Business plan for a provider of access control systems based on fingerprints

This master thesis consist on a business plan that describes a technology business idea planning to make an access and time attendance control service based on fingerprints through a remote system. The main characteristics of this product are a low cost system and low installation impact on client's premises, respect to existing systems on biometric market. Although some of main competitors are beginning to offer more portable and wireless technology devices, there is a market gap to cover, taking a low cost and a easy installation as core values to apply this technology in different sectors, in order to offer a good value for money ratio product to attract potential clients who intend to use biometric systems (associated with a high security, economic cost and installation impact) respect traditional access and time attendance control technologies as magnetic cards, passwords usage..etc. The aim is to provide a product to attract clients requiring these services in environments where previously this wasn't considered for their high cost and installation impact to realize shifts control and other complementary functions as authentication for a photocopier usage, meeting rooms access...etc. Therefore the product offered is not focused in offering a high security system for critical environments like an airport for example, but it's directed to those environments where the purpose is to make a flexible and economical access and/or time attendance control, providing an optimal security level through a low-cost fingerprint system with low impact in their installation (easy installation in client premises to the system work) that can be consulted through an Internet connection. The objective of this thesis is to develop a business plan, where it's seeking a business opportunity that implies a technological analysis to offer a profitable solution for a company capable of performing the requirements described, taking into account all intermediate steps to get there. Finally, after analyzing all important parameters of a business plan evaluation, we can say that it's a profitable business idea

Analysis Of Data Stratification In A Multi-Sensor Fingerprint Dataset Using Match Score Statistics

Biometric data is an essential feature employed in testing the performance of any real time biometric recognition system prior to its usage. The variations introduced in the match performance critically determine the authenticity of the biometric data to be able to be used in an everyday scenario for the testing of biometric verification systems. This study in totality aims at understanding the impact of data stratification of a such a biometric test dataset on the match performance of each of its stratum. In order to achieve this goal, the fingerprint dataset of the West Virginia University\u27s 2012 BioCOP has been employed which is a part of the many multimodal biometric data collection projects that the University has accomplished. This test dataset has been initially segmented based on the scanners employed in the process of data acquisition to check for the variations in match performance with reference to the acquisition device. The secondary stage of data stratification included the creation of stratum based on the demographic features of the subjects in the dataset.;The main objectives this study aims to achieve are:;• Developing a framework to assess the match score distributions of each stratum..;• Assessing the match performance of demographic strata in comparison to the total dataset..;• Statistical match performance evaluation using match score statistics..;Following the generation of genuine and imposter match score distributions , Receiver Operating Characteristic Curves (ROC) were plotted to compare the match performance of each demographic stratum with respect to the total dataset. The divergence measures KLD and JSD have been calculated which signify the amount of variation between the match score distributions of each stratum. With the help of these procedures, the task of estimating the effect of data stratification on the match performance has been accomplished which serves as a measure of understanding the impact of this fingerprint dataset when used for biometric testing purposes

Fusion of fingerprint presentation attacks detection and matching: a real approach from the LivDet perspective

The liveness detection ability is explicitly required for current personal verification systems in many security applications. As a matter of fact, the project of any biometric verification system cannot ignore the vulnerability to spoofing or presentation attacks (PAs), which must be addressed by effective countermeasures from the beginning of the design process. However, despite significant improvements, especially by adopting deep learning approaches to fingerprint Presentation Attack Detectors (PADs), current research did not state much about their effectiveness when embedded in fingerprint verification systems. We believe that the lack of works is explained by the lack of instruments to investigate the problem, that is, modelling the cause-effect relationships when two systems (spoof detection and matching) with non-zero error rates are integrated. To solve this lack of investigations in the literature, we present in this PhD thesis a novel performance simulation model based on the probabilistic relationships between the Receiver Operating Characteristics (ROC) of the two systems when implemented sequentially. As a matter of fact, this is the most straightforward, flexible, and widespread approach. We carry out simulations on the PAD algorithms’ ROCs submitted to the editions of LivDet 2017-2019, the NIST Bozorth3, and the top-level VeriFinger 12.0 matchers. With the help of this simulator, the overall system performance can be predicted before actual implementation, thus simplifying the process of setting the best trade-off among error rates. In the second part of this thesis, we exploit this model to define a practical evaluation criterion to assess whether operational points of the PAD exist that do not alter the expected or previous performance given by the verification system alone. Experimental simulations coupled with the theoretical expectations confirm that this trade-off allows a complete view of the sequential embedding potentials worthy of being extended to other integration approaches

Postmortem iris recognition and its application in human identification

Iris recognition is a validated and non-invasive human identification technology currently implemented for the purposes of surveillance and security (i.e. border control, schools, military). Similar to deoxyribonucleic acid (DNA), irises are a highly individualizing component of the human body. Based on a lack of genetic penetrance, irises are unique between an individual’s left and right iris and between identical twins, proving to be more individualizing than DNA. At this time, little to no research has been conducted on the use of postmortem iris scanning as a biometric measurement of identification. The purpose of this pilot study is to explore the use of iris recognition as a tool for postmortem identification. Objectives of the study include determining whether current iris recognition technology can locate and detect iris codes in postmortem globes, and if iris scans collected at different postmortem time intervals can be identified as the same iris initially enrolled. Data from 43 decedents involving 148 subsequent iris scans demonstrated a subsequent match rate of approximately 80%, supporting the theory that iris recognition technology is capable of detecting and identifying an individual’s iris code in a postmortem setting. A chi-square test of independence showed no significant difference between match outcomes and the globe scanned (left vs. right), and gender had no bearing on the match outcome. There was a significant relationship between iris color and match outcome, with blue/gray eyes yielding a lower match rate (59%) compared to brown (82%) or green/hazel eyes (88%), however, the sample size of blue/gray eyes in this study was not large enough to draw a meaningful conclusion. An isolated case involving an antemortem initial scan collected from an individual on life support yielded an accurate identification (match) with a subsequent scan captured at approximately 10 hours postmortem. Falsely rejected subsequent iris scans or "no match" results occurred in about 20% of scans; they were observed at each PMI range and varied from 19-30%. The false reject rate is too high to reliably establish non-identity when used alone and ideally would be significantly lower prior to implementation in a forensic setting; however, a "no match" could be confirmed using another method. Importantly, the data showed a false match rate or false accept rate (FAR) of zero, a result consistent with previous iris recognition studies in living individuals. The preliminary results of this pilot study demonstrate a plausible role for iris recognition in postmortem human identification. Implementation of a universal iris recognition database would benefit the medicolegal death investigation and forensic pathology communities, and has potential applications to other situations such as missing persons and human trafficking cases

