Search results for: Behavioural biometric

Authors: Sakthi Priya Balaji R., Vijayendar G.

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This paper proposes a technique to block adult images displayed in websites. The filter is designed so as to perform even in exceptional cases such as, where face detection is not possible or improper face visibility. This is achieved by using an alternative phase to extract the MFC (Most Frequent Color) from the Human Body regions estimated using a biometric of anthropometric distances between fixed rigidly connected body locations. The logical results generated can be protected from overriding by a firewall or intrusion, by encrypting the result in a SSH data packet.

Keywords: Face detection, characteristics extraction andclassification, Component based shape analysis and classification, open source SSH V2 protocol

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Authors: Edward Guillen, Daniel Padilla, Adriana Hernandez, Kenneth Barner

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Biometrics methods include recognition techniques such as fingerprint, iris, hand geometry, voice, face, ears and gait. The gait recognition approach has some advantages, for example it does not need the prior concern of the observed subject and it can record many biometric features in order to make deeper analysis, but most of the research proposals use high computational cost. This paper shows a gait recognition system with feature subtraction on a bundle rectangle drawn over the observed person. Statistical results within a database of 500 videos are shown.

Keywords: Autentication, Biometrics, Gait Recognition, Human Identification, Security.

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Authors: Jenny Ngo, Harry De Boer, Jürgen Enders

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Indonesian higher education has experienced significant changes over the last decade. In 1999, the government published an overall strategy for decentralisation and enhancement of local autonomy in many sectors, including (higher) education. Indonesian higher education reforms have forced universities to restructure their internal university governance to become more entrepreneurial. These new types of internal university governance are likely to affect the institutions’ leadership and management. This paper discusses the approach and findings of a study on the managerial leadership styles of deans in Indonesian universities. The study aims to get a better understanding of styles exhibited by deans manifested in their behaviours. Using the theories of reasoned action and planned behaviour, in combination with the competing values framework, a large-scale survey was conducted to gather information on the deans’ behaviours, attitudes, subjective norms, and perceived behavioural control. Based on the responses of a sample of 218 deans, the study identifies a number of leadership styles: the Master, the Competitive Consultant, the Consensual Goal-Setter, the Focused Team Captain, and the Informed Trust-Builder style. The study demonstrates that attitudes are the primary determinant of the styles that were found. Perceived behavioural control is a factor that explains some managerial leadership styles. By understanding the attitudes of deans in Indonesian universities, and their leadership styles, universities can strengthen their management and governance, and thus improve their effectiveness.

Keywords: Deans, Indonesian higher education, leadership and management, style.

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Authors: Girija Chetty, Monica Singh

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In this paper we propose a novel approach for ascertaining human identity based on fusion of profile face and gait biometric cues The identification approach based on feature learning in PCA-LDA subspace, and classification using multivariate Bayesian classifiers allows significant improvement in recognition accuracy for low resolution surveillance video scenarios. The experimental evaluation of the proposed identification scheme on a publicly available database [2] showed that the fusion of face and gait cues in joint PCA-LDA space turns out to be a powerful method for capturing the inherent multimodality in walking gait patterns, and at the same time discriminating the person identity..

Keywords: Biometrics, gait recognition, PCA, LDA, Eigenface, Fisherface, Multivariate Gaussian Classifier

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Authors: Cecilia Perri, Vincenzo Corvello

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The aim of the present study is to investigate consumers' determinants of intention toward the adoption of Smart Grid solutions and technologies. Ajzen's Theory of Planned Behaviour (TPB) model is applied and tested to explain the formation of such adoption intention. An exogenous variable, taking into account the resistance to change of individuals, was added to the basic model. The elicitation study allowed obtaining salient modal beliefs, which were used, with the support of literature, to design the questionnaire. After the screening phase, data collected from the main survey were analysed for evaluating measurement model's reliability and validity. Consistent with the theory, the results of structural equation analysis revealed that attitude, subjective norm, and perceived behavioural control positively, which affected the adoption intention. Specifically, the variable with the highest estimate loading factor was found to be the perceived behavioural control, and, the most important belief related to each construct was determined (e.g., energy saving was observed to be the most significant belief linked with attitude). Further investigation indicated that the added exogenous variable has a negative influence on intention; this finding confirmed partially the hypothesis, since this influence was indirect: such relationship was mediated by attitude. Implications and suggestions for future research are discussed.

