Relevant bibliographies by topics / Fingerprints

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Fingerprints'

Author: Grafiati
Published: 4 June 2021
Last updated: 30 July 2024

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Journal articles on the topic "Fingerprints"

1

Varmarken, Janus, Jad Al Aaraj, Rahmadi Trimananda, and Athina Markopoulou. "FingerprinTV: Fingerprinting Smart TV Apps." Proceedings on Privacy Enhancing Technologies 2022, no. 3 (July 2022): 606–29. http://dx.doi.org/10.56553/popets-2022-0088.

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This paper proposes FingerprinTV, a fully automated methodology for extracting fingerprints from the network traffic of smart TV apps and assessing their performance. FingerprinTV (1) installs, repeatedly launches, and collects network traffic from smart TV apps; (2) extracts three different types of network fingerprints for each app, i.e., domain-based fingerprints (DBF), packet-pair-based fingerprints (PBF), and TLS-based fingerprints (TBF); and (3) analyzes the extracted fingerprints in terms of their prevalence, distinctiveness, and sizes. From applying FingerprinTV to the top-1000 apps of the three most popular smart TV platforms, we find that smart TV app network fingerprinting is feasible and effective: even the least prevalent type of fingerprint manifests itself in at least 68% of apps of each platform, and up to 89% of fingerprints uniquely identify a specific app when two fingerprinting techniques are used together. By analyzing apps that exhibit identical fingerprints, we find that these apps often stem from the same developer or “no code” app generation toolkit. Furthermore, we show that many apps that are present on all three platforms exhibit platformspecific fingerprints.
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Poorani Thiruvengadasamy Rajendran, Ramya Chinniah, and Ramya Manohar. "Thermal Manipulation of Latent Fingerprints using Cyanoacrylate Fuming with Rare Earth Material." Journal of Advanced Research in Fluid Mechanics and Thermal Sciences 110, no. 2 (December 15, 2023): 1–13. http://dx.doi.org/10.37934/arfmts.110.2.113.

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Latent fingerprints are used to identify specific individuals during a forensic investigation. Fingerprints provide a clear and concise means of identifying an individual and their history. Traditional techniques for fingerprint analysis include metal powder and magnetic powder dusting; fluorescent dye staining; iodine fuming; vacuum metal deposition and many more. There are several issues with the conventional technologies now in use, including their sensitivity, contrast, background interference, toxicity and complexity. In this study, the cyanoacrylate fuming technique was combined with enhancing agents such as metallic and rare earth minerals to increase the visibility of latent fingerprints in a quick and easy approach. The vapours of ethyl 2-cyanoacrylate react with the fingerprint's natural compounds, increasing the contrast of the impression. Therefore, fingerprints are visible to the human eye after being treated with cyanoacrylate. Rare earth europium oxide was also used to improve the fingerprints. The fingerprints were sprayed with a mixture of europium oxide. Images of the fingerprint samples were taken and they were evaluated. Cyanoacrylate treatment and europium oxide deposition both enhanced the visibility of fingerprints. In contrast to the cyanoacrylate-treated sample, the europium oxide-deposited specimen stood out more clearly. Hence, rare earth elements improved the visibility of hidden fingerprints.
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Cubeta, M. A., B. R. Cody, Y. Kohli, and L. M. Kohn. "Clonality in Sclerotinia sclerotiorum on Infected Cabbage in Eastern North Carolina." Phytopathology® 87, no. 10 (October 1997): 1000–1004. http://dx.doi.org/10.1094/phyto.1997.87.10.1000.

