Security methods based on biometrics have been gaining importance increasingly in the last few years due to recent advances in biometrics technology and its reliability and efficiency in real world applications. Also, several major security disasters that occurred in the last decade have given a new momentum to this research area. The successful development of biometric security applications cannot only minimise such threats but may also help in preventing them from happening on a global scale. Biometric security methods take into account humans’ unique physical or behavioural traits that help to identify them based on their intrinsic characteristics. However, there are a number of issues related to biometric security, in particular with regard to surveillance images. The first issue is related to the poor visibility of the images produced by surveillance cameras and the second issue is concerned with the effective image retrieval based on user query. This research addresses both issues. This research addresses the first issue of low quality of surveillance images by proposing an integrated image enhancement approach for face detection. The proposed approach is based on contrast enhancement and colour balancing methods. The contrast enhancement method is used to improve the contrast, while the colour balancing method helps to achieve a balanced colour. Importantly, in the colour balancing method, a new process for colour cast adjustment is introduced which relies on statistical calculation. It can adjust the colour cast and maintain the luminance of the whole image at the same level. The research addresses the second issue relating to image retrieval by proposing a content-based image retrieval approach. The approach is based on the three welliii known algorithms: colour histogram, texture and moment invariants. Colour histogram is used to extract the colour features of an image. Gabor filter is used to extract the texture features and the moment invariant is used to extract the shape features of an image. The use of these three algorithms ensures that the proposed image retrieval approach produces results which are highly relevant to the content of an image query, by taking into account the three distinct features of the image and the similarity metrics based on Euclidean measure. In order to retrieve the most relevant images the proposed approach also employs a set of fuzzy heuristics to improve the quality of the results further. The integrated image enhancement approach is applied to the enhancement of low quality images produced by surveillance cameras. The performance of the proposed approach is evaluated by applying three face detection methods (skin colour based face detection, feature based face detection and image based face detection methods) to surveillance images before and after enhancement using the proposed approach. The results show a significant improvement in face detection when the proposed approach was applied. The performance of the content-based image retrieval approach is carried out using the standard Precision and Recall measures, and the results are compared with wellknown existing approaches. The results show the proposed approach perform s better than the well-known existing approaches.

Baigiamajame magistro darbe nagrinėjamas nekilnojamojo turto įmonių darbuotojų darbo efektyvumas ir jo didinimo galimybės panaudojant naujausias technologijas – biometrinę kompiuterio pelytę bei VGTU studentų ir dėstytojų sukurtą internetinę ekspertinę sistemą, duodančią patarimus darbuotojų našumui didinti. Darbe apibendrintai aprašomas Lietuvos ūkio darbo našumas, jo pasikeitimai per pastaruosius metus, bei veiksniai, turintys didžiausią įtaką darbo našumui. Taip pat darbe aprašomos biometrinės technologijos, apžvelgiamas jų panaudojimas nekilnojamojo turto sektoriuje ir galimybė jas pritaikyti darbo efektyvumui didinti. Atlikus stebėjimus biometrine kompiuterio pelyte ir nustačius didžiausią įtaką darbuotojų našumui darančius veiksnius, remiantis A. Maslowo poreikių teorija buvo sukurta ekspertinė darbo našumo didinimo sistema. Išanalizavus darbo su biometrine pelyte ir sukurta ekspertine sistema rezultatus, darbo gale pateikiamos darbo išvados ir pasiūlymai. / The labour productivity problem and possibility to improve labour productivity by using biometric technologies and web-based expert system, developed by students and academics of VGTU is analyzed in this thesis. Summarized description of the labour productivity in general, its progress during few past years in Lithuania and factors that make the biggest influence on the level of labour productivity are described. Also the work contains overview of the biometric systems, usage of them in real estate and the possibility to increase labour productivity. After making observations during work with biometric mouse and identifying factors that affect productivity the most, the expert system, based on the A.Maslows hierarchy of needs was developed. Conclusion and suggestions were made after performing the analysis of the results of working with the biometric mouse and web-based expert system.

