An accurate multi-modal biometric identification system for person identification via fusion of face and finger print

Sidra Aleem, Po Yang, Saleha Masood, Ping Li, Bin Sheng

Research output: Journal article publicationJournal articleAcademic researchpeer-review

2 Citations (Scopus)

Abstract

Internet of things (IoT) have entirely revolutionized the industry. However, the cyber-security of IoT enabled cyber-physical systems is still one of the main challenges. The success of cyber-physical system is highly reliant on its capability to withstand cyberattacks. Biometric identification is the key factor responsible for the provision of secure cyber-physical system. The conventional unimodal biometric systems do not have the potential to provide the required level of security for cyber-physical system. The unimodal biometric systems are affected by a variety of issues like noisy sensor data, non-universality, susceptibility to forgery and lack of invariant representation. To overcome these issues and to provide higher-security enabled cyber-physical systems, the combination of different biometric modalities is required. To ensure a secure cyber-physical system, a novel multi-modal biometric system based on face and finger print is proposed in this work. Finger print matching is performed using alignment-based elastic algorithm. For the improved facial feature extraction, extended local binary patterns (ELBP) are used. For the effective dimensionality reduction of extracted ELBP feature space, local non-negative matrix factorization is used. Score level fusion is performed for the fusion. Experimental evaluation is done on FVC 2000 DB1, FVC 2000 DB2, ORL (AT&T) and YALE databases. The proposed method achieved a high recognition accuracy of 99.59%.

Original languageEnglish
Pages (from-to)1299-1317
Number of pages19
JournalWorld Wide Web
Volume23
Issue number2
DOIs
Publication statusPublished - 1 Mar 2020

Keywords

  • Cyber-physical systems
  • Extended local binary patterns
  • Face recognition
  • Finger print recognition
  • Local non-matrix factorization

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications

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