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Eighty-four isolates of Sclerotinia sclerotiorum from four cabbage production fields in North Carolina and 16 isolates from an experimental cabbage field plot in Louisiana were DNA-fingerprinted and tested for mycelial compatibility. In a comparison with 594 unique DNA fingerprints of S. sclerotiorum from Canadian canola, no fingerprints were shared among Canadian, North Carolina, and Louisiana populations. DNA fingerprints from the North Carolina sample were distinctive from those of the Canadian and Louisiana samples, with significantly more hybridizing fragments in the 7.7- to 18-kilobase range. Forty-one mycelial compatibility groups (MCGs) and 50 unique DNA fingerprints were identified from the North Carolina sample. Three MCGs and three fingerprints were identified from the Louisiana sample. From the North Carolina sample, 32 MCGs were each associated with a unique fingerprint; of these, there were 11 clones (i.e., cases in which two or more isolates belonged to the same MCG and shared the same DNA fingerprint). Six clones sampled from two or more fields represented approximately 29% of the total sample (24 of 84 isolates), with six clones recovered from fields 75 km apart. There were 10 cases in which one MCG was associated with more than one DNA fingerprint and two cases in which one DNA fingerprint was associated with more than one MCG. The small sample from Louisiana was strictly clonal. The North Carolina sample had a clonal component, but deviated from one-to-one association of MCG with DNA fingerprint to an extent consistent with more recombination or transposition than the other two populations sampled.
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Mao, Wenhui, Yadong Zhao, Petro Pavlenko, Yihan Chen, and Xuezhi Shi. "Innovative Solutions for Worn Fingerprints: A Comparative Analysis of Traditional Fingerprint Impression and 3D Printing." Sensors 24, no. 8 (April 20, 2024): 2627. http://dx.doi.org/10.3390/s24082627.

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Fingerprint recognition systems have achieved widespread integration into various technological devices, including cell phones, computers, door locks, and time attendance machines. Nevertheless, individuals with worn fingerprints encounter challenges when attempting to unlock original fingerprint systems, which results in disruptions to their daily activities. This study explores two distinct methods for fingerprint backup: traditional fingerprint impression and 3D printing technologies. Unlocking tests were conducted on commonly available optical fingerprint lock-equipped cell phones to assess the efficacy of these methods, particularly in unlocking with worn fingerprints. The research findings indicated that the traditional fingerprint impression method exhibited high fidelity in reproducing fingerprint patterns, achieving an impressive unlocking success rate of 97.8% for imprinting unworn fingerprints. However, when dealing with worn fingerprints, the traditional fingerprint impression technique showed a reduced unlocking success rate, progressively decreasing with increasing degrees of finger wear. In contrast, 3D-printed backup fingerprints, with image processing and optimization of ridge height, mitigated the impact of fingerprint wear on the unlocking capability, resulting in an unlocking success rate of 84.4% or higher. Thus, the utilization of 3D printing technology proves advantageous for individuals with severely worn or incomplete fingerprints, providing a viable solution for unforeseen circumstances.
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Lee, Youn Kyu, Jongwook Jeong, and Dongwoo Kang. "An Effective Orchestration for Fingerprint Presentation Attack Detection." Electronics 11, no. 16 (August 11, 2022): 2515. http://dx.doi.org/10.3390/electronics11162515.

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Fingerprint presentation attack detection has become significant due to a wide-spread usage of fingerprint authentication systems. Well-replicated fingerprints easily spoof the authentication systems because their captured images do not differ from those of genuine fingerprints in general. While a number of techniques have focused on fingerprint presentation attack detection, they suffer from inaccuracy in determining the liveness of fingerprints and performance degradation on unknown types of fingerprints. To address existing limitations, we present a robust fingerprint presentation attack detection method that orchestrates different types of neural networks by incorporating a triangular normalization method. Our method has been evaluated on a public benchmark comprising 13,000 images with five different fake materials. The evaluation exhibited our method’s higher accuracy in determining the liveness of fingerprints as well as better generalization performance on different types of fingerprints compared to existing techniques.
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Yoon, Soweon, and Anil K. Jain. "Longitudinal study of fingerprint recognition." Proceedings of the National Academy of Sciences 112, no. 28 (June 29, 2015): 8555–60. http://dx.doi.org/10.1073/pnas.1410272112.

