A Prototype for a Multimodal Biometric Security system based on Face and Audio Signatures

Any automatically measurable, robust and distinctive physical characteristic or personal trait that can be used to identify an individual or verify the claimed identity of an individual, referred to as biometrics, has gained significant interest in the wake of heightened concerns about security and rapid advancements in networking, communication and mobility. Multimodal biometrics is expected to be ultra-secure and reliable, due to the presence of multiple and independent—verification clues. In this study, a multimodal biometric system utilising audio and facial signatures has been implemented and error analysis has been carried out. A total of one thousand face images and 250 sound tracks of 50 users are used for training the proposed system. To account for the attempts of the unregistered signatures data of 25 new users are tested. The short term spectral features were extracted from the sound data and Vector Quantization was done using K-means algorithm. Face images are identified based on Eigen face approach using Principal Component Analysis. The success rate of multimodal system using speech and face is higher when compared to individual unimodal recognition systems

Fluorescent Superparamagnetic Iron Oxide Core–Shell Nanoprobes for Multimodal Cellular Imaging

Multimodal imaging agents that combine magnetic and fluorescent imaging capabilities are desirable for the high spatial and temporal resolution. In the present work, we report the synthesis of multifunctional fluorescent ferrofluids using iron oxide as the magnetic core and rhodamine B as fluorochrome shell. The core–shell structure was designed in such a way that fluorescence quenching due to the inner magnetic core was minimized by an intermediate layer of silica. The intermediate passive layer of silica was realized by a novel method which involves the esterification reaction between the epoxy group of prehydrolysed 3-Glyidoxypropyltrimethoxysilane and the surfactant over iron oxide. The as-synthesized ferrofluids have a high saturation magnetization in the range of 62–65 emu/g and were found to emit light of wavelength 640 nm ( excitation = 446 nm). Time resolved life time decay analysis showed a bi-exponential decay pattern with an increase in the decay life time in the presence of intermediate silica layer. Cytotoxicity studies confirmed the cell viability of these materials. The in vitro MRI imaging illustrated a high contrast when these multimodal nano probes were employed and the R2 relaxivity of these ∗Author to whom correspondence should be addressed. Email: smissmis@gmail.com sample was found to be 334 mM−1s−1 which reveals its high potential as a T2 contrast enhancing agent

Improved Biometric Authentication System Using Multimodal Cue Integration

Biometrics is an efficient technology with great possibilities in the area of security system development for official and commercial applications. The biometrics has recently become a significant part of any efficient person authentication solution. The advantage of using biometric traits is that they cannot be stolen, shared or even forgotten. The thesis addresses one of the emerging topics in Authentication System, viz., the implementation of Improved Biometric Authentication System using Multimodal Cue Integration, as the operator assisted identification turns out to be tedious, laborious and time consuming. In order to derive the best performance for the authentication system, an appropriate feature selection criteria has been evolved. It has been seen that the selection of too many features lead to the deterioration in the authentication performance and efficiency. In the work reported in this thesis, various judiciously chosen components of the biometric traits and their feature vectors are used for realizing the newly proposed Biometric Authentication System using Multimodal Cue Integration. The feature vectors so generated from the noisy biometric traits is compared with the feature vectors available in the knowledge base and the most matching pattern is identified for the purpose of user authentication. In an attempt to improve the success rate of the Feature Vector based authentication system, the proposed system has been augmented with the user dependent weighted fusion technique.

Development of a Biometric Personal Authentication System Based on Fingerprint and Speech

Biometrics deals with the physiological and behavioral characteristics of an individual to establish identity. Fingerprint based authentication is the most advanced biometric authentication technology. The minutiae based fingerprint identification method offer reasonable identification rate. The feature minutiae map consists of about 70-100 minutia points and matching accuracy is dropping down while the size of database is growing up. Hence it is inevitable to make the size of the fingerprint feature code to be as smaller as possible so that identification may be much easier. In this research, a novel global singularity based fingerprint representation is proposed. Fingerprint baseline, which is the line between distal and intermediate phalangeal joint line in the fingerprint, is taken as the reference line. A polygon is formed with the singularities and the fingerprint baseline. The feature vectors are the polygonal angle, sides, area, type and the ridge counts in between the singularities. 100% recognition rate is achieved in this method. The method is compared with the conventional minutiae based recognition method in terms of computation time, receiver operator characteristics (ROC) and the feature vector length. Speech is a behavioural biometric modality and can be used for identification of a speaker. In this work, MFCC of text dependant speeches are computed and clustered using k-means algorithm. A backpropagation based Artificial Neural Network is trained to identify the clustered speech code. The performance of the neural network classifier is compared with the VQ based Euclidean minimum classifier. Biometric systems that use a single modality are usually affected by problems like noisy sensor data, non-universality and/or lack of distinctiveness of the biometric trait, unacceptable error rates, and spoof attacks. Multifinger feature level fusion based fingerprint recognition is developed and the performances are measured in terms of the ROC curve. Score level fusion of fingerprint and speech based recognition system is done and 100% accuracy is achieved for a considerable range of matching threshold