A Longitudinal Analysis on the Feasibility of Iris Recognition Performance for Infants 0-2 Years Old

The focus of this study was to longitudinally evaluate iris recognition for infants between the ages of 0 to 2 years old. Image quality metrics of infant and adult irises acquired on the same iris camera were compared. Matching performance was evaluated for four groups, infants 0 to 6 months, 7 to 12 months, 13 to 24 months, and adults. A mixed linear regression model was used to determine if infants’ genuine similarity scores changed over time. This study found that image quality metrics were different between infants and adults but in the older group, (13 to 24 months old) the image quality metric scores were more likely to be similar to adults. Infants 0 to 6 months old had worse performance at an FMR of 0.01% than infants 7 to 12 months, 13 to 24 months, and adults

Fingerprint Recognition for Children

This document is the final report of the Fingerprint Recognition Study of Children below the Age of 12 Years . The key findings of the study are: • Growth has limited influence on fingerprint recognition • Size (in terms of the dimensions of the relevant fingerprint characteristics) does not constitute any theoretical barrier for automated fingerprint recognition. • Image quality (in terms of low contrast and distortion effects) is the ultimate problem for child fingerprints, and image quality is strongly influenced by size. • Relevant quality metrics for fingerprints need revision with regard to the children case. • Isotropic growth model may serve as a good approximation to cover changes over time. • Alternative acquisition devices for fingerprints should be seriously considered in the future. Apart from these major findings, the report provides a number of recommendations to improve the process of acquiring fingerprints from children.JRC.G.7-Digital Citizen Securit

Business plan for a provider of access control systems based on fingerprints

This master thesis consist on a business plan that describes a technology business idea planning to make an access and time attendance control service based on fingerprints through a remote system. The main characteristics of this product are a low cost system and low installation impact on client's premises, respect to existing systems on biometric market. Although some of main competitors are beginning to offer more portable and wireless technology devices, there is a market gap to cover, taking a low cost and a easy installation as core values to apply this technology in different sectors, in order to offer a good value for money ratio product to attract potential clients who intend to use biometric systems (associated with a high security, economic cost and installation impact) respect traditional access and time attendance control technologies as magnetic cards, passwords usage..etc. The aim is to provide a product to attract clients requiring these services in environments where previously this wasn't considered for their high cost and installation impact to realize shifts control and other complementary functions as authentication for a photocopier usage, meeting rooms access...etc. Therefore the product offered is not focused in offering a high security system for critical environments like an airport for example, but it's directed to those environments where the purpose is to make a flexible and economical access and/or time attendance control, providing an optimal security level through a low-cost fingerprint system with low impact in their installation (easy installation in client premises to the system work) that can be consulted through an Internet connection. The objective of this thesis is to develop a business plan, where it's seeking a business opportunity that implies a technological analysis to offer a profitable solution for a company capable of performing the requirements described, taking into account all intermediate steps to get there. Finally, after analyzing all important parameters of a business plan evaluation, we can say that it's a profitable business idea

Intelligent Sensing for Robotic Re-Manufacturing in Aerospace - An Industry 4.0 Design Based Prototype

Emerging through an industry-academia collaboration between the University of Sheffield and VBC Instrument Engineering Ltd, a proposed robotic solution for remanufacturing of jet engine compressor blades is under ongoing development, producing the first tangible results for evaluation. Having successfully overcome concept adaptation, funding mechanisms, design processes, with research and development trials, the stage of concept optimization and end-user application has commenced. A variety of new challenges is emerging, with multiple parameters requiring control and intelligence. An interlinked collaboration between operational controllers, Quality Assurance (QA) and Quality Control (QC) systems, databases, safety and monitoring systems, is creating a complex network, transforming the traditional manual re-manufacturing method to an advanced intelligent modern smart-factory. Incorporating machine vision systems for characterization, inspection and fault detection, alongside advanced real-time sensor data acquisition for monitoring and evaluating the welding process, a huge amount of valuable industrial data is produced. Information regarding each individual blade is combined with data acquired from the system, embedding data analytics and the concept of ìInternet of Thingsî (IoT) into the aerospace re-manufacturing industry. The aim of this paper is to give a first insight into the challenges of the development of an Industry 4.0 prototype system and an evaluation of first results of the operational prototype

Biometric Spoofing: A JRC Case Study in 3D Face Recognition

Based on newly available and affordable off-the-shelf 3D sensing, processing and printing technologies, the JRC has conducted a comprehensive study on the feasibility of spoofing 3D and 2.5D face recognition systems with low-cost self-manufactured models and presents in this report a systematic and rigorous evaluation of the real risk posed by such attacking approach which has been complemented by a test campaign. The work accomplished and presented in this report, covers theories, methodologies, state of the art techniques, evaluation databases and also aims at providing an outlook into the future of this extremely active field of research.JRC.G.6-Digital Citizen Securit