71 research outputs found
Agent-Based Image Iris Segmentation and MultipleViews Boundary Refining
No full textThe paper presents two different methods to deal with the problem of iris segmentation: an agent-based method capable to localize the center of the pupil and a method to process the iris boundaries by a multiple views approach. In the first method, an agent corresponds to the coordinates of a specific point of analysis in the input image. A population of agents is deployed in the input image, then, each agent collects local information concerning the intensity patterns visible in its region of interest. By iterations, an agent changes its position accordingly to the local properties, moving towards the estimation of the pupil center. If no available information is present in its region of interest, the agent will move itself along a random walk. After few iterations, the population tends to spread and then concentrate in the inner portion of the pupil. Once the center of the pupil has been located, the inner and outer iris boundaries are refined by an approach based on multiple views analysis. This method starts with a set of points that can be considered as an approximation of the pupil center. For each point, a detailed estimation of the iris boundaries is computed, and the final description of the iris boundaries is obtained by merging all the obtained descriptions. The two methods were tested using CASIA v.3 and UBIRIS v.2 images. Experiments show that the proposed approaches are feasible, also in eye images taken in noisy or non-ideal conditions, achieving a total error segmentation accuracy up to 97%
ALL-IDB : the acute lymphoblastic leukemia image database for image processing
No full textThe visual analysis of peripheral blood samples is an important test in the procedures for the diagnosis of leukemia. Automated systems based on artificial vision methods can speed up this operation and increase the accuracy and homogeneity of the response also in telemedicine applications. Unfortunately, there are not available public image datasets to test and compare such algorithms. In this paper, we propose a new public dataset of blood samples, specifically designed for the evaluation and the comparison of algorithms for segmentation and classification. For each image in the dataset, the classification of the cells is given, as well as a specific set of figures of merits to fairly compare the performances of different algorithms. This initiative aims to offer a new test tool to the image processing and pattern matching communities, direct to stimulating new studies in this important field of research
Neural-based iterative approach for iris detection in iris recognition systems
No full textThe detection of the iris boundaries is considered in the literature as one of the most critical steps in the identification task of the iris recognition systems. In this paper we present an iterative approach to the detection of the iris center and boundaries by using neural networks. The proposed algorithm starts by an initial random point in the input image, then it processes a set of local image properties in a circular region of interest searching for the peculiar transition patterns of the iris boundaries. A trained neural network processes the parameters associated to the extracted boundaries and it estimates the offsets in the vertical and horizontal axis with respect to the estimated center. The coordinates of the starting point are then updated with the processed offsets. The steps are then iterated for a fixed number of epochs, producing an iterative refinements of the coordinates of the pupils center and its boundaries. Experiments showed that the method is feasible and it can be exploited even in non-ideal operative condition of iris recognition biometric systems
A neural-based minutiae pair identification method for touch-less fingerprint images
No full textContact-based sensors are the traditional devices used to capture fingerprint images in commercial and homeland security applications. Contact-less systems achieve the fingerprint capture by vision systems avoiding that users touch any parts of the biometric device. Typically, the finger is placed in the working area of an optics system coupled with a CCD module. The captured light pattern on the finger is related to the real ridges and valleys of the user fingertip, but the obtained images present important differences from the traditional fingerprint images. These differences are related to multiple factors such as light, focus, blur, and the color of the skin. Unfortunately, the identity comparison methods designed for fingerprint images captured with touch-based sensors do not obtain sufficient accuracy when are directly applied to touch-less images. Recent works show that multiple views analysis and 3D reconstruction can enhance the final biometric accuracy of such systems. In this paper we propose a new method for the identification of the minutiae pairs between two views of the same finger, an important step in the 3D reconstruction of the fingerprint template. The method is divisible in the sequent tasks: first, an image preprocessing step is performed; second, a set of candidate minutiae pairs is selected in the two images, then a list of candidate pairs is created; last, a set of local features centered around the two minutiae is produced and processed by a classifier based on a trained neural network. The output of the system is the list of the minutiae pairs present in the input images. Experiments show that the method is feasible and accurate in different light conditions and setup configurations
Neural-based quality measurement of fingerprint images in contactless biometric systems
No full textTraditional fingerprint biometric systems capture the user fingerprint images by a contact-based sensor. Differently, contactless systems aim to capture the fingerprint images by an approach based on a vision system without the need of any contact of the user with the sensor. The user finger is placed in front of a special CCD-based system that captures the pattern of ridges and valleys of the fingertips. This approach is less constrained by the point of view of the user, but it requires much more capability of the system to deal with the focus of the moving target, the illumination problems and the complexity of the background in the captured image. During the acquisition procedure, the quality of each frame must be carefully evaluated in order to extract only the correct frames with valuable biometric information from the sequence. In this paper, we present a neural-based approach for the quality estimation of the contactless fingertips images. The application of the neural classification models allowed for a relevant reduction of the computational complexity permitting the application in realtime. Experimental results show that the proposed method has an adequate accuracy, and it can capture fingerprints at a distance up to 0.2 meters
Touchless fingerprint biometrics
No full textOffering the first comprehensive analysis of touchless fingerprint-recognition technologies, Touchless Fingerprint Biometrics gives an overview of the state of the art and describes relevant industrial applications. It also presents new techniques to efficiently and effectively implement advanced solutions based on touchless fingerprinting.