Although handwritten signature verification has been extensively researched, it has not achieved optimum accuracy rate. Therefore, efficient and accurate signature verification techniques are required since signatures are still widely used as a means of personal verification. This research work presents efficient distance-based classification techniques as an alternative to supervised learning classification techniques (SLTs). Two different feature extraction techniques were used, namely the Enhanced Modified Direction Feature (EMDF) and the Local Directional Pattern feature (LDP). These were used to analyze the effect of using several different distance-based classification techniques. Among the classification techniques used, are the cosine similarity measure, Mahalanobis, Canberra, Manhattan, Euclidean, weighted Euclidean and fractional distances. Additionally, the novel weighted fractional distances, as well as locally optimized resampling of feature vector sizes were tested. The best accuracy was achieved through applying a combination of the weighted fractional distances and locally optimized resampling classification techniques to the Local Directional Pattern feature extraction. This combination of multiple distance-based classification techniques achieved accuracy rate of 89.2% when using the EMDF feature extraction technique, and 90.8% when using the LDP feature extraction technique. These results are comparable to those in literature, where the same feature extraction techniques were classified with SLTs. The best of the distance-based classification techniques were found to produce greater accuracy than the SLTs. / Thesis (M.Sc.)-University of KwaZulu-Natal, Westville, 2012.

Naval Postgraduate School's (NPS) Tactical Network Topology (TNT) experiments seek to develop, implement and identify sensor-unmanned vehicle network, and network-centric operations to assist DoD warfighters in the Global War on Terrorism (GWOT). Using biometric data for rapid identification of High Value Targets (HVT) in ground and Maritiime Interdiction Operations (MIO) is critical to the emeging special operations concept. The goal is to explore solutions and operational constraints associated with biometric data analysis and rapid identification by means of adhoc self forming sensor unmanned vehicle (UV) wireless networks. The objectives of this thesis are to look at how biometrics has performed in a testbed environment that is simulating a real special operations environment in theatre. This thesis is meant to explore and explain the biometrics process that was conducted on top of the tactical network and evaluate its performance. This thesis provided the process model for biometrics identification in the tactical networks environment. This thesis also evaluated the length of time that it took to transmit the fingerprint data from the field to the ABIS databvase, with an identification result then sent back to the field. The longest time that was observed was 70 minutes (using low bandwidth Satellite communications), while the shortest time was 4 minutes for reachback to ABIS and 2 minutes for a local database.

The issue of traditional user authentication methods, such as username/passwords, when accessing information systems, the Internet, and Web-based applications still pose significant vulnerabilities. The problem of user authentication including physical and logical access appears to have limited, if any, coverage in research from the perspective of biometric as ‘something the user knows.’ Previous methods of establishing ones’ identity by using a password, or presenting a token or identification (ID) card are vulnerable to circumvention by misplacement or unauthorized sharing. The need for reliable user authentication techniques has increased in the wake of heightened concerns about information security and rapid advancements in networking, communication, and mobility. The main goal of this research study was to examine the role of the authentication method (BIO-PIN™ or username/password) and time, on the effectiveness of authentication, as well as the users’ ability to remember the BIO-PIN™ versus username/password (UN/PW). Moreover, this study compared the BIO-PIN™ with a traditional multi-factor biometric authentication using multiple fingerprints (without sequence) and a numerical PIN sequence (noted as "BIO+PIN"). Additionally, this research study examined the authentication methods when controlled for age, gender, user’s computer experience, and number of accounts. This study used a quasi-experimental multiple baseline design method to evaluate the effectiveness of the BIO-PIN™ authentication method. The independent, dependent, and control variables were addressed using descriptive statistics and Multivariate Analysis of Variance (MANOVA) statistical analysis to compare the BIO-PIN™, the BIO+PIN, and UN/PW authentication methods for research questions (RQs) 1 and 2. Additionally, the Multivariate Analysis of Covariance (MANCOVA) was used to address RQ 3 and RQ4, which seeks to test any differences when controlled by age, gender, user experience, and number of accounts. This research study was conducted over a 10-week period with participant engagement occurring over time including a registration week and in intervals of 2 weeks, 3 weeks, and 5 weeks. This study advances the current research in multi-factor biometric authentication and increases the body of knowledge regarding users’ ability to remember industry standard UN/PWs, the BIO-PIN™ sequence, and traditional BIO+PIN.