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Human identification by fingerprints is based on the fundamental premise that ridge patterns from distinct fingers are different (uniqueness) and a fingerprint pattern does not change over time (persistence). Although the uniqueness of fingerprints has been investigated by developing statistical models to estimate the probability of error in comparing two random samples of fingerprints, the persistence of fingerprints has remained a general belief based on only a few case studies. In this study, fingerprint match (similarity) scores are analyzed by multilevel statistical models with covariates such as time interval between two fingerprints in comparison, subject’s age, and fingerprint image quality. Longitudinal fingerprint records of 15,597 subjects are sampled from an operational fingerprint database such that each individual has at least five 10-print records over a minimum time span of 5 y. In regard to the persistence of fingerprints, the longitudinal analysis on a single (right index) finger demonstrates that (i) genuine match scores tend to significantly decrease when time interval between two fingerprints in comparison increases, whereas the change in impostor match scores is negligible; and (ii) fingerprint recognition accuracy at operational settings, nevertheless, tends to be stable as the time interval increases up to 12 y, the maximum time span in the dataset. However, the uncertainty of temporal stability of fingerprint recognition accuracy becomes substantially large if either of the two fingerprints being compared is of poor quality. The conclusions drawn from 10-finger fusion analysis coincide with the conclusions from single-finger analysis.
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Bercelin, Rose Mary W., N. Subbulakshmi, and Tofflin R. Bini. "Fingerprint Combination of Privacy Preservation is Improved by Delaunay Triangulation Method." Applied Mechanics and Materials 573 (June 2014): 437–41. http://dx.doi.org/10.4028/www.scientific.net/amm.573.437.

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Fingerprints are graphical ridge and valley patterns on the tips of human fingers. Owing to their uniqueness and permanence, the use of fingerprints is considered to be one of the most reliable methods of personal verification. Fingerprints are today among the most popularly used biometric modalities in automatic verification systems. At the same time, Protecting the privacy of Fingerprint is an important one, here a novel system propose protecting fingerprint by combining two different fingerprints. In the enrolment stage, fingerprints will be captured from two different fingers. Minutiae positions are extracted from one fingerprint (its the detailed pattern of the fingerprint). The orientation, (it indicates the flow of ridges and valleys) from other fingerprint, and the reference points are calculated from both the two fingerprints. Extracted combined minutiae templates are stored into database. Here A Delaunay Triangulation indexing scheme has been designed for protecting biometric template and non-invertible template are calculated for verifies the authorized person. By using the Delaunay triangulation method fingerprint privacy has to be improved.
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Secundo, Lavi, Kobi Snitz, Kineret Weissler, Liron Pinchover, Yehuda Shoenfeld, Ron Loewenthal, Nancy Agmon-Levin, et al. "Individual olfactory perception reveals meaningful nonolfactory genetic information." Proceedings of the National Academy of Sciences 112, no. 28 (June 22, 2015): 8750–55. http://dx.doi.org/10.1073/pnas.1424826112.

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Each person expresses a potentially unique subset of ∼400 different olfactory receptor subtypes. Given that the receptors we express partially determine the odors we smell, it follows that each person may have a unique nose; to capture this, we devised a sensitive test of olfactory perception we termed the “olfactory fingerprint.” Olfactory fingerprints relied on matrices of perceived odorant similarity derived from descriptors applied to the odorants. We initially fingerprinted 89 individuals using 28 odors and 54 descriptors. We found that each person had a unique olfactory fingerprint (P < 10−10), which was odor specific but descriptor independent. We could identify individuals from this pool using randomly selected sets of 7 odors and 11 descriptors alone. Extrapolating from this data, we determined that using 34 odors and 35 descriptors we could individually identify each of the 7 billion people on earth. Olfactory perception, however, fluctuates over time, calling into question our proposed perceptual readout of presumably stable genetic makeup. To test whether fingerprints remain informative despite this temporal fluctuation, building on the linkage between olfactory receptors and HLA, we hypothesized that olfactory perception may relate to HLA. We obtained olfactory fingerprints and HLA typing for 130 individuals, and found that olfactory fingerprint matching using only four odorants was significantly related to HLA matching (P < 10−4), such that olfactory fingerprints can save 32% of HLA tests in a population screen (P < 10−6). In conclusion, a precise measure of olfactory perception reveals meaningful nonolfactory genetic information.
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Lakshmi, M. Sri, S. Sai Jayanth, Jayanth ., and Mahendra . "BIO-METRIC IDENTITY BY CONTACTLESS AND CONTACT-BASED MATCHING WITH CONSERVATIVE FINGERPRINT IMAGES." International Journal of Engineering Applied Sciences and Technology 6, no. 10 (February 1, 2022): 261–67. http://dx.doi.org/10.33564/ijeast.2022.v06i10.034.

