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Wang R.,Autonomous University of Madrid | Ramos D.,Autonomous University of Madrid | Veldhuis R.,University of Twente | Fierrez J.,Autonomous University of Madrid | And 2 more authors.
IET Biometrics | Year: 2014

The spectral minutiae representation (SMC) has been recently proposed as a novel method to minutiae-based fingerprint recognition, which is invariant to minutiae translation and rotation and presents low computational complexity. As high-resolution palmprint recognition is also mainly based on minutiae sets, SMC has been applied to palmprints and used in full-to-full palmprint matching. However, the performance of that approach was still limited. As one of the main reasons for this is the much bigger size of a palmprint compared with a fingerprint, the authors propose a division of the palmprint into smaller regions. Then, to further improve the performance of spectral minutiae-based palmprint matching, in this work the authors present anatomically inspired regional fusion while using SMC for palmprints. Firstly, the authors consider three regions of the palm, namely interdigital, thenar and hypothenar, which have inspiration in anatomic cues. Then, the authors apply SMC to region-to-region palmprint comparison and study regional discriminability when using the method. After that, the authors implement regional fusion at score level by combining the scores of different regional comparisons in the palm with two fusion methods, that is, sum rule and logistic regression. The authors evaluate region-to-region comparison and regional fusion based on spectral minutiae matching on a public high-resolution palmprint database, THUPALMLAB. Both manual segmentation and automatic segmentation are performed to obtain the three palm regions for each palm. Essentially using the complex SMC, the authors obtain results on region-to-region comparison which show that the hypothenar and interdigital regions outperform the thenar region. More importantly, the authors achieve significant performance improvements by regional fusion using regions segmented both manually and automatically. One main advantage of the approach the authors took is that human examiners can segment the palm into the three regions without prior knowledge of the system, which makes the segmentation process easy to be incorporated in protocols such as in forensic science. © The Institution of Engineering and Technology 2014.

Wang R.,Autonomous University of Madrid | Veldhuis R.,University of Twente | Ramos D.,Autonomous University of Madrid | Spreeuwers L.,University of Twente | And 2 more authors.
2013 International Workshop on Biometrics and Forensics, IWBF 2013 | Year: 2013

The spectral minutiae representation has been proposed as a novel method to minutiae-based fingerprint recognition, which can handle minutiae translation and rotation and improve matching speed. As high-resolution palmprint recognition is also mainly based on minutiae sets, we apply spectral minutiae representation to palmprints and implement spectral minutiae based matching. We optimize key parameters for the method by experimental study on the characteristics of spectral minutiae using both fingerprints and palmprints. However, experimental results show that spectral minutiae representation has much worse performance for palmprints than that for fingerprints. EER 15.89% and 14.2% are achieved on the public high-resolution palmprint database THUPALMLAB using location-based spectral minutiae representation (SML) and the complex spectral minutiae representation (SMC) respectively while 5.1% and 3.05% on FVC2002 DB2A fingerprint database. Based on statistical analysis, we find the worse performance for palmprints mainly due to larger non-linear distortion and much larger number of minutiae. © 2013 IEEE.

Jagroep E.,University Utrecht | Van Der Werf J.M.E.M.,University Utrecht | Jansen S.,University Utrecht | Ferreira M.,Software Improvement Group B.V. | Visser J.,Software Improvement Group B.V.
Proceedings of the ACM Symposium on Applied Computing | Year: 2015

While energy is directly consumed by hardware, it is the software that provides the instructions to do so. Energy profilers provide a means to measure the energy consumption of software, enabling the user to take measures in making software more sustainable. Although each energy profiler has access to roughly the same data, the reported measurements can differ significantly between energy profilers. In this research, energy profilers are evaluated through a series of experiments on their functionality and the accuracy of the reported measurements. The results show that there is still work to be done before these software tools can be safely used for their intended purpose. As a start, a correction factor is suggested for the energy profilers. Copyright is held by the author(s).

Agency: Cordis | Branch: H2020 | Program: MSCA-ITN-EID | Phase: MSCA-ITN-2014-EID | Award Amount: 2.24M | Year: 2015

The growth of cloud computing is phenomenal, with vendors experiencing yearly growth over 90%. This reflects the rate at which organizations and individuals are leaving the comfort of tried and tested solutions to move into promising but uncharted territory. The aim of SENECA is no less than to address key issues in the software engineering of cloud-based systems, including a disciplined approach to their development and operation. The project partners have pooled their considerable knowledge and experience to identify areas where applied research, industrial tests, as well as graduate-level training can deliver the most promising results. The main challenge associated with cloud-based systems is their quality, as characterized (following ISO 25010) by their functional suitability, security, reliability, usability, performance efficiency, maintainability, and portability. Important quality issues include: How can the quality of a software-defined cloud infrastructure be measured and assured? How can the security of a cloud-based system be ensured, taking into account that it may be running on an un-trusted infrastructure? How can the energy-efficiency and CO2 footprints of cloud-based applications be optimized? SENECA addresses this challenge along the axes of A) cloud-based products and B) the cloud development process and tools. Research along axis A reaches from extending traditional quality assurance techniques to the cloud environment, to techniques for optimizing energy consumption by cloud systems without compromising performance or reliability. Research along axis B reaches from combining theory and practice to allow construction of secure systems on top of insecure cloud infrastructures, to improving testing practices for cloud development. Additionally SENECA pursues objectives to train recruited fellows on conducting industry-motivated research and to create joint supervision structures among industry and academia in the software engineering community.

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