An alignment-free non-invertible transformation-based method for generating the cancellable fingerprint template

被引:0
作者
Diwakar Agarwal
Atul Bansal
机构
[1] GLA University,Electronics and Communication Engineering
[2] Chandigarh University,Electronics and Communication Engineering
来源
Pattern Analysis and Applications | 2022年 / 25卷
关键词
Cancellable; Fingerprint; Matching; Polar histogram; Template; Transformation;
D O I
暂无
中图分类号
学科分类号
摘要
Since long time fingerprint has been the most compelling biometric due to its permanence, universality, acceptability, and collectability. However, fingerprint recognition raises some privacy concerns. A stolen fingerprint template from the reference database could be used by an antagonist to gain a unauthorized access of the system. Therefore, the fingerprint needs to be secured from being compromised. In this paper, a non-invertible transformation function-based method for generating the cancellable fingerprint template is proposed. The transformation matrix is governed by the user key which is in the form of a randomly generated binary string. An alignment-free approach is proposed in which the fingerprint template is stored in the form of a polar histogram that contains the information about location of neighbouring minutiae around each detected minutia point. The matching score is obtained by computing the Chi-square distance between two templates. The pre-requisites for being the secured template are satisfied by conducting series of experiments on DB1 and DB2 datasets of FVC2000, FVC2002, FVC2004, and FVC2006 databases. The performance is evaluated in both non-transformed and transformed domains by computing error rates based on the receiver operating characteristic (ROC) of the fingerprint recognition system.
引用
收藏
页码:837 / 852
页数:15
相关论文
共 95 条
[1]  
Dargan S(2020)A comprehensive survey on the biometric recognition systems based on physiological and behavioral modalities Expert Syst Appl 143 1320-1329
[2]  
Kumar M(2020)Biometric recognition using fusion ICDSMLA 2019 5523-65
[3]  
Rane M(2020)Deep learning approach for multimodal biometric recognition system based on fusion of iris, face, and finger vein traits Sensors 20 54-3446
[4]  
Latne T(2015)Cancelable biometrics: a review IEEE Signal Process Mag 32 3403-1329
[5]  
Bhadade U(2020)Cancelable biometrics: a comprehensive survey Artif Intell Rev 53 141-147
[6]  
Alay N(2019)Security and accuracy of fingerprint-based biometrics: a review Symmetry 11 1321-139
[7]  
Al-Baity HH(2014)Design of alignment-free cancellable fingerprint templates via curtailed circular convolution Pattern Recogn 47 137-62
[8]  
Patel VM(2014)A non-invertible randomized graph-based hamming embedding for generating cancelable fingerprint template Pattern Recogn Lett 42 131-458
[9]  
Ratha NK(2016)Generating cancellable fingerprint templates based on Delaunay triangle feature set construction IET Biometrics 5 50-407
[10]  
Chellappa R(2016)Biometric cryptosystems: a new biometric key binding and its implementation for fingerprint minutiae-based representation Pattern Recogn 56 447-20