Keywords: Adoption of innovation, consumers behaviour, energy management, smart grid, theory of planned behaviour.

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Authors: Luisa Mesquita Oliveira Ribeiro, Alexei Manso Correa Machado

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Handwritten signature is a unique form for recognizing an individual, used to discern documents, carry out investigations in the criminal, legal, banking areas and other applications. Signature verification is based on large amounts of biometric data, as they are simple and easy to acquire, among other characteristics. Given this scenario, signature forgery is a worldwide recurring problem and fast and precise techniques are needed to prevent crimes of this nature from occurring. This article carried out a study on the efficiency of the Capsule Network in analyzing and recognizing signatures. The chosen architecture achieved an accuracy of 98.11% and 80.15% for the CEDAR and GPDS databases, respectively.

Keywords: Biometrics, deep learning, handwriting, signature forgery.

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Authors: Anouar Ben Khalifa, Sami Gazzah, Najoua Essoukri BenAmara

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The Choquet integral is a tool for the information fusion that is very effective in the case where fuzzy measures associated with it are well chosen. In this paper, we propose a new approach for calculating fuzzy measures associated with the Choquet integral in a context of data fusion in multimodal biometrics. The proposed approach is based on genetic algorithms. It has been validated in two databases: the first base is relative to synthetic scores and the second one is biometrically relating to the face, fingerprint and palmprint. The results achieved attest the robustness of the proposed approach.

Keywords: Multimodal biometrics, data fusion, Choquet integral, fuzzy measures, genetic algorithm.

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Authors: Andrew Lock, Alastair Allen

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Fragile watermarking has been proposed as a means of adding additional security or functionality to biometric systems, particularly for authentication and tamper detection. In this paper we describe an experimental study on the effect of watermarking iris images with a particular class of fragile algorithm, reversible algorithms, and the ability to correctly perform iris recognition. We investigate two scenarios, matching watermarked images to unmodified images, and matching watermarked images to watermarked images. We show that different watermarking schemes give very different results for a given capacity, highlighting the importance ofinvestigation. At high embedding rates most algorithms cause significant reduction in recognition performance. However, in many cases, for low embedding rates, recognition accuracy is improved by the watermarking process.

Keywords: Biometrics, iris recognition, reversible watermarking.

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Authors: Ç. Gökçek-Saraç, Ş. Özen, N. Derin

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The N-methyl-D-aspartate (NMDA)-dependent pathway is the major intracellular signaling pathway implemented in both short- and long-term memory formation in the hippocampus which is the most studied brain structure because of its well documented role in learning and memory. However, little is known about the effects of RF-EMR exposure on NMDA receptor signaling pathway including activation of protein kinases, notably Ca²⁺/calmodulin-dependent protein kinase II alpha (CaMKIIα). The aim of the present study was to investigate the effects of acute and chronic 900 MHz RF-EMR exposure on both passive avoidance behaviour and hippocampal levels of CaMKIIα and its phosphorylated form (pCaMKIIα). Rats were divided into the following groups: Sham rats, and rats exposed to 900 MHz RF-EMR for 2 h/day for 1 week (acute group) or 10 weeks (chronic group), respectively. Passive avoidance task was used as a behavioural method. The hippocampal levels of selected kinases were measured using Western Blotting technique. The results of passive avoidance task showed that both acute and chronic exposure to 900 MHz RF-EMR can impair passive avoidance behaviour with minor effects on chronic group of rats. The analysis of western blot data of selected protein kinases demonstrated that hippocampal levels of CaMKIIα and pCaMKIIα were significantly higher in chronic group of rats as compared to acute groups. Taken together, these findings demonstrated that different duration times (1 week vs 10 weeks) of 900 MHz RF-EMR exposure have different effects on both passive avoidance behaviour of rats and hippocampal levels of selected protein kinases.