D'une manière générale, la biométrie a pour objectif d'établir ou de vérifier l'identité d'individu, notamment à partir de ces caractéristiques physiques ou comportementales. Cette pratique tend à remplacer les méthodes traditionnelles basées sur la connaissance, à savoir un mot de passe ou un code PIN ou basées sur les possessions telles qu'une pièce d'identité ou un badge. Au quotidien, plusieurs modalités biométriques ont été développées dans une certaine mesure, dont les produits sont disponibles et déjà utilisés dans des nombreuses applications. La reconnaissance biométrique est un domaine de recherche qui ne cesse pas d'évoluer et la recherche des nouvelles modalités de hautes performances est d'actualité. L'objectif de notre thèse consiste à développer et d'évaluer de nouvelles modalités biométriques basées sur des caractéristiques cachées, infalsifiables et ne pouvant pas être modifiées volontairement. C'est dans ce contexte que nous introduisons une nouvelle modalité biométrique utilisant les caractéristiques du cerveau humain et la faisabilité d'une telle modalité a fait l'objet de notre étude. À cet effet, des images volumiques cérébrales, obtenues par IRM (Imagerie par Résonance Magnétique) sont utilisées pour en extraire les informations pertinentes et générer par la suite des codes biométriques du cerveau, appelés « BrainCode », qui serviront à l'identification ou à l'authentification d'un individu. Ainsi, nous avons élaboré trois techniques de reconnaissance biométrique. La première technique utilise l'information de la texture d'une image numérique du cerveau comme signature individuelle, alors que la deuxième est basée sur l'utilisation des caractéristiques géométriques et morphologiques du cerveau. Enfin, la dernière technique explorée se base sur la fusion des caractéristiques géométriques et les caractéristiques de la texture du cerveau. Ces nouvelles techniques biométriques nécessitent évidemment l'acquisition des images IRM du cerveau en considérant, uniquement des personnes saines et adultes.Les résultats obtenus ont conduit à des performances de reconnaissance intéressantes. Plus précisément, la première technique, basée sur l'analyse de texture et la génération d'un « BrainCode » du cerveau, permet d'obtenir une précision de vérification de l'ordre de 97,53% avec un FAR = 1,5%, FRR = 3,41% et un EER = 2,72%. La deuxième technique, utilisant un modèle géométrique du cerveau, appelé « MGC » (Modèle Géométrique du Cerveau), nous arrivons à une précision maximale de l'ordre de 98,80% avec un FAR = 0,09%, un FRR = 2,31% et un EER = 1,92%. Enfin, la fusion des caractéristiques géométriques et de texture, permet d'atteindre une précision de l'ordre de 99,43% avec un FAR = 0,32% et un FRR = 0,72%. Dans cette étude, nous nous sommes aussi intéressés à l'étude de la robustesse des approches proposées par rapport au bruit / In general, biometrics aims is the identification or verification of individual, especially using their physical or behavioral characteristics. This practice tends to replace the traditional knowledge-based methods such us a password or PIN code and token-based methods such as identity document or a badge. Daily, multiple biometric modalities have been developed, where the products are available and already used in many applications. Biometric recognition is a research area that does not stop evolving and seeking new forms of high performance modalities. The main of this thesis is to develop and evaluate new methods based on hidden biometric features, tamper-proof and can't be voluntarily changed. In this context, that we introduce a new biometric modality that using human brain characteristics and the feasibility of such a method was the object of our study. For this, brain volumetric images, obtained by MRI (Magnetic Resonance Imaging) are used to extract the most discriminative brain patterns. Afterward, biometric code of the brain, called « BrainCode », is generated that serve on individual identification or authentication. Thus, we developed three biometric techniques based on the brain. The first technique uses textural patterns of a brain digital image, while the second technique is based on the use of morphological and geometrical characteristics of the brain. The last explored technique, based on the fusion of geometric features and the textural patterns from brain MRI slice. These new biometric techniques obviously require the acquisition of brain MRI images by considering only healthy and adult peoples. According to obtained results from experiments, the developed techniques lead to interesting recognition performance. More precisely, the first technique based on texture patterns analysis and « BrainCode » generation, provides about 97,53% of accuracy, FAR = 1,5%, FRR = 3,41% and the EER = 2,72%. The second technique, using a geometric model of the brain, called « GMB » (Geometric Model of the Brain), we obtained a maximum accuracy around 98,80%, FAR = 0,09%, FRR = 2,31% and the EER = 1,92%. Finally, the merger of geometric features and the texture, we have reached about 99, 47% of accuracy, FAR = 0,32% and the FRR = 0,72%. In this study, we are also interested on the robustness study of the proposed approaches against noise

