Enhancement of Latent Fingerprint Recognition Using Global Transform

Latent Fingerprints plays a vital role in identifying thefts, crime etc. Latent fingerprints are of 3 types. Noise in the Latent Fingerprints is removed by smoothing. Manual marking in Latent Fingerprint is slow and also latent examiner may make mistake while marking. The minutiae in the same latent marked by different latent examiners or even by the same examiner (but at different times) may not be the same. To overcome this issue new Orientation field estimation algorithm is introduced. It based on latent fingerprint feature extraction and edge detection. Orientation field estimation algorithm has dictionary construction stage. Dictionary Construction has 2 Stages. i) Offline stage ii) online stage. Orientation field estimation algorithm is applied for Overlapped fingerprint. Hough transform is used for detecting edges. It is shown that this method is slower to recognize latent fingerprint feature extraction and edge linking. In order to further increase the speed and perfect edge linking Hough transform method can be modified for better performance. Global transform is used for perfect edge linking and get the full fingerprint structure and comparison is made between two transforms to show which transform is better. DOI: 10.17762/ijritcc2321-8169.15034

Um novo arcabouço para análise de qualidade de imagens de impressões digitais de alta resolução

Orientador: Neucimar Jerônimo LeiteTese (doutorado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: A falta de robustez referente à degradação de qualidade de conjuntos de características extraídas de padrões de cristas-e-vales, contidos na epiderme dos dedos humanos, é uma das questões em aberto na análise de imagens de impressões digitais, com implicações importantes em problemas de segurança, privacidade e fraude de identificação. Neste trabalho, introduzimos uma nova metodologia para analisar a qualidade de conjuntos de características de terceiro nível em imagens de impressões digitais representados, aqui, por poros de transpiração. A abordagem sugerida leva em conta a interdependência espacial entre as características consideradas e algumas transformações básicas envolvendo a manipulação de processos pontuais e sua análise a partir de ferramentas anisotrópicas. Foram propostos dois novos algoritmos para o cálculo de índices de qualidade que se mostraram eficazes na previsão da qualidade da correspondência entre as impressões e na definição de pesos de filtragem de características de baixa qualidade a ser empregado num processo de identificação. Para avaliar experimentalmente o desempenho destes algoritmos e suprir a ausência de uma base de dados com níveis de qualidade controlados, criamos uma base de dados com diferentes recursos de configuração e níveis de qualidade. Neste trabalho, propusemos ainda um método para reconstruir imagens de fase da impressão digital a partir de um dado conjunto de coordenadas de poros. Para validar esta idéia sob uma perspectiva de identificação, consideramos conjuntos de minúcias presentes nas imagens reconstruídas, inferidas a partir das configurações de poros, e associamos este resultado ao problema típico de casamento de impressões digitaisAbstract: The lack of robustness against the quality degradation affecting sets of features extracted from patterns of epidermal ridges on our fingers is one of the open issues in fingerprint image analysis, with implications for security, privacy, and identity fraud. In this doctorate work we introduce a new methodology to analyze the quality of sets of level-3 fingerprint features represented by pores. Our approach takes into account the spatial interrelationship between the considered features and some basic transformations involving point process and anisotropic analysis. We propose two new quality index algorithms, which have proved to be effective as a matcher predictor and in the definition of weights filtering out low-quality features from an identification process. To experimentally assess the performance of these algorithms and supply the absence of a feature-based controlled quality database in the biometric community, we created a dataset with features configurations containing different levels of quality. In this work, we also proposed a method for reconstructing phase images from a given set of pores coordinates. To validate this idea from an identification perspective, we considered the set of minutia present in the reconstructed images and inferred from the pores configurations and used this result in fingerprint matchingsDoutoradoCiência da ComputaçãoDoutor em Ciência da Computação01-P-3951/2011147050/2012-0CAPESCNP

Individual and collective identification in contemporary forensics

It has long been understood that individual and collective identification are inexorably intertwined. This convergence is not limited to genetics. This paper discusses the convergence of individual and collective identification in a comparative analysis of three other forensic areas: fingerprint analysis, microscopic hair comparison, and microbiome forensics. In all three case studies, we see purportedly individualizing technologies reverting, in a sense, to collective identification. Presumably, this has much to do with the perceived utility of collective identification. When knowing precisely who is the donor of a trace is not possible, or not useful, then knowing that the donor is ‘white,’ or ‘black,’ or ‘Middle Eastern’ begins to seem somehow useful. In each case, we also see that these collective identifications are ultimately founded on crude and broad, seemingly ‘commonsensical’ or ‘social,’ racial categories. These categories, meanwhile, are based on a less-than-fully-transparent combination of self-identification or official ascription. These suspect data are then transformed into seemingly persuasive scientific claims about the genetic attributes of this or that ‘race,’ ‘ethnicity,’ or ‘ancestry.’ Through this comparison the paper will explore how the individual and the collective are ‘done’ differently and similarly in different forensic disciplines