Keywords: Hippocampus, protein kinase, rat, RF-EMR.

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Authors: R. Abdulrahman, A. Eardley, A. Soliman

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The proliferation in the development of mobile learning (m-learning) has played a vital role in the rapidly growing electronic learning market. This relatively new technology can help to encourage the development of in learning and to aid knowledge transfer a number of areas, by familiarizing students with innovative information and communications technologies (ICT). M-learning plays a substantial role in the deployment of learning methods for nursing students by using the Internet and portable devices to access learning resources ‘anytime and anywhere’. However, acceptance of m-learning by students is critical to the successful use of m-learning systems. Thus, there is a need to study the factors that influence student’s intention to use m-learning. This paper addresses this issue. It outlines the outcomes of a study that evaluates the unified theory of acceptance and use of technology (UTAUT) model as applied to the subject of user acceptance in relation to m-learning activity in nurse education. The model integrates the significant components across eight prominent user acceptance models. Therefore, a standard measure is introduced with core determinants of user behavioural intention. The research model extends the UTAUT in the context of m-learning acceptance by modifying and adding individual innovativeness (II) and quality of service (QoS) to the original structure of UTAUT. The paper goes on to add the factors of previous experience (of using mobile devices in similar applications) and the nursing students’ readiness (to use the technology) to influence their behavioural intentions to use m-learning. This study uses a technique called ‘convenience sampling’ which involves student volunteers as participants in order to collect numerical data. A quantitative method of data collection was selected and involves an online survey using a questionnaire form. This form contains 33 questions to measure the six constructs, using a 5-point Likert scale. A total of 42 respondents participated, all from the Nursing Institute at the Armed Forces Hospital in Saudi Arabia. The gathered data were then tested using a research model that employs the structural equation modelling (SEM), including confirmatory factor analysis (CFA). The results of the CFA show that the UTAUT model has the ability to predict student behavioural intention and to adapt m-learning activity to the specific learning activities. It also demonstrates satisfactory, dependable and valid scales of the model constructs. This suggests further analysis to confirm the model as a valuable instrument in order to evaluate the user acceptance of m-learning activity.

Keywords: Mobile learning, nursing institute, unified theory of acceptance and use of technology model.

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Authors: Young Geun Kim, Tae Woo Lee, Changmin Yeo, Jung min Yoo, Yeo Jin Kang, Tack-Joong Kim, Byungjo Jung, Ji Hun Cha, Chan Hoi Hur, Dong-Sup Kim, Ki Jung Park, Han Sung Kim

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The intention of this lessons is to assess the probability of optical coherence tomography (OCT) for biometric recognition. The OCT is the foundation on an optical signal acquisition and processing method and has the micrometer-resolution. In this study, we used the porcine skin for verifying the abovementioned means. The porcine tissue was sound acknowledged for structural and immunohistochemical similarity with human skin, so it could be suitable for pre-clinical trial as investigational specimen. For this reason, it was tattooed by the tattoo machine with the tattoo-pigment. We detected the pattern of the tattooed skin by the OCT according to needle speed. The result was consistent with the histology images. This result showed that the OCT was effective to examine the tattooed skin section noninvasively. It might be available to identify morphological changes inside the skin.

