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Raghavendra R.,University of Mysore | Ashok R.,Channabasaveshwara Institute of Technology | Kumar G.H.,University of Mysore
Journal of Computer Science and Technology | Year: 2010

Multimodal biometric fusion is gaining more attention among researchers in recent days. As multimodal biometric system consolidates the information from multiple biometric sources, the effective fusion of information obtained at score level is a challenging task. In this paper, we propose a framework for optimal fusion of match scores based on Gaussian Mixture Model (GMM) and Monte Carlo sampling based hypothesis testing. The proposed fusion approach has the ability to handle: 1) small size of match scores as is more commonly encountered in biometric fusion, and 2) arbitrary distribution of match scores which is more pronounced when discrete scores and multimodal features are present. The proposed fusion scheme is compared with well established schemes such as Likelihood Ratio (LR) method and weighted SUM rule. Extensive experiments carried out on five different multimodal biometric databases indicate that the proposed fusion scheme achieves higher performance as compared with other contemporary state of art fusion techniques. © 2010 Springer Science+Business Media, LLC &Science Press, China. Source


Lakshmeesha T.R.,Bangalore University | Sateesh M.K.,Bangalore University | Prasad B.D.,BMS College of Engineering | Sharma S.C.,North Park University | And 3 more authors.
Crystal Growth and Design | Year: 2014

For the first time, different morphologies of zinc oxide (ZnO) superstructures are synthesized by a simple and environmental friendly route using Nerium oleander leaf extract as fuel. Powder X-ray diffraction, scanning electron microscopy, UV-visible spectroscopy, and photoluminescence studies are performed to ascertain the formation and characterization of ZnO. X-ray diffraction confirmed the crystalline nature of the compound with hexagonal Wurtzite structure. When the concentration of the leaf extract is varied, different morphologies are formed. ZnO are tested for antifungal using soybean seed-borne fungi by food-poison method and antibacterial activity against bacterial human pathogens by a broth microplate dilution method using 96-well plates. Among the screened soybean seed-borne fungi, Fusarium equisiti was found to be more susceptible, which was followed by Macrophomina phaseolina for ZnO nanoparticles (NPs) prepared using 0.2188 mol/dm3 N. oleander leaf extract. It was observed that NPs exhibited pronounced antifungal activity in a dose-dependent manner with a relatively high percentage of mycelial inhibition. ZnO obtained with the concentration of 0.2188 mol/dm3 leaf extract showed both minimum inhibitory concentration and minimum bactericidal concentration effectiveness compared to other synthesized compounds. It is observed that the samples with small crystallite size show greater antibacterial activity than those of larger crystallite size. Further, we found that crystallite size and morphology significantly affects the antibacterial activity of ZnO. Prepared compounds showed significant inhibition against Escherichia coli, Staphylococcus aureus, Bacillus subtilis, and Pseudomonas aeurginosa. Among the tested bacteria, P. aeurginosa is more susceptible and E. coli is the least effective against bacterial pathogens. The antibacterial activities of the as-formed ZnO are preliminarily studied against Gram-positive (B. subtilis and S. aureus) and Gram-negative (E. coli and P. aeruginosa) bacteria and are found to be dependent on the shape of the nanostructures. © 2014 American Chemical Society. Source


Raghavendra R.,University of Mysore | Raghavendra R.,Orange S.A. | Dorizzi B.,Orange S.A. | Rao A.,Channabasaveshwara Institute of Technology | Hemantha Kumar G.,University of Mysore
Pattern Recognition | Year: 2011

In this paper, we address the problem of designing efficient fusion schemes of complementary biometric modalities such as face and palmprint, which are effectively coded using Log-Gabor transformations, resulting in high dimensional feature spaces. We propose different fusion schemes at match score level and feature level, which we compare on a database of 250 virtual people built from the face FRGC and the palmprint PolyU databases. Moreover, in order to reduce the complexity of the fusion scheme, we implement a particle swarm optimization (PSO) procedure which allows the number of features (identifying a dominant subspace of the large dimension feature space) to be significantly reduced while keeping the same level of performance. Results in both closed identification and verification rates show a significant improvement of 6% in performance when performing feature fusion in Log-Gabor space over the more common optimized match score level fusion method. © 2010 Elsevier Ltd. All rights reserved. Source


Raghavendra R.,Institute Tlcom | Dorizzi B.,Institute Tlcom | Rao A.,Channabasaveshwara Institute of Technology | Hemantha Kumar G.,University of Mysore
Pattern Recognition | Year: 2011

This paper presents two novel image fusion schemes for combining visible and near infrared face images (NIR), aiming at improving the verification performance. Sub-band decomposition is first performed on the visible and NIR images separately. In both cases, we further employ particle swarm optimization (PSO) to find an optimal strategy for performing fusion of the visible and NIR sub-band coefficients. In the first scheme, PSO is used to calculate the optimum weights of a weighted linear combination of the coefficients. In the second scheme, PSO is used to select an optimal subset of features from visible and near infrared face images. To evaluate and compare the efficacy of the proposed schemes, we have performed extensive verification experiments on the IRVI database. This database was acquired in our laboratory using a new sensor that is capable of acquiring visible and near infrared face images simultaneously thereby avoiding the need for image calibration. The experiments show the strong superiority of our first scheme compared to NIR and score fusion performance, which already showed a good stability to illumination variations. © 2010 Elsevier Ltd. All rights reserved. Source


Kavyashree D.,Channabasaveshwara Institute of Technology | Kumari R.A.,Sree Siddaganga College for Women | Nagabhushana H.,Tumkur University | Sharma S.C.,Dr Hari Singh Gour University | And 6 more authors.
Journal of Luminescence | Year: 2015

Abstract Europium ions doped (1-11 mol%) ZnO nanoparticles (NPs) were synthesized by a facile green synthesis method using Guizotia abyssinica as fuel. The obtained ZnO:Eu3+ (1-11 mol%) NPs were characterized by using powder X-ray diffraction studies (PXRD), scanning electron microscopy (SEM) and photoluminescence (PL) techniques. The dependency of dopant concentration on the crystal structure, surface morphology and luminescence properties was discussed in detail. The particle size and the existing states of the ions within the material were analyzed by TEM and XPS respectively. The PL emission of ZnO:Eu3+ NPs shows characteristics transitions of Eu3+ ions. It has been demonstrated that intrinsic defects may act as the media in the energy transfer process from the ZnO host to Eu3+ ions. The CIE chromaticity and CCT confirms the phosphor material as orange red emitting hence it was quite useful in display applications. © 2015 Elsevier B.V. Source

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