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To defend state borders and backup egovernance programs, enormous databases of contactbased fingerprints have been generated. Contactless fingerprints sensors are becoming more popular because they provide a greater cleanliness, security and accuracy. The existing method have capacity to match contactless 2D fingerprints with legacy contact-based fingerprint databases is critical to the adoption and success of such contactless fingerprint technologies. This research looks at the issue and proposes a novel method for reliably matching fingerprint scans. The project consists of a robust thin-plate spline model that was a incorporated for the correction of deformations to address contact based and contactless sensor interoperability problems. The robust thin-plate spline (RTPS) is a new type of spline that can be more correctly describe elastic fingerprint deformations. The RTPS-based generalized fingerprint deformation correction model (DCM) is presented to correct such deformations on contact-based fingerprints. When DCM is used, essential minutiae element on both contactless and contact-based fingerprints are aligned accurately. Incorporating minutiae-related ridges into such cross-matching performance will be researched further. In addition, we create a new database of 1800 contactless 2D fingerprints and the associated contactbased fingerprints obtained from 300 clients, which is made public ally available for further research. Using two public ally available databases, the experimental results provided in this work confirm our approach and produce outperforming results for matching contactless 2D and contact-based fingerprint photos. Automated detection and correction of perspective distortion in contactless fingerprint images is expected to reduce the error rates. This work incorporates more robust core detection algorithms and powerful match strategy.
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Kirfel, Alexander, Tobias Scheer, Norbert Jung, and Christoph Busch. "Robust Identification and Segmentation of the Outer Skin Layers in Volumetric Fingerprint Data." Sensors 22, no. 21 (October 27, 2022): 8229. http://dx.doi.org/10.3390/s22218229.

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Despite the long history of fingerprint biometrics and its use to authenticate individuals, there are still some unsolved challenges with fingerprint acquisition and presentation attack detection (PAD). Currently available commercial fingerprint capture devices struggle with non-ideal skin conditions, including soft skin in infants. They are also susceptible to presentation attacks, which limits their applicability in unsupervised scenarios such as border control. Optical coherence tomography (OCT) could be a promising solution to these problems. In this work, we propose a digital signal processing chain for segmenting two complementary fingerprints from the same OCT fingertip scan: One fingerprint is captured as usual from the epidermis (“outer fingerprint”), whereas the other is taken from inside the skin, at the junction between the epidermis and the underlying dermis (“inner fingerprint”). The resulting 3D fingerprints are then converted to a conventional 2D grayscale representation from which minutiae points can be extracted using existing methods. Our approach is device-independent and has been proven to work with two different time domain OCT scanners. Using efficient GPGPU computing, it took less than a second to process an entire gigabyte of OCT data. To validate the results, we captured OCT fingerprints of 130 individual fingers and compared them with conventional 2D fingerprints of the same fingers. We found that both the outer and inner OCT fingerprints were backward compatible with conventional 2D fingerprints, with the inner fingerprint generally being less damaged and, therefore, more reliable.
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Dissertations / Theses on the topic "Fingerprints"

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Dimitrov, Emanuil. "Fingerprints recognition." Thesis, Växjö University, School of Mathematics and Systems Engineering, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:vxu:diva-5522.

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Nowadays biometric identification is used in a variety of applications-administration, business and even home. Although there are a lot of biometric identifiers, fingerprints are the most widely spread due to their acceptance from the people and the cheap price of the hardware equipment. Fingerprint recognition is a complex image recognition problem and includes algorithms and procedures for image enhancement and binarization, extracting and matching features and sometimes classification. In this work the main approaches in the research area are discussed, demonstrated and tested in a sample application. The demonstration software application is developed by using Verifinger SDK and Microsoft Visual Studio platform. The fingerprint sensor for testing the application is AuthenTec AES2501.

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Larsen, Vegard Andreas. "Combining Audio Fingerprints." Thesis, Norwegian University of Science and Technology, Department of Computer and Information Science, 2008. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-8869.