Keywords: mechanical skin damage, optical coherence tomography, tattooed skin

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Authors: Mario Mastriani

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This paper describes a novel projection algorithm, the Projection Onto Span Algorithm (POSA) for wavelet-based superresolution and removing speckle (in wavelet domain) of unknown variance from Synthetic Aperture Radar (SAR) images. Although the POSA is good as a new superresolution algorithm for image enhancement, image metrology and biometric identification, here one will use it like a tool of despeckling, being the first time that an algorithm of super-resolution is used for despeckling of SAR images. Specifically, the speckled SAR image is decomposed into wavelet subbands; POSA is applied to the high subbands, and reconstruct a SAR image from the modified detail coefficients. Experimental results demonstrate that the new method compares favorably to several other despeckling methods on test SAR images.

Keywords: Projection, speckle, superresolution, synthetic aperture radar, thresholding, wavelets.

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Authors: Fatima Akhmedova, Simon Liao

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One of the most critical decision points in the design of a face recognition system is the choice of an appropriate face representation. Effective feature descriptors are expected to convey sufficient, invariant and non-redundant facial information. In this work we propose a set of Hahn moments as a new approach for feature description. Hahn moments have been widely used in image analysis due to their invariance, nonredundancy and the ability to extract features either globally and locally. To assess the applicability of Hahn moments to Face Recognition we conduct two experiments on the Olivetti Research Laboratory (ORL) database and University of Notre-Dame (UND) X1 biometric collection. Fusion of the global features along with the features from local facial regions are used as an input for the conventional k-NN classifier. The method reaches an accuracy of 93% of correctly recognized subjects for the ORL database and 94% for the UND database.

Keywords: Face Recognition, Hahn moments, Recognition-by-parts, Time-lapse.

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Authors: M. Cristea, F. Paran, P. Delhomme

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Eco-driving allows the driver to optimize his/her behaviour in order to achieve several types of benefits: reducing pollution emissions, increasing road safety, and fuel saving. One of the main rules for adopting eco-driving is to anticipate the traffic events by avoiding strong acceleration or braking and maintaining a steady speed when possible. Therefore, drivers have to comply with speed limits and time headway. The present study explored the role of three types of motivation and social norms in predicting French drivers- intentions to comply with speed limits and time headway as eco-driving practices as well as examine the variations according to gender and age. 1234 drivers with ages between 18 and 75 years old filled in a questionnaire which was presented as part of an online survey aiming to better understand the drivers- road habits. It included items assessing: a) behavioural intentions to comply with speed limits and time headway according to three types of motivation: reducing pollution emissions, increasing road safety, and fuel saving, b) subjective and descriptive social norms regarding the intention to comply with speed limits and time headway, and c) sociodemographical variables. Drivers expressed their intention to frequently comply with speed limits and time headway in the following 6 months; however, they showed more intention to comply with speed limits as compared to time headway regardless of the type of motivation. The subjective injunctive norms were significantly more important in predicting drivers- intentions to comply with speed limits and time headway as compared to the descriptive norms. In addition, the most frequently reported type of motivation for complying with speed limits and time headway was increasing road safety followed by fuel saving and reducing pollution emissions, hence underlining a low motivation to practice eco-driving. Practical implications of the results are discussed.

Keywords: Eco-driving, social norms, speed limits, time headway.

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Authors: S. Sowmyayani

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The advancement of computer-aided design helps the medical force and security force. Some applications include biometric recognition, elderly fall detection, face recognition, cancer recognition, tumor recognition, etc. This paper deals with different machine learning algorithms that are more generically used for any health care system. The most focused problems are classification and regression. With the rise of big data, machine learning has become particularly important for solving problems. Machine learning uses two types of techniques: supervised learning and unsupervised learning. The former trains a model on known input and output data and predicts future outputs. Classification and regression are supervised learning techniques. Unsupervised learning finds hidden patterns in input data. Clustering is one such unsupervised learning technique. The above-mentioned models are discussed briefly in this paper.

Keywords: Supervised learning, unsupervised learning, regression, neural network.

