A novel method based on the cross-modality intersecting features of the palm-vein and the palmprint is proposed for identity verification.Capitalising on the unique geometrical relationship between the two biometric m...A novel method based on the cross-modality intersecting features of the palm-vein and the palmprint is proposed for identity verification.Capitalising on the unique geometrical relationship between the two biometric modalities,the cross-modality intersecting points provides a stable set of features for identity verification.To facilitate flexibility in template changes,a template transformation is proposed.While maintaining non-invertibility,the template transformation allows transformation sizes beyond that offered by the con-ventional means.Extensive experiments using three public palm databases are conducted to verify the effectiveness the proposed system for identity recognition.展开更多
In this paper,a novel cancellable biometrics technique calledMulti-Biometric-Feature-Hashing(MBFH)is proposed.The MBFH strategy is utilized to actualize a single direction(non-invertibility)biometric shape.MBFH is a t...In this paper,a novel cancellable biometrics technique calledMulti-Biometric-Feature-Hashing(MBFH)is proposed.The MBFH strategy is utilized to actualize a single direction(non-invertibility)biometric shape.MBFH is a typical model security conspire that is distinguished in the utilization of this protection insurance framework in numerous sorts of biometric feature strategies(retina,palm print,Hand Dorsum,fingerprint).A more robust and accurate multilingual biological structure in expressing human loneliness requires a different format to record clients with inseparable comparisons from individual biographical sources.This may raise worries about their utilization and security when these spread out designs are subverted as everybody is acknowledged for another biometric attribute.The proposed structure comprises of four sections:input multi-biometric acquisition,feature extraction,Multi-Exposure Fusion(MEF)and secure hashing calculation(SHA-3).Multimodal biometrics systems that are more powerful and precise in human-unmistakable evidence require various configurations to store a comparative customer that can be contrasted with biometric wellsprings of people.Disparate top words,biometrics graphs can’t be denied and change to another request for positive Identifications(IDs)while settling.Cancellable biometrics is may be the special procedure used to recognize this issue.展开更多
Cancelable biometrics are required in most remote access applications that need an authentication stage such as the cloud and Internet of Things(IoT)networks.The objective of using cancelable biometrics is to save the...Cancelable biometrics are required in most remote access applications that need an authentication stage such as the cloud and Internet of Things(IoT)networks.The objective of using cancelable biometrics is to save the original ones from hacking attempts.A generalized algorithm to generate cancelable templates that is applicable on both single and multiple biometrics is proposed in this paper to be considered for cloud and IoT applications.The original biometric is blurred with two co-prime operators.Hence,it can be recovered as the Greatest Common Divisor(GCD)between its two blurred versions.Minimal changes if induced in the biometric image prior to processing with co-prime operators prevents the recovery of the original biometric image through a GCD operation.Hence,the ability to change cancelable templates is guaranteed,since the owner of the biometric can pre-determine and manage the minimal change induced in the biometric image.Furthermore,we test the utility of the proposed algorithm in the single-and multi-biometric scenarios.The multi-biometric scenario depends on compressing face,fingerprint,iris,and palm print images,simultaneously,to generate the cancelable templates.Evaluation metrics such as Equal Error Rate(EER)and Area and Receiver Operator Characteristic curve(AROC)are considered.Simulation results on single-and multi-biometric scenarios show high AROC values up to 99.59%,and low EER values down to 0.04%.展开更多
结合指纹和声纹在识别环境中的优良互补性以及两种特征相关性不强的特点,提出一种基于指纹和声纹决策级融合识别方法。在对相应的指纹和声纹分别提取特征和识别之后,使用提出的二次比较选择模型(second comparison of choosing model,SC...结合指纹和声纹在识别环境中的优良互补性以及两种特征相关性不强的特点,提出一种基于指纹和声纹决策级融合识别方法。在对相应的指纹和声纹分别提取特征和识别之后,使用提出的二次比较选择模型(second comparison of choosing model,SCCM)在决策层上利用分数层数据信息进行辅助分类,根据类别判断是否启用声纹识别,使得双模态融合系统平均数据处理量降低了32.8%。基于FVC2002DB1指纹库和自采集声纹库进行了实验验证。实验结果显示,多模态融合可以有效解决单模态的识别限制,识别率相对单模态提升了将近5.08%和4.60%,且稳定性较高。展开更多
Biometrics was identified as one amongst 10 emerging technologies which would change the world in the twenty-first century. Components and processes of biometric system and the relevant technologies are explained in t...Biometrics was identified as one amongst 10 emerging technologies which would change the world in the twenty-first century. Components and processes of biometric system and the relevant technologies are explained in this article. Examples of biometric applications and trends of biometric research, together with industry development, are introduced, which illustrate the challenges and opportunities of this technology.展开更多
多生物特征融合考虑了个体的多种生理或行为特征,因而能显著地改善系统的识别性能,成为生物特征识别技术未来发展趋势之一。利用训练样本的识别率和误识率,提出了基于证据理论的多生物特征融合识别方法;对各识别专家的识别率和误识率进...多生物特征融合考虑了个体的多种生理或行为特征,因而能显著地改善系统的识别性能,成为生物特征识别技术未来发展趋势之一。利用训练样本的识别率和误识率,提出了基于证据理论的多生物特征融合识别方法;对各识别专家的识别率和误识率进行分析,提出了一种基于累积频率和证据理论(Cumulative Frequency based D-S,CFDS)的多生物特征融合方法;通过几个实验证明了改进的D-S算法的有效性,提高了合成结果的可靠性。展开更多
基金National Research Foundation of Korea funded by the Ministry of Education,Science and Technology,Grant/Award Number:NRF-2021R1A2C1093425。
文摘A novel method based on the cross-modality intersecting features of the palm-vein and the palmprint is proposed for identity verification.Capitalising on the unique geometrical relationship between the two biometric modalities,the cross-modality intersecting points provides a stable set of features for identity verification.To facilitate flexibility in template changes,a template transformation is proposed.While maintaining non-invertibility,the template transformation allows transformation sizes beyond that offered by the con-ventional means.Extensive experiments using three public palm databases are conducted to verify the effectiveness the proposed system for identity recognition.