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Large music collections are now more common than ever before. Yet, search technology for music is still in its infancy. Audio fingerprinting is one method that allows searching for music. In this thesis several audio fingerprinting solutions are combined into a single solution to determine if such a combination can yield better results than any of the solutions can separately. The solution is used to find duplicate music files in a personal collection. The results show that applying the weighted root-mean square (WRMS) to the problem most effectively ranked the results in a satisfying manner. It was notably better than the other approaches tried. The WRMS produced 61% more correct matches than the original FDMF solution, and 49% more correct matches than libFooID.

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Deng, Huimin. "Robust minutia-based fingerprint verification." Click to view the E-thesis via HKUTO, 2006. http://sunzi.lib.hku.hk/hkuto/record/B37036427.

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Llewelyn, Stephanie Jane. "Statistical modelling of fingerprints." Thesis, University of Sheffield, 2014. http://etheses.whiterose.ac.uk/7722/.

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It is believed that fingerprints are determined in embryonic development. Unlike other personal characteristics the fingerprint appears to be a result of a random process. For example fingerprints of identical twins (whose DNA is identical) are distinct, and extensive studies have found little evidence of a genetic relationship in terms of types of fingerprint, certainly at the small scale. At a larger scale the pattern of ridges on fingerprints can be categorised as belonging to one of five basic forms: loops (left and right), whorls, arches and tented arches. The population frequencies of these types show little variation with ethnicity and a list of the types occurring on the ten digits can be used as an initial basis for identification of individuals. However, such a system would not uniquely identify an individual although the frequency of certain combinations could be extremely small. At a smaller scale various minutiae or singularities can be observed in a fingerprint. These include ridge endings and bifurcations, amongst others. Typical fingerprints have several hundred of these as well as two key points (with the exception of a simple arch) referred to as the core and delta, which are focal points of the overall pattern of ridges. Modern identification systems are based upon ridge endings and bifurcations, not least because they are the easiest to determine automatically from image analysis. The configuration of these minutiae is unique to the individual. This research explores the relationship between the locations of minutiae to determine if they can be modelled using a statistical process. In addition, since the approach is based on how fingerprints can be examined in a forensic situation an algorithm is created and tested which allows the strength of a match between a fingermark left at a crime and a fingerprint from a known suspect to be calculated. Currently the result of matching a fingermark and fingerprint is expressed as a categorical value of; match, no match or inconclusive. The method in this research allows this to be expressed as a numerical value allowing for a wider and more flexible use of fingerprint evidence.
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Vrábľová, Žofia. "Pokročilé generování artefaktů falzifikátů do syntetických otisků prstů." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2021. http://www.nusl.cz/ntk/nusl-445551.

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The goal of this thesis is to extend the application for spoof effects generation into synthetic fingerprints with the possibility of generation of two new spoof effects together with annotations of generated damages. Spoof effects chosen for this thesis are areas with lower clarity and defects in spoof material. Those effects were analyzed, methods to generate those effects were designed and then implemented. According to testing, generation of two new added spoof effects led to reduction in quality of fingerprint images, as well as the value of the similarity score determined during identification. In comparison with the original solution, the quality of the fingerprints decreased more in the extended solution, the similarity score in the generation of separate spoof effect decreased overall approximately equally.
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Kuecken, Michael U. "On the formation of fingerprints." Diss., The University of Arizona, 2004. http://hdl.handle.net/10150/290075.

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The fingerprint pattern (epidermal ridge pattern) becomes established at about the 10th to 16th week of pregnancy, when the lowest layer of the epidermis, the basal layer, becomes undulated. The pattern established by these undulations becomes visible on the skin surface in subsequent weeks of pregnancy. We argue that the undulation process is initiated by buckling of the basal layer. The necessary compressive stress is generated by differential growth. The instability is investigated using the classic von Karman equations for curved surfaces. The analysis reveals that ridges (rolls) are the most common pattern type and that the local ridge direction of the pattern is perpendicular to the direction of largest stress. For certain parameter regimes dot patterns (hexagons) are a stable solution of the equations. Such dot patterns are, in fact, observed on the palms of certain marsupials. The stress in the basal layer is induced by two mechanisms. First, the basal layer expands faster than the other skin structures. Such expansion is resisted at the major flexion creases and the nail furrow. Second, there is a change in fingertip geometry at the time of pattern generation that provides a different source of growth stress. The combination of the two processes predicts the correct sequence of pattern spread over the fingertip. It also explains the observation that fingerprint configurations are related to the fingertip geometry at the time of ridge formation. Computer simulations for the most important configurations exhibit many features of actual fingerprints and suggest directions for future work.
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Sandström, Marie. "Liveness Detection in Fingerprint Recognition Systems." Thesis, Linköping University, Department of Electrical Engineering, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-2397.