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Authors: A. Jalal, S. Kim

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Different methods containing biometric algorithms are presented for the representation of eigenfaces detection including face recognition, are identification and verification. Our theme of this research is to manage the critical processing stages (accuracy, speed, security and monitoring) of face activities with the flexibility of searching and edit the secure authorized database. In this paper we implement different techniques such as eigenfaces vector reduction by using texture and shape vector phenomenon for complexity removal, while density matching score with Face Boundary Fixation (FBF) extracted the most likelihood characteristics in this media processing contents. We examine the development and performance efficiency of the database by applying our creative algorithms in both recognition and detection phenomenon. Our results show the performance accuracy and security gain with better achievement than a number of previous approaches in all the above processes in an encouraging mode.

Keywords: Ubiquitous architecture, verification, Identification, recognition

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Authors: Gioacchino Lavanco, Floriana Romano, Anna Milio

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Terrorism represents an unexpected and unwanted change which challenges one-s social identity. We carried out a study to explore the demographic variables- role on the perception of personal and national threat, and to investigate the effects of perceived terrorist threat on people-s ways of life, moods, opinions and hopes. 313 residents of Palermo (Italy) were interviewed. The results pointed out that the fear of terrorism affects three areas: the cognitive, the emotional and the behavioural one.

Keywords: Disaster, national threat, personal threat, terrorism.

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Authors: Ali Safaeianpour, Nima Shamandi

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As air traffic expands, many airports have evolved into transit centers for people, information, and commerce, and technology implementation is an absolute part of airport development. Several challenges are in the way of implementing technology in an airport. Airport 4.0 proposes the "Smart Airport" concept, which focuses on using modern technologies such as Big Data, the Internet of Things (IoT), advanced biometric systems, blockchain, and cloud computing to alter and enhance passengers' journeys. Several common IoT concrete topics as partial keys to smart airports are discussed and introduced, ranging from automated check-in systems to exterior tracking processes, with the goal of enlightening more and more insightful ideas and proposals about smart airport solutions. IoT will dramatically alter people's lives by infusing intelligence, boosting the quality of life, and assembling it smarter. This paper reviews the approaches to transforming an airport into a smart airport and describes several enabling components of IoT and challenges that can hinder the implementation of a smart airport's function, which require to be addressed.

Keywords: Airport 4.0, Digital Airport, Smart airport, IoT.

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Authors: D. M. S. Bandara, Yunqi Lei, Ye Luo

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Fingerprints are suitable as long-term markers of human identity since they provide detailed and unique individual features which are difficult to alter and durable over life time. In this paper, we propose an algorithm to encrypt and decrypt fingerprint images by using a specially designed Elliptic Curve Cryptography (ECC) procedure based on block ciphers. In addition, to increase the confusing effect of fingerprint encryption, we also utilize a chaotic-behaved method called Arnold Cat Map (ACM) for a 2D scrambling of pixel locations in our method. Experimental results are carried out with various types of efficiency and security analyses. As a result, we demonstrate that the proposed fingerprint encryption/decryption algorithm is advantageous in several different aspects including efficiency, security and flexibility. In particular, using this algorithm, we achieve a margin of about 0.1% in the test of Number of Pixel Changing Rate (NPCR) values comparing to the-state-of-the-art performances.

Keywords: Arnold cat map, biometric encryption, block cipher, elliptic curve cryptography, fingerprint encryption, Koblitz’s Encoding.