基金supported by Taif University Researchers Supporting Project Number(TURSP-2020/215)Taif University,Taif,Saudi Arabia(www.tu.edu.sa).
文摘In this paper,a novel cancellable biometrics technique calledMulti-Biometric-Feature-Hashing(MBFH)is proposed.The MBFH strategy is utilized to actualize a single direction(non-invertibility)biometric shape.MBFH is a typical model security conspire that is distinguished in the utilization of this protection insurance framework in numerous sorts of biometric feature strategies(retina,palm print,Hand Dorsum,fingerprint).A more robust and accurate multilingual biological structure in expressing human loneliness requires a different format to record clients with inseparable comparisons from individual biographical sources.This may raise worries about their utilization and security when these spread out designs are subverted as everybody is acknowledged for another biometric attribute.The proposed structure comprises of four sections:input multi-biometric acquisition,feature extraction,Multi-Exposure Fusion(MEF)and secure hashing calculation(SHA-3).Multimodal biometrics systems that are more powerful and precise in human-unmistakable evidence require various configurations to store a comparative customer that can be contrasted with biometric wellsprings of people.Disparate top words,biometrics graphs can’t be denied and change to another request for positive Identifications(IDs)while settling.Cancellable biometrics is may be the special procedure used to recognize this issue.
基金This research was funded by the Deanship of Scientific Research at Princess Nourah Bint Abdulrahman University through the Fast-track Research Funding Program to support publication in the top journal(Grant No.42-FTTJ-13).
文摘Cancelable biometrics are required in most remote access applications that need an authentication stage such as the cloud and Internet of Things(IoT)networks.The objective of using cancelable biometrics is to save the original ones from hacking attempts.A generalized algorithm to generate cancelable templates that is applicable on both single and multiple biometrics is proposed in this paper to be considered for cloud and IoT applications.The original biometric is blurred with two co-prime operators.Hence,it can be recovered as the Greatest Common Divisor(GCD)between its two blurred versions.Minimal changes if induced in the biometric image prior to processing with co-prime operators prevents the recovery of the original biometric image through a GCD operation.Hence,the ability to change cancelable templates is guaranteed,since the owner of the biometric can pre-determine and manage the minimal change induced in the biometric image.Furthermore,we test the utility of the proposed algorithm in the single-and multi-biometric scenarios.The multi-biometric scenario depends on compressing face,fingerprint,iris,and palm print images,simultaneously,to generate the cancelable templates.Evaluation metrics such as Equal Error Rate(EER)and Area and Receiver Operator Characteristic curve(AROC)are considered.Simulation results on single-and multi-biometric scenarios show high AROC values up to 99.59%,and low EER values down to 0.04%.
文摘结合指纹和声纹在识别环境中的优良互补性以及两种特征相关性不强的特点,提出一种基于指纹和声纹决策级融合识别方法。在对相应的指纹和声纹分别提取特征和识别之后,使用提出的二次比较选择模型(second comparison of choosing model,SCCM)在决策层上利用分数层数据信息进行辅助分类,根据类别判断是否启用声纹识别,使得双模态融合系统平均数据处理量降低了32.8%。基于FVC2002DB1指纹库和自采集声纹库进行了实验验证。实验结果显示,多模态融合可以有效解决单模态的识别限制,识别率相对单模态提升了将近5.08%和4.60%,且稳定性较高。
文摘Biometrics was identified as one amongst 10 emerging technologies which would change the world in the twenty-first century. Components and processes of biometric system and the relevant technologies are explained in this article. Examples of biometric applications and trends of biometric research, together with industry development, are introduced, which illustrate the challenges and opportunities of this technology.
文摘多生物特征融合考虑了个体的多种生理或行为特征,因而能显著地改善系统的识别性能,成为生物特征识别技术未来发展趋势之一。利用训练样本的识别率和误识率,提出了基于证据理论的多生物特征融合识别方法;对各识别专家的识别率和误识率进行分析,提出了一种基于累积频率和证据理论(Cumulative Frequency based D-S,CFDS)的多生物特征融合方法;通过几个实验证明了改进的D-S算法的有效性,提高了合成结果的可靠性。
