POLYBIO: Multimodal Biometric Data Acquisition Platform and Security System

Kounoudes, Anastasis; Tsapatsoulis, Nicolas; Θεοδοσίου, Ζήνωνας; Milis, Marios

doi:10.1007/978-3-540-89991-4_23

Cited by 6 publications

(4 citation statements)

References 15 publications

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“…The proposed procedure, other than providing results that are imperceptible to human visual system, it also outputs a stego-object that can resist different signal distortions. Experimental results on the database of POLY-BIO project [37], which contains more than 1500 biometric signals, illustrate the performance of the proposed system. Experiments have been designed to fulfill the requirements of three different scenarios.…”

Section: Discussionmentioning

confidence: 86%

“…For evaluation purposes, the proposed video-objects oriented biometric signals hiding scheme is examined in terms of security and efficiency. In particular, the database of the POLY-BIO project [37] was used, which contains more than 1500 biometric signals, 300 of which are fingerprints. The authentication setting, which focused on fingerprints, was simulation-based and included three different scenarios that are described in the following paragraphs.…”

Section: Resultsmentioning

confidence: 99%

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Video-Object Oriented Biometrics Hiding for User Authentication under Error-Prone Transmissions

Ntalianis

Tsapatsoulis

Drigas

2011

EURASIP Journal on Information Security

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An automatic video-object oriented steganographic system is proposed for biometrics authentication over error-prone networks. Initially, the host video object is automatically extracted through analysis of videoconference sequences. Next, the biometric pattern corresponding to the segmented video object is encrypted by a chaotic cipher module. Afterwards, the encrypted biometric signal is inserted to the most significant wavelet coefficients of the video object, using its qualified significant wavelet trees (QSWTs). QSWTs provide both invisibility and significant resistance against lossy transmission and compression, conditions that are typical in error prone networks. Finally, the inverse discrete wavelet transform (IDWT) is applied to provide the stego-object. Experimental results under various losses and JPEG compression ratios indicate the security, robustness, and efficiency of the proposed biometrics hiding system.

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Section: Discussionmentioning

confidence: 86%

Section: Resultsmentioning

confidence: 99%

Video-Object Oriented Biometrics Hiding for User Authentication under Error-Prone Transmissions

Ntalianis

Tsapatsoulis

Drigas

2011

EURASIP Journal on Information Security

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“…Overall, the results show that the proposed method can be improved upon and might be considered useful for high-security applications. Kounoudes et al (2008) designed a multimodal biometric system that combined voice, face, finger and palm features and compared the results with those of the unimodal biometrics of each of the traits. Biometric evidence was collected from 30 individuals using BOLYBIO datasets.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimized Negative Selection Algorithm for Image Classification in Multimodal Biometric System

Balogun¹,

Odeniyi²,

Omidiora³

et al. 2023

AIP

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Classification is a crucial stage in identification systems, most specifically in biometric identification systems. A weak and inaccurate classification system may produce false identity, which in turn impacts negatively on delicate decisions. Decision making in biometric systems is done at the classification stage. Due to the importance of this stage, many classifiers have been developed and modified by researchers. However, most of the existing classifiers are limited in accuracy due to false representation of image features, improper training of classifier models for newly emerging data (over-fitting or under-fitting problem) and lack of an efficient mode of generating model parameters (scalability problem). The Negative Selection Algorithm (NSA) is one of the major algorithms of the Artificial Immune System, inspired by the operation of the mammalian immune system for solving classification problems. However, it is still prone to the inability to consider the whole self-space during the detectors/features generation process. Hence, this work developed an Optimized Negative Selection Algorithm (ONSA) for image classification in biometric systems. The ONSA is characterized by the ability to consider whole feature spaces (feature selection balance), having good training capability and low scalability problems. The performance of the ONSA was compared with that of the standard NSA (SNSA), and it was discovered that the ONSA has greater recognition accuracy by producing 98.33% accuracy compared with that of the SNSA which is 96.33%. The ONSA produced TP and TN values of 146% and 149%, respectively, while the SNSA produced 143% and 146% for TP and TN, respectively. Also, the ONSA generated a lower FN and FP rate of 4.00% and 1.00%, respectively, compared to the SNSA, which generated FN and FP values of 7.00% and 4.00%, respectively. Therefore, it was discovered in this work that global feature selection improves recognition accuracy in biometric systems. The developed biometric system can be adapted by any organization that requires an ultra-secure identification system.

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“…Experimentation for the palm and fingerprint modalities is based on biometric templates constructed with the aid of MPEG-7 visual features [11] computed using the MPEG-7 experimentation software [19]. We have used the POLYBIO database [14] for our experiments. In this database there are four hand images per subject taken using low cost cameras as well as four fingerprint images per finger per subject taken using a light-reflection based fingerprint sensor.…”

Section: Experiments With Palm and Fingerprint Templatesmentioning

confidence: 99%

On the Quantification of Aging Effects on Biometric Features

Lanitis

Tsapatsoulis

2010

IFIP Advances in Information and Communication Technology

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Biometric templates are often used in intelligent human computer interaction systems that include automated access control and personalization of user interaction. The effectiveness of biometric systems is directly linked with aging that causes modifications on biometric features. For example the long term performance of person identification systems decreases as biometric templates derived from aged subjects may display substantial differences when compared to reference templates whereas in age estimation, aging variation allows the age of a subject to be estimated. In this paper we attempt to quantify the effects of aging for different biometric modalities facilitating in that way the design of systems that use biometric features. In this context the homogeneity of statistical distributions of biometric features belonging to certain age classes is quantified enabling in that way the definition of age sensitive and age invariant biometric features. Experimental results demonstrate the applicability of the method in quantifying aging effects.

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POLYBIO: Multimodal Biometric Data Acquisition Platform and Security System

Cited by 6 publications

References 15 publications

Video-Object Oriented Biometrics Hiding for User Authentication under Error-Prone Transmissions

Video-Object Oriented Biometrics Hiding for User Authentication under Error-Prone Transmissions

Optimized Negative Selection Algorithm for Image Classification in Multimodal Biometric System

On the Quantification of Aging Effects on Biometric Features

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