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Authors: Julia Terlet, Thomas H. Beach, Yacine Rezgui

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Urbanization, population growth, climate change and the current increase in water demand have made the adoption of innovative demand management strategies crucial to the water industry. Water conservation in urban areas has to be improved by encouraging consumers to adopt more sustainable habits and behaviours. This includes informing and educating them about their households’ water consumption and advising them about ways to achieve significant savings on a daily basis. This paper presents a study conducted in the context of the European FP7 WISDOM Project. By integrating innovative Information and Communication Technologies (ICT) frameworks, this project aims at achieving a change in water savings. More specifically, behavioural change will be attempted by implementing smart meters and in-home displays in a trial group of selected households within Cardiff (UK). Using this device, consumers will be able to receive feedback and information about their consumption but will also have the opportunity to compare their consumption to the consumption of other consumers and similar households. Following an initial survey, it appeared necessary to implement these in-home displays in a way that matches consumer's motivations to save water. The results demonstrated the importance of various factors influencing people’s daily water consumption. Both the relevant literature on the subject and the results of our survey therefore led us to include within the in-home device a variety of elements. It first appeared crucial to make consumers aware of the economic aspect of water conservation and especially of the significant financial savings that can be achieved by reducing their household’s water consumption on the long term. Likewise, reminding participants of the impact of their consumption on the environment by making them more aware of water scarcity issues around the world will help increasing their motivation to save water. Additionally, peer pressure and social comparisons with neighbours and other consumers, accentuated by the use of online social networks such as Facebook or Twitter, will likely encourage consumers to reduce their consumption. Participants will also be able to compare their current consumption to their past consumption and to observe the consequences of their efforts to save water through diverse graphs and charts. Finally, including a virtual water game within the display will help the whole household, children and adults, to achieve significant reductions by providing them with simple tips and advice to save water on a daily basis. Moreover, by setting daily and weekly goals for them to reach, the game will expectantly generate cooperation between family members. Members of each household will indeed be encouraged to work together to reduce their water consumption within different rooms of the house, such as the bathroom, the kitchen, or the toilets. Overall, this study will allow us to understand the elements that attract consumers the most and the features that are most commonly used by the participants. In this way, we intend to determine the main factors influencing water consumption in order to identify the measures that will most encourage water conservation in both the long and short term.

Keywords: Behavioural change, ICT technologies, water consumption, water conservation.

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Authors: N. B. Mahesh Kumar, K. Premalatha

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The inherent skin patterns created at the joints in the finger exterior are referred as finger knuckle-print. It is exploited to identify a person in a unique manner because the finger knuckle print is greatly affluent in textures. In biometric system, the region of interest is utilized for the feature extraction algorithm. In this paper, local and global features are extracted separately. Fast Discrete Orthonormal Stockwell Transform is exploited to extract the local features. Global feature is attained by escalating the size of Fast Discrete Orthonormal Stockwell Transform to infinity. Two features are fused to increase the recognition accuracy. A matching distance is calculated for both the features individually. Then two distances are merged mutually to acquire the final matching distance. The proposed scheme gives the better performance in terms of equal error rate and correct recognition rate.

Keywords: Hamming distance, Instantaneous phase, Region of Interest, Recognition accuracy.

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Authors: Hassan Haleh, Zohreh Nasiri, Parisa Farahpour

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During recent years, the traditional learning approaches have undergone fundamental changes due to the emergence of new technologies such as multimedia, hypermedia and telecommunication. E-learning is a modern world phenomenon that has come into existence in the information age and in a knowledgebased society. E-learning has developed significantly within a short period of time. Thus it is of a great significant to secure information, allow a confident access and prevent unauthorized accesses. Making use of individuals- physiologic or behavioral (biometric) properties is a confident method to make the information secure. Among the biometrics, fingerprint is more acceptable and most countries use it as an efficient methods of identification. This article provides a new method to compare the fingerprint comparison by pattern recognition and image processing techniques. To verify fingerprint, the shortest distance method is used together with perceptronic multilayer neural network functioning based on minutiae. This method is highly accurate in the extraction of minutiae and it accelerates comparisons due to elimination of false minutiae and is more reliable compared with methods that merely use directional images.