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Biometrics deals with identifying individuals with help of their biological data. Fingerprint scanning is the most common method of the biometric methods available today. The security of fingerprint scanners has however been questioned and previous studies have shown that fingerprint scanners can be fooled with artificial fingerprints, i.e. copies of real fingerprints. The fingerprint recognition systems are evolving and this study will discuss the situation of today.

Two approaches have been used to find out how good fingerprint recognition systems are in distinguishing between live fingers and artificial clones. The first approach is a literature study, while the second consists of experiments.

A literature study of liveness detection in fingerprint recognition systems has been performed. A description of different liveness detection methods is presented and discussed. Methods requiring extra hardware use temperature, pulse, blood pressure, electric resistance, etc., and methods using already existent information in the system use skin deformation, pores, perspiration, etc.

The experiments focus on making artificial fingerprints in gelatin from a latent fingerprint. Nine different systems were tested at the CeBIT trade fair in Germany and all were deceived. Three other different systems were put up against more extensive tests with three different subjects. All systems werecircumvented with all subjects'artificial fingerprints, but with varying results. The results are analyzed and discussed, partly with help of the A/R value defined in this report.

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Green, Nathan Alan. "Establishing Public Confidence in the Viability of Fingerprint Biometric Technology." Diss., CLICK HERE for online access, 2005. http://contentdm.lib.byu.edu/ETD/image/etd919.pdf.

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Svoradová, Veronika. "Pokročilé generování projevů poškození do syntetických otisků prstů." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2021. http://www.nusl.cz/ntk/nusl-445560.

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The main goal of this thesis was to design and implement a application that would be able to generate fingerprint damage into a synthetic fingerprint. The application can create fingerprint images damaged by pressure, moisture and skin disease dyshidrosis with different intensity of damage. The application also allows annotation of the generated damage and its export. Selected damages were analyzed before the design was created. A database of fingerprints from five users was created to analyze the damage caused by pressure and moisture. The generated images and the achieved results are tested with VeriFinger and FiQiVi. For testing, 19 sets with fingerprints of different intensity and different type of damage were created. Experiments showed that the quality of the fingerprint decreased the most during the generation of moisture with the highest intensity of damage, where the quality decreased by 61.8 %. This thesis can be used for further research in the field of biometric fingerprint processing.
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Noor, Azad. "A new algorithm for minutiae extraction and matching in fingerprint." Thesis, Brunel University, 2012. http://bura.brunel.ac.uk/handle/2438/7473.

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A novel algorithm for fingerprint template formation and matching in automatic fingerprint recognition has been developed. At present, fingerprint is being considered as the dominant biometric trait among all other biometrics due to its wide range of applications in security and access control. Most of the commercially established systems use singularity point (SP) or ‘core’ point for fingerprint indexing and template formation. The efficiency of these systems heavily relies on the detection of the core and the quality of the image itself. The number of multiple SPs or absence of ‘core’ on the image can cause some anomalies in the formation of the template and may result in high False Acceptance Rate (FAR) or False Rejection Rate (FRR). Also the loss of actual minutiae or appearance of new or spurious minutiae in the scanned image can contribute to the error in the matching process. A more sophisticated algorithm is therefore necessary in the formation and matching of templates in order to achieve low FAR and FRR and to make the identification more accurate. The novel algorithm presented here does not rely on any ‘core’ or SP thus makes the structure invariant with respect to global rotation and translation. Moreover, it does not need orientation of the minutiae points on which most of the established algorithm are based. The matching methodology is based on the local features of each minutiae point such as distances to its nearest neighbours and their internal angle. Using a publicly available fingerprint database, the algorithm has been evaluated and compared with other benchmark algorithms. It has been found that the algorithm has performed better compared to others and has been able to achieve an error equal rate of 3.5%.
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Books on the topic "Fingerprints"

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Galton, Francis. Fingerprints. Buffalo, N.Y: W.S. Hein, 2003.