Multifinger Feature Level Fusion Based Fingerprint Identification

Fingerprint based authentication systems are one of the cost-effective biometric authentication techniques employed for personal identification. As the data base population increases, fast identification/recognition algorithms are required with high accuracy. Accuracy can be increased using multimodal evidences collected by multiple biometric traits. In this work, consecutive fingerprint images are taken, global singularities are located using directional field strength and their local orientation vector is formulated with respect to the base line of the finger. Feature level fusion is carried out and a 32 element feature template is obtained. A matching score is formulated for the identification and 100% accuracy was obtained for a database of 300 persons. The polygonal feature vector helps to reduce the size of the feature database from the present 70-100 minutiae features to just 32 features and also a lower matching threshold can be fixed compared to single finger based identification

β-glucosidases from Aspergillus unguis NII 08123: Molecular characterization, properties and applications

Lignocellulosic biomass is probably the best alternative resource for biofuel production and it is composed mainly of cellulose, hemicelluloses and lignin. Cellulose is the most abundant among the three and conversion of cellulose to glucose is catalyzed by the enzyme cellulase. Cellulases are groups of enzymes act synergistically upon cellulose to produce glucose and comprise of endoglucanase, cellobiohydrolase and β-glucosidase. β -glucosidase assumes great importance due to the fact that it is the rate limiting enzyme. Endoglucanases (EG) produces nicks in the cellulose polymer exposing reducing and non reducing ends, cellobiohydrolases (CBH) acts upon the reducing or non reducing ends to liberate cellobiose units, and β - glucosidases (BGL) cleaves the cellobiose to liberate glucose completing the hydrolysis. . β -glucosidases undergo feedback inhibition by their own product- β glucose, and cellobiose which is their substrate. Few filamentous fungi produce glucose tolerant β - glucosidases which can overcome this inhibition by tolerating the product concentration to a particular threshold. The present study had targeted a filamentous fungus producing glucose tolerant β - glucosidase which was identified by morphological as well as molecular method. The fungus showed 99% similarity to Aspergillus unguis strain which comes under the Aspergillus nidulans group where most of the glucose tolerant β -glucosidase belongs. The culture was designated the strain number NII 08123 and was deposited in the NII culture collection at CSIR-NIIST. β -glucosidase multiplicity is a common occurrence in fungal world and in A.unguis this was demonstrated using zymogram analysis. A total 5 extracellular isoforms were detected in fungus and the expression levels of these five isoforms varied based on the carbon source available in the medium. Three of these 5 isoforms were expressed in higher levels as identified by the increased fluorescence (due to larger amounts of MUG breakdown by enzyme action) and was speculated to contribute significantly to the total _- β glucosidase activity. These isoforms were named as BGL 1, BGL3 and BGL 5. Among the three, BGL5 was demonstrated to be the glucose tolerant β -glucosidase and this was a low molecular weight protein. Major fraction was a high molecular weight protein but with lesser tolerance to glucose. BGL 3 was between the two in both activity and glucose tolerance.121 Glucose tolerant .β -glucosidase was purified and characterized and kinetic analysis showed that the glucose inhibition constant (Ki) of the protein is 800mM and Km and Vmax of the enzyme was found to be 4.854 mM and 2.946 mol min-1mg protein-1respectively. The optimumtemperature was 60°C and pH 6.0. The molecular weight of the purified protein was ~10kDa in both SDS as well as Native PAGE indicating that the glucose tolerant BGL is a monomeric protein.The major β -glucosidase, BGL1 had a pH and temperature optima of 5.0 and 60 °C respectively. The apparent molecular weight of the Native protein is 240kDa. The Vmax and Km was 78.8 mol min-1mg protein-1 and 0.326mM respectively. Degenerate primers were designed for glycosyl hydrolase families 1, 3 and 5 and the BGL genes were amplified from genomic DNA of Aspergillus unguis. The sequence analyses performed on the amplicons results confirmed the presence of all the three genes. Amplicon with a size of ~500bp was sequenced and which matched to a GH1 –BGL from Aspergillus oryzae. GH3 degenerate primers producing amplicons were sequenced and