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Image enhancement is a common pre-processing step before the extraction of biometric features from a fingerprint sample. This can be essential especially for images of low image quality. An ideal fingerprint image enhancement should intend to improve the end-to-end biometric performance, i.e. the performance achieved on biometric features extracted from enhanced fingerprint samples. We use a model...
In scenarios that are ambitious to protect sensitive data in compliance with privacy regulations, conventional score normalization utilizing large proportions of speaker cohort data is not feasible for existing technology, since the entire cohort data would need to be stored on each mobile device. Hence, in this work we motivate score normalization utilizing deep neural networks. Considering unconstrained...
In this paper an advanced iris-biometric comparator is presented. In the proposed scheme an analysis of bit-error patterns produced by Hamming distance-based iris-code comparisons is performed. The lengths of sequences of horizontal consecutive mis-matching bits are measured and a frequency distribution is estimated. The difference of the extracted frequency distribution to that of an average genuine...
The performance of a biometric system gets affected by various types of errors such as systematic errors, random errors, etc. These kinds of errors usually occur due to the natural variations in the biometric traits of subjects, different testing, and comparison methodologies. Neither of these errors can be easily quantifiable by mathematical formulas. This behavior introduces an uncertainty in the...
The proliferation of cameras and personal devices results in a wide variability of imaging conditions, producing large intra-class variations and a significant performance drop when images from heterogeneous environments are compared. However, many applications require to deal with data from different sources regularly, thus needing to overcome these interoperability problems. Here, we employ fusion...
Presentation attacks (or spoofing) on finger-vein biometric capture devices are gaining increased attention because of their wider deployment in multiple secure applications. In this work. we propose a novel method for fingervein Presentation Attack Detection (PAD) by exploring the transfer learning ability of Deep Convolutional Neural Network (CNN). To this extent, we have considered the pre-trained...
Reliability and accuracy of the features extracted from fingerprints are essential for the performance of any fingerprint comparison algorithm. Image Enhancement as a pre-processing step allows to extract features more accurately by enhancing the quality of the fingerprint signal. This work proposes to use De-Convolutional Auto-Encoders for fingerprint image enhancement. Its performance is compared...
Biometrics identification systems containing a largescale database have been gaining increasing attention. In order to speed up searching in a large-scale fingerprint database, fingerprint indexing algorithm has been studied and introduced into biometrics identification system. One critical component of a fingerprint indexing algorithm is the feature extraction method. Majority of researchers developed...
The performance limitations of the state-of-the-art methods for fingerprint presentation attack detection motivate the application of the Optical Coherence Tomography as the scanning technology capable of capturing all the information necessary for both the fingerprint identification and the presentation attack detection. The previous research has evidenced the need for a reliable technique for assessing...
Ear classification refers to the process by which an input ear image is assigned to one of several pre-defined classes based on a set of features extracted from the image. In the context of large-scale ear identification, where the input probe image has to be compared against a large set of gallery images in order to locate a matching identity, classification can be used to restrict the matching process...
Due to the uniqueness and permanence properties of the biometric fingerprint characteristic, large scale in border control and governmental applications such as the Visa Information System (VIS) in Europe, US-VISIT / IDENT system in the USA and the Aadhaar project in India are based on fingerprint recognition. These systems generally contain millions of fingerprint samples. In order to improve the...
Promising results have been obtained when using Hidden Markov Models for accelerometer-based biometric gait recognition. So far, the used testing data contains only walking straight on a flat floor, which is not a realistic scenario. This paper shows the results when using a more realistic data set containing walking around corners, upstairs and downstairs etc. It is analyzed to which extent the biometric...
In this paper, we describe the GUC100 multi-scanner fingerprint database that has been created for independent and in-house (semi-public) performance and interoperability testing of third party algorithms. The GUC100 was collected by using six different fingerprint scanners (TST, L-1, Cross Match, PreciseBiometrics, Lumidigm and Sagem). Over several months fingerprint images of all 10 fingers from...
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