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Collins, Clarence Gerald. Fingerprint science: How to roll, classify, file, and use fingerprints. Costa Mesa, CA: Custom Pub. Co., 1985.

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Cook, Nancy. Classifying fingerprints. Menlo Park, Calif: Innovative Learning Publications, Addison- Wesley Pub. Co., 1995.

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Galina, Popova, ed. Shakespeare's fingerprints. [Vashon Island, Wash.]: Adonis Editions, 2002.

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Martin, Mistie A. Fingerprint identification errors caused by human error, not fingerprints of the methodology. [San Diego, California]: National University, 2013.

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Norman, Haber Ralph, ed. Challenges to fingerprints. Tucson, AZ: Lawyers & Judges Pub. Co., 2009.

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1941-, Tomblin Linda, ed. Fingerprints of God. Nashville, Tenn: Broadman Press, 1990.

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Madonia, Kristen-Paige. Fingerprints of you. New York: Simon & Schuster Books for Young Readers, 2012.

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Casteren, Anton van. The devil's fingerprints. New York: Carlton Press, 1994.

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Copp, Rick. Fingerprints and facelifts. New York, NY: Kensington Pub. Corp., 2009.

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Book chapters on the topic "Fingerprints"

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Artone, Carmine J. "Fingerprints." In The Forensic Laboratory Handbook Procedures and Practice, 145–80. Totowa, NJ: Humana Press, 2010. http://dx.doi.org/10.1007/978-1-60761-872-0_6.

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Grinstead, Charles, William Peterson, and J. Snell. "Fingerprints." In Probability Tales, 191–224. Providence, Rhode Island: American Mathematical Society, 2011. http://dx.doi.org/10.1090/stml/057/04.

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Dalrymple, Brian E. "Fingerprints." In The Forensic Laboratory Handbook, 117–41. Totowa, NJ: Humana Press, 2006. http://dx.doi.org/10.1385/1-59259-946-x:117.

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Boone, Leggie L. "Fingerprints." In Manual of Crime Scene Investigation, 181–92. Boca Raton: CRC Press, 2022. http://dx.doi.org/10.4324/9781003129554-12.

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Carr, Mary Ann. "Fingerprints." In The Great Chocolate Caper, 9. New York: Routledge, 2021. http://dx.doi.org/10.4324/9781003238805-6.

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Othman, Asem, and Arun Ross. "Mixing Fingerprints." In Encyclopedia of Biometrics, 1–6. Boston, MA: Springer US, 2014. http://dx.doi.org/10.1007/978-3-642-27733-7_9100-2.

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Lehmann, Ann-Sophie. "Taking Fingerprints." In Spur der Arbeit, 199–218. Köln: Böhlau Verlag, 2018. http://dx.doi.org/10.7788/9783412505080.199.

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Newbould, Brian. "Harmonic Fingerprints." In Schubert's Workshop: Volume 1, 70–86. New York: Routledge, 2022. http://dx.doi.org/10.4324/9781003311263-9.

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Mainguet, Jean-François. "Fingerprints Hashing." In Encyclopedia of Biometrics, 543–49. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-73003-5_60.

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Othman, Asem, and Arun Ross. "Mixing Fingerprints." In Encyclopedia of Biometrics, 1122–27. Boston, MA: Springer US, 2015. http://dx.doi.org/10.1007/978-1-4899-7488-4_9100.

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Conference papers on the topic "Fingerprints"

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Olimb, Hal E., Thomas F. Krile, and John F. Walkup. "Optical enhancement of degraded fingerprints." In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1985. http://dx.doi.org/10.1364/oam.1985.wj37.

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The identifying features of degraded fingerprints are optically enhanced with a coherent optical processor. The spatial and spatial frequency information contained in a fingerprint and its Fourier transform are located and characterized. A spectral model is developed