Keywords: Fingerprint, minutiae, extraction of properties, multilayer neural network

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Authors: Mohamed Shahin, Ahmed Badawi, Mohamed Kamel

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This paper presents a hand vein authentication system using fast spatial correlation of hand vein patterns. In order to evaluate the system performance, a prototype was designed and a dataset of 50 persons of different ages above 16 and of different gender, each has 10 images per person was acquired at different intervals, 5 images for left hand and 5 images for right hand. In verification testing analysis, we used 3 images to represent the templates and 2 images for testing. Each of the 2 images is matched with the existing 3 templates. FAR of 0.02% and FRR of 3.00 % were reported at threshold 80. The system efficiency at this threshold was found to be 99.95%. The system can operate at a 97% genuine acceptance rate and 99.98 % genuine reject rate, at corresponding threshold of 80. The EER was reported as 0.25 % at threshold 77. We verified that no similarity exists between right and left hand vein patterns for the same person over the acquired dataset sample. Finally, this distinct 100 hand vein patterns dataset sample can be accessed by researchers and students upon request for testing other methods of hand veins matching.

Keywords: Biometrics, Verification, Hand Veins, PatternsSimilarity, Statistical Performance.

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Authors: Fattah Alizadeh, Saeed Nalousi, Chiman Savari

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Because of increasing demands for security in today-s society and also due to paying much more attention to machine vision, biometric researches, pattern recognition and data retrieval in color images, face detection has got more application. In this article we present a scientific approach for modeling human skin color, and also offer an algorithm that tries to detect faces within color images by combination of skin features and determined threshold in the model. Proposed model is based on statistical data in different color spaces. Offered algorithm, using some specified color threshold, first, divides image pixels into two groups: skin pixel group and non-skin pixel group and then based on some geometric features of face decides which area belongs to face. Two main results that we received from this research are as follow: first, proposed model can be applied easily on different databases and color spaces to establish proper threshold. Second, our algorithm can adapt itself with runtime condition and its results demonstrate desirable progress in comparison with similar cases.

Keywords: face detection, skin color modeling, color, colorfulimages, face recognition.

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Authors: Sanjay Kanade, Danielle Camara, Dijana Petrovska-Delacretaz, Bernadette Dorizzi

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In this paper, a two factor scheme is proposed to generate cryptographic keys directly from biometric data, which unlike passwords, are strongly bound to the user. Hash value of the reference iris code is used as a cryptographic key and its length depends only on the hash function, being independent of any other parameter. The entropy of such keys is 94 bits, which is much higher than any other comparable system. The most important and distinct feature of this scheme is that it regenerates the reference iris code by providing a genuine iris sample and the correct user password. Since iris codes obtained from two images of the same eye are not exactly the same, error correcting codes (Hadamard code and Reed-Solomon code) are used to deal with the variability. The scheme proposed here can be used to provide keys for a cryptographic system and/or for user authentication. The performance of this system is evaluated on two publicly available databases for iris biometrics namely CBS and ICE databases. The operating point of the system (values of False Acceptance Rate (FAR) and False Rejection Rate (FRR)) can be set by properly selecting the error correction capacity (ts) of the Reed- Solomon codes, e.g., on the ICE database, at ts = 15, FAR is 0.096% and FRR is 0.76%.

Keywords:

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Authors: Vishal Awasthi, Atul Kumar Agnihotri

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Face is a non-intrusive strong biometrics for identification of original and dummy facial by different artificial means. Face recognition is extremely important in the contexts of computer vision, psychology, surveillance, pattern recognition, neural network, content based video processing. The availability of a widespread face database is crucial to test the performance of these face recognition algorithms. The openly available face databases include face images with a wide range of poses, illumination, gestures and face occlusions but there is no dummy face database accessible in public domain. This paper presents a face detection algorithm based on the image segmentation in terms of distance from a fixed point and template matching methods. This proposed work is having the most appropriate number of nodal points resulting in most appropriate outcomes in terms of face recognition and detection. The time taken to identify and extract distinctive facial features is improved in the range of 90 to 110 sec. with the increment of efficiency by 3%.

