Curved Gabor Filters for Fingerprint Image Enhancement

Gabor filters play an important role in many application areas for the enhancement of various types of images and the extraction of Gabor features. For the purpose of enhancing curved structures in noisy images, we introduce curved Gabor filters which locally adapt their shape to the direction of flow. These curved Gabor filters enable the choice of filter parameters which increase the smoothing power without creating artifacts in the enhanced image. In this paper, curved Gabor filters are applied to the curved ridge and valley structure of low-quality fingerprint images. First, we combine two orientation field estimation methods in order to obtain a more robust estimation for very noisy images. Next, curved regions are constructed by following the respective local orientation and they are used for estimating the local ridge frequency. Lastly, curved Gabor filters are defined based on curved regions and they are applied for the enhancement of low-quality fingerprint images. Experimental results on the FVC2004 databases show improvements of this approach in comparison to state-of-the-art enhancement methods

A DoG based Approach for Fingerprint Image Enhancement

Fingerprints have been the most accepted tool for personal identification since many decades. It is also an invaluable tool for law enforcement and forensics for over a century, motivating the research in Automated fingerprint-based identification, an application of biometric system. The matching or identification accuracy using fingerprints has been shown to be very high. The theory on the uniqueness of fingerprint minutiae leads to the steps in studying the statistics of extracting the minutiae features reliably. Fingerprint images obtained through various sources are rarely of perfect quality. They may be degraded or noisy due to variations in skin or poor scanning technique or due to poor impression condition. Hence enhancement techniques are applied on fingerprint images prior to the minutiae point extraction to get sure of less spurious and more accurate minutiae points from the reliable minutiae location. This thesis focuses on fingerprint image enhancement techniques through histogram equalization applied locally on the degraded image. The proposed work is based on the Laplacian pyramid framework that decomposes the input image into a number of band-pass images to improve the local contrast, as well as the local edge information. The resultant image is passed through the regular methodologies of fingerprint, like ridge orientation, ridge frequency calculation, filtering, binarization and finally the morphological operation thinning. Experiments using different texture of images are conducted to enhance the images and to show a comparative result in terms of number of minutiae extracted from them along with the spurious and actual number existing in each enhanced image. Experimental results out performs well to overcome the counterpart of enhancement technique

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

A technique to improve ridge flows of fingerprint orientation fields estimation

An accurate estimated fingerprint orientation fields is a significant step for detection of singular points. Gradient-based methods are frequently used for estimating orientation fields but those methods are sensitive to noise. Fingerprints that perfect quality are seldom. They may be corrupted and degraded due to impression conditions or variations on skin. Enhancement of ridge flows improved the structure of orientation fields and hence increased the number of true singular points thereby conducting the overall performance of the classification process. In this paper, we provided discussion on the technique and implementation to improve local ridge flows of fingerprint orientation fields. That main technique have four steps; firstly, fingerprint segmentation; secondly, identification of noise areas and marking; thirdly, estimation of fingerprint orientation fields, and finally, enhancement of ridge flows using minimum variance of the cross centre block direction in squared gradients. A standard fingerprint database is used for testing of proposed technique to verify the tier of effectivity of algorithm. The experimental results suggest that our enhanced algorithm achieves visibly better ridge flows compare to other methods