the sequences matched to β - glucosidase of GH3 family from Aspergillus nidulans and Aspergillus acculateus. GH5 degenerate primers also gave amplification and sequencing results indicated the presence of GH5 family BGL gene in the Aspergillus unguis genomic DNA.From the partial gene sequencing results, specific as well as degenerate primers were designed for TAIL PCR. Sequencing results of the 1.0 Kb amplicon matched Aspergillus nidulans β -glucosidase gene which belongs to the GH1 family. The sequence mainly covered the N-Terminal region of the matching peptide. All the three BGL proteins ie. BGL1, BGL3 and BGL5 were purified by chromatography an electro elution from Native PAGE gels and were subjected to MALDI-TOF mass spectrometric analysis. The results showed that BGL1 peptide mass matched to . β -glucosidase-I of Aspergillus flavus which is a 92kDa protein with 69% protein coverage. The glucose tolerant β -glucosidase BGL5 mass matched to the catalytic C-terminal domain of β -glucosidase-F from Emericella nidulans, but the protein coverage was very low compared to the size of the Emericella nidulans protein. While comparing the size of BGL5 from Aspergillus unguis, the protein sequence coverage is more than 80%. BGL F is a glycosyl hydrolase family 3 protein.The properties of BGL5 seem to be very unique, in that it is a GH3 β -glucosidase with a very low molecular weight of ~10kDa and at the same time having catalytic activity and glucose 122 tolerance which is as yet un-described in GH β -glucosidases. The occurrence of a fully functional 10kDA protein with glucose tolerant BGL activity has tremendous implications both from the points of understanding the structure function relationships as well as for applications of BGL enzymes. BGL-3 showed similarity to BGL1 of Aspergillus aculateus which was another GH3 β -glucosidase. It may be noted that though PCR could detect GH1, GH3 and GH5 β-glucosidases in the fungus, the major isoforms BGL1 BGL3 and BGL5 were all GH3 family enzymes. This would imply that β-glucosidases belonging to other families may also co-exist in the fungus and the other minor isoforms detected in zymograms may account for them. In biomass hydrolysis, GT-BGL containing BGL enzyme was supplemented to cellulase and the performances of blends were compared with a cocktail where commercial β- glucosidase was supplemented to the biomass hydrolyzing enzyme preparation. The cocktail supplemented with A unguis BGL preparation yielded 555mg/g sugar in 12h compared to the commercial enzyme preparation which gave only 333mg/g in the same period and the maximum sugar yield of 858 mg/g was attained in 36h by the cocktail containing A. unguis BGL. While the commercial enzyme achieved almost similar sugar yield in 24h, there was rapid drop in sugar concentration after that, indicating probably the conversion of glucose back to di-or oligosaccharides by the transglycosylation activity of the BGl in that preparation. Compared this, the A.unguis enzyme containing preparation supported peak yields for longer duration (upto 48h) which is important for biomass conversion to other products since the hydrolysate has to undergo certain unit operations before it goes into the next stage ie – fermentation in any bioprocesses for production of either fuels or chemicals.. Most importantly the Aspergillus unguis BGL preparation yields approximately 1.6 fold increase in the sugar release compared to the commercial BGL within 12h of time interval and 2.25 fold increase in the sugar release compared to the control ie. Cellulase without BGL supplementation. The current study therefore leads to the identification of a potent new isolate producing glucose tolerant β - glucosidase. The organism identified as Aspergillus unguis comes under the Aspergillus nidulans group where most of the GT-BGL producers belong and the detailed studies showed that the glucose tolerant β -glucosidase was a very low molecular weight protein which probably belongs to the glycosyl hydrolase family 3. Inhibition kinetic studies helped to understand the Ki and it is the second highest among the nidulans group of Aspergilli. This has promoted us for a detailed study regarding the mechanism of glucose tolerance. The proteomic 123 analyses clearly indicate the presence of GH3 catalytic domain in the protein. Since the size of the protein is very low and still its active and showed glucose tolerance it is speculated that this could be an entirely new protein or the modification of the existing β -glucosidase with only the catalytic domain present in it. Hydrolysis experiments also qualify this BGL, a suitable candidate for the enzyme cocktail development for biomass hydrolysis