, 01.03.2018.

Research output: Contribution to journalArticle

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