Keywords: Face recognition, Principal Component Analysis, PCA, Linear Discriminant Analysis, LDA, Improved Support Vector Machine, iSVM, elastic bunch mapping technique.

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Authors: Zuraidasahana Zulkarnain, Mohd Shafry Mohd Rahim, Nor Anita Fairos Ismail, Mohd Azhar M. Arsad

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Handwritten signature is accepted widely as a biometric characteristic for personal authentication. The use of appropriate features plays an important role in determining accuracy of signature verification; therefore, this paper presents a feature based on the geometrical concept. To achieve the aim, triangle attributes are exploited to design a new feature since the triangle possesses orientation, angle and transformation that would improve accuracy. The proposed feature uses triangulation geometric set comprising of sides, angles and perimeter of a triangle which is derived from the center of gravity of a signature image. For classification purpose, Euclidean classifier along with Voting-based classifier is used to verify the tendency of forgery signature. This classification process is experimented using triangular geometric feature and selected global features. Based on an experiment that was validated using Grupo de Senales 960 (GPDS-960) signature database, the proposed triangular geometric feature achieves a lower Average Error Rates (AER) value with a percentage of 34% as compared to 43% of the selected global feature. As a conclusion, the proposed triangular geometric feature proves to be a more reliable feature for accurate signature verification.

Keywords: biometrics, euclidean classifier, feature extraction, offline signature verification, VOTING-based classifier

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Authors: S. Bader, N. Essoukri Ben Amara

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With the technological development and rise of virtual worlds, these spaces are becoming more and more attractive for cybercriminals, hidden behind avatars and fictitious identities. Since access to these spaces is not restricted or controlled, some impostors take advantage of gaining unauthorized access and practicing cyber criminality. This paper proposes an identity management approach for securing access to virtual worlds. The major purpose of the suggested solution is to install a strong security mechanism to protect virtual identities represented by avatars. Thus, only legitimate users, through their corresponding avatars, are allowed to access the platform resources. Access is controlled by integrating an authentication process based on biometrics. In the request process for registration, a user fingerprint is enrolled and then encrypted into a watermark utilizing a cancelable and non-invertible algorithm for its protection. After a user personalizes their representative character, the biometric mark is embedded into the avatar through a watermarking procedure. The authenticity of the avatar identity is verified when it requests authorization for access. We have evaluated the proposed approach on a dataset of avatars from various virtual worlds, and we have registered promising performance results in terms of authentication accuracy, acceptation and rejection rates.

Keywords: Identity management, security, biometrics authentication and authorization, avatar, virtual world.

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Authors: Jo Rhodes, Peter Lok, Zahra Sadeghinejad

Abstract:

The aim of this study is to determine the impact of metacognition on top management team members and firm performance based on full team integration. A survey of 1500 small to medium enterprises (SMEs) was initiated and 140 firms were obtained in this study (with response rate of 9%). The result showed that different metacognitive abilities of managers [knowledge and experience] could enhance team decision-making and problem solving, resulting in greater firm performance. This is a significant finding for SMEs because these organisations have small teams with owner leadership and entrepreneurial orientation.

Keywords: Metacognition, behavioural integration, top management team, performance.

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Authors: Chokri Jebali, Noureddine Boulejfen, Ali Gharsallah, Fadhel M. Ghannouchi

Abstract:

In this paper, a system level behavioural model for RF power amplifier, which exhibits memory effects, and based on multibranch system is proposed. When higher order terms are included, the memory polynomial model (MPM) exhibits numerical instabilities. A set of memory orthogonal polynomial model (OMPM) is introduced to alleviate the numerical instability problem associated to MPM model. A data scaling and centring algorithm was applied to improve the power amplifier modeling accuracy. Simulation results prove that the numerical instability can be greatly reduced, as well as the model precision improved with nonlinear model.

Keywords: power amplifier, orthogonal model, polynomialmodel , memory effects.

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