International Journal of Industrial Engineering & Production Research
Iran University of Science & Technology
Wed, Sep 18, 2024
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Volume 33, Issue 1 (IJIEPR 2022)
IJIEPR 2022, 33(1): 150-161 |
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ALLAM F Z, HAMAMI-MITICHE L, BOUSBIA-SALAH H. Evaluation and Comparison of the Performance of Biometric Recognition. IJIEPR 2022; 33 (1) :150-161
URL: http://ijiepr.iust.ac.ir/article-1-1385-en.html
URL: http://ijiepr.iust.ac.ir/article-1-1385-en.html
1- Assistant Professor at ICT Research Laboratory, National Institute of Post and ICT (INPTIC)Researcher at Laboratory of Signal and Communication Laboratory, Department of Electronics, National Polytechnic School (ENP)
2- Professor, Signal and Communication Laboratory, Department of Electronics, National Polytechnic School
3- Professor, Signal and Communication Laboratory, Department of Electronics, National Polytechnic School ,hicham.bousbia-salah@g.enp.edu.dz
2- Professor, Signal and Communication Laboratory, Department of Electronics, National Polytechnic School
3- Professor, Signal and Communication Laboratory, Department of Electronics, National Polytechnic School ,
Abstract: (1946 Views)
For several years, considerable efforts have been made in the field of biometric research. The major interest of this line of research is linked, among other things, to the recognition of the individual because the security needs are becoming increasingly important, and the economic stakes are colossal. There are many and diverse biometric applications that provide a substantial level of security.
Unimodal biometric systems allow a person to be recognized using a single biometric modality, but cannot guarantee correct identification with certainty. While multimodal biometric systems, using several biometric modalities, guarantee better recognition.
In this article, we are interested in the study of evaluation tools for biometric systems. For this, we will first calculate three essential parameters, namely: False Rejection Rate (FRR), False Acceptance Rate (FAR) and Equal Error Rate (EER). Second, we will determine the performance curves, in this case, the ROC curve (Receiver Operating Characteristic) and the DET curve (Detection Error Tradeoff). The calculation of these metrics allows the evaluation of unimodal and bimodal biometric systems to compare the benefit of merging the biometric modalities.
Unimodal biometric systems allow a person to be recognized using a single biometric modality, but cannot guarantee correct identification with certainty. While multimodal biometric systems, using several biometric modalities, guarantee better recognition.
In this article, we are interested in the study of evaluation tools for biometric systems. For this, we will first calculate three essential parameters, namely: False Rejection Rate (FRR), False Acceptance Rate (FAR) and Equal Error Rate (EER). Second, we will determine the performance curves, in this case, the ROC curve (Receiver Operating Characteristic) and the DET curve (Detection Error Tradeoff). The calculation of these metrics allows the evaluation of unimodal and bimodal biometric systems to compare the benefit of merging the biometric modalities.
Keywords: Unimodal and Bimodal Recognition Systems, Authentication Mode, ROC Curve, DET Curve, Unimodal and Bimodal Recognition Systems, Authentication Mode, Unimodal and Bimodal Recognition Systems, Authentication Mode, FRR, FER
Type of Study: Research |
Subject:
Systems Modeling and Simulation
Received: 2021/12/11 | Accepted: 2021/12/28 | Published: 2022/03/10
Received: 2021/12/11 | Accepted: 2021/12/28 | Published: 2022/03/10
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