Data protection in the EU - Biometric data The main aim of this thesis is to deal with the data protection in connection with the biometric data. In the first chapter, the author of this work deals with the historical context. The right to privacy even nowadays represents the solid ground of the data protection. Therefore, its de- limitation and subsequent connection with the data privacy is of an upmost importance for a proper understanding of this problematics. The author also deals with the data protection not only in the european context, but also with the disunited legislation in the US, where a legisla- tion in the context of general data protection regulation is absent. The second chapter mainly dealt with stating the general legal principles and their rel- evance to the legal order as well as with the special principles laid down in the regulation, which are mandatory to be upheld. The third chapter dealt with the term of personal data. Moreover, it was also important to define the other terms, which goes hand in hand with the personal data term. Therefore, anonymous data as a personal data, which went through the anonymisation process, as well as the special category of personal data, which represents the fundament of the problematics of the biometric data and lastly also the term of data...

Two experiments were conducted to investigate the impact of poser and perceiver gender on the Happiness/Anger Superiority effect and the Female Advantage in facial expression recognition. Happy, neutral, and angry facial expressions were presented on male and female faces under Continuous Flash Suppression (CFS). Participants of both genders indicated when the presented faces broke through the suppression. In the second experiment, angry and happy expressions were reduced to 50% intensity. At full intensity, there was no difference in the reaction time for female neutral and angry faces, but male faces showed a difference in detection between all expressions. Across experiments, male faces were detected later than female faces for all facial expressions. Happiness was generally detected faster than anger, except when on female faces at 50% intensity. No main effect for perceiver gender emerged. It was concluded that happiness is superior to anger in CFS, and that poser gender affects facial expression recognition. / by Sophia Peaco. / Thesis (M.A.)--Florida Atlantic University, 2013. / Includes bibliography. / Mode of access: World Wide Web. / System requirements: Adobe Reader.

Biometrics is the science and technology of measuring and analyzing biological data for authentication purposes. Its progress has brought in a large number of civilian and government applications. The candidate modalities used in biometrics include retinas, fingerprints, signatures, audio, faces, etc. There are two types of biometric system: single modal systems and multiple modal systems. Single modal systems perform person recognition based on a single biometric modality and are affected by problems like noisy sensor data, intra-class variations, distinctiveness and non-universality. Applying multiple modal systems that consolidate evidence from multiple biometric modalities can alleviate those problems of single modal ones. Integration of evidence obtained from multiple cues, also known as fusion, is a critical part in multiple modal systems, and it may be consolidated at several levels like feature fusion level, matching score fusion level and decision fusion level. Among biometric modalities, both audio and face modalities are easy to use and generally acceptable by users. Furthermore, the increasing availability and the low cost of audio and visual instruments make it feasible to apply such Audio-Visual (AV) systems for security applications. Therefore, this dissertation proposes an algorithm of face recognition. In addition, it has developed some novel algorithms of fusion in different levels for multiple modal biometrics, which have been tested by a virtual database and proved to be more reliable and robust than systems that rely on a single modality. / by Lin Huang. / Thesis (Ph.D.)--Florida Atlantic University, 2010. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2010. Mode of access: World Wide Web.

Facial reconstructions, like archaeology, consists of many layers that one must get through to understand the whole picture. The development of the methods that reconstructions rely on, occurred during the 20th century. By focusing on the various elements such as studies of tissue depth, chemical processes (DNA and isotope analysis), solid craftsmanship and the development of computer technology, researchers around the world have been able to build a method that can give us an extended understanding of history. However, a lot of opinions have risen for the subject, people begin to question it ́s accuracy and what the real purpose really is. Besides the reliability of facial reconstruction, the experience of how a facial reconstruction is perceived by another person is equally important, the ethical principles have been brought up to discussion because it involves human remains. Discussions may occur during cases when facial reconstructions are inevitable, one example could be with minority groups that have a different view on how a body should be handled and treated after death. These scenarios are more likely to develop in the identification in forensic contexts, but the problem may also increase in archaeological contexts if the remains are from more recent times and the individuals as a population group has suffered repression. Therefore, this paper aims to discuss such questions but also embark on a mission to perform a facial reconstruction of an individual from the medieval church of St. Hans and the challenges that may occur during the way. The American method used in this essay shows that you can get a good result by following the instructions and guidelines that are displayed in various books and articles.