Fingerprint Recognition in Biometric Security -A State of the Art

Today, because of the vulnerability of standard authentication system, law-breaking has accumulated within the past few years. Identity authentication that relies on biometric feature like face, iris, voice, hand pure mathematics, handwriting, retina, fingerprints will considerably decrease the fraud. so that they square measure being replaced by identity verification mechanisms. Among bioscience, fingerprint systems are one amongst most generally researched and used. it\'s fashionable due to their easy accessibility. during this paper we tend to discuss the elaborated study of various gift implementation define strategies together with their comparative measures and result analysis thus as realize a brand new constructive technique for fingerprint recognition

Fingerprint Authentication System

Fingerprint is one of the most widely used biometric modality for recognition due to its reliability, non-invasive characteristic, speed and performance. The patterns remain stable throughout the lifetime of an individual. Attributable to these advantages, the application of Fingerprint biometric is increasingly encouraged by various commercial as well as government organizations. Fingerprint feature detection is to automatically and reliably extract minutiae from the input Fingerprint images. However, the performance of a minutiae extraction algorithm relies heavily on the quality of the input Fingerprint images. In order to ensure that the performance of an Fingerprint authentication system to be robust, it is essential to preprocessing Fingerprint image. This thesis describes steps involved during Fingerprint preprocessing, which improves the clarity of ridge and bifurcation structures of input Fingerprint images. After preprocessing minutiae are extracted and stored in database. Further an online Fingerprint authentication system is implemented in which elementary indexing strat- egy is used. Indexing Fingerprint data is done to identify and retrieve a small subset of candidate data from the database of Fingerprint data of individuals. Experimental work show that incorporating the online system, preprocessing algorithm, matching algorithm improves the overall response time

Improving patient safety, health data accuracy, and remote self-management of health through the establishment of a biometric-based global UHID

Healthcare systems globally continue to face challenges surrounding patient identification. Consequences of misidentification include incomplete and inaccurate electronic patient health records potentially jeopardizing patients\u27 safety, a significant amount of cases of medical fraud because of inadequate identification mechanisms, and difficulties affiliated with the value of remote health self-management application data being aggregated accurately into the user\u27s Electronic Health Record (EHR). We introduce a new technique of user identification in healthcare capable of establishing a global identifier. Our research has developed algorithms capable of establishing a Unique Health Identifier (UHID) based on the user\u27s fingerprint biometric, with the utilization of facial-recognition as a secondary validation step before health records can be accessed. Biometric captures are completed using standard smartphones and Web cameras in a touchless method. We present a series of experiments to demonstrate the formation of an accurate, consistent, and scalable UHID. We hope our solution will aid in the reduction of complexities associated with user misidentification in healthcare resulting in lowering costs, enhancing population health monitoring, and improving patient-safety

Security analysis of a fingerprint-secured USB drive

In response to user demands for mobile data security and maximum ease of use, fingerprint-secured mobile storage devices have been increasingly available for purchase. A fingerprint-secured Universal Serial Bus (USB) drive looks like a regular USB drive, except that it has an integrated optical scanner. When a fingerprint-secured USB drive is plugged into a computer running Windows, a program on this drive will run automatically to ask for fingerprint authentication. (When the program runs the very first time, it will ask for fingerprint enrollment). After a successful fingerprint authentication, a new private drive (for example, drive G:) will appear and data stored on the private drive can be accessed. This private drive will not appear if the fingerprint authentication fails. This thesis studies the security of a representative fingerprint-secured USB drive referred to by the pseudonym AliceDrive. Our results are two fold. First, through black-box reverse engineering and manipulation of binary code in a DLL, we bypassed AliceDrive’s fingerprint authentication and accessed the private drive without actually presenting a valid fingerprint. Our attack is a class attack in that the modified DLL can be distributed to any naive user to bypass AliceDevice’s fingerprint authentication. Second, in our security analysis of AliceDrive, we recovered fingerprint reference templates from memory, which may make AliceDrive worse than a regular USB drive: when Alice loses her fingerprint-secured USB drive, she does not only lose her data, she also loses her fingerprints, which are difficult to recover as Alice’s fingerprints do not change much over a long period of time. In this thesis, we also explore details in integrating fuzzy vault schemes to enhance the security of AliceDrive

Minutiae Based Thermal Human Face Recognition using Label Connected Component Algorithm

In this paper, a thermal infra red face recognition system for human identification and verification using blood perfusion data and back propagation feed forward neural network is proposed. The system consists of three steps. At the very first step face region is cropped from the colour 24-bit input images. Secondly face features are extracted from the croped region, which will be taken as the input of the back propagation feed forward neural network in the third step and classification and recognition is carried out. The proposed approaches are tested on a number of human thermal infra red face images created at our own laboratory. Experimental results reveal the higher degree performanceComment: 7 pages, Conference. arXiv admin note: substantial text overlap with arXiv:1309.1000, arXiv:1309.0999, arXiv:1309.100