The most accurate current biometric technologies in touch-based fingerprint-recognition systems require a relatively high level of user cooperation to acquire samples of the concerned biometric trait. With the potential for reduced constraints, reduced hardware costs, quicker acquisition time, wider usability, and increased user acceptability, this book argues for the potential superiority of touchless biometrics over touch-based methods.
The book considers current problems in developing high-accuracy touchless recognition technology. It discusses factors such as shadows, reflections, complex backgrounds, distortions due to perspective effects, uncontrolled finger placement, inconstant resolution of the ridge pattern, and reconstruction and processing of three-dimensional models. The last section suggests what future work can be done to increase accuracy in touchless systems, such as intensive studies on extraction and matching methods and three-dimensional analytical capabilities within systems.
In a world where usability and mobility have increasing relevance, Touchless Fingerprint Biometrics demonstrates that touchless technologies are also part of the future. A presentation of the state of the art, it introduces you to the field and its immediate future directions
Two-view contactless fingerprint acquisition systems : a case study for clay artworks
No full textThe detection of latent fingerprints can be a great aid in determining the authenticity of ancient artworks. In fact, a commonly used technique for the authentication of artworks consists in the comparison of fingerprints present on the surface of an artifact with other available latent fingerprints of an artist. This kind of analysis is particularly important for the authentication of clay artifacts. The clay, in fact, is often modeled barehanded, causing a great number of fingerprints left on the surface. In many cases, the artworks are very valuable or fragile and the latent fingerprints cannot be acquired using classical forensic methods. For this reason, contactless acquisition techniques have been proposed. Most of these techniques are based on the use of a single camera. In single-view acquisition systems, however, it can be difficult to properly estimate the size of the captured area, the obtained images can suffer from problems related to perspective distortions, and a calibration task cannot be performed in all the cases. In this paper, we propose a two-view acquisition system able to capture the latent fingerprints left on a clay artwork, and to compute their three-dimensional metric reconstruction. The obtained results show that the proposed approach is feasible and the reconstructed models provide a metric, view-independent, and less-distorted reconstruction of the fingerprint. In particular, we describe the application of the proposed method on a specific clay artwork associated by experts to the famous sculptor Antonio Canova (Italy, 1757-1822)
Biometric privacy protection : guidelines and technologies
No full textCompared with traditional techniques used to establish the identity of a person, biometric systems offer a greater confidence level that the authenticated individual is not impersonated by someone else. However, it is necessary to consider different privacy and security aspects in order to prevent possible thefts and misuses of biometric data. The effective protection of the privacy must encompass different aspects, such as the perceived and real risks pertaining to the users, the specificity of the application, the adoption of correct policies, and data protection methods as well. This chapter focuses on the most important privacy issues related to the use of biometrics, it presents actual guidelines for the implementation of privacy-protective biometric systems, and proposes a discussion of the methods for the protection of biometric data
Virtual environment for 3-D synthetic fingerprints
No full textContactless biometric recognition performed using three-dimensional fingerprint models has the advantages of reducing problems related to the deformations of the skin, dust on the sensor, and spoofing of latent fingerprints. Moreover, the fingerprint area usable for the recognition is wider than the one captured by traditional contact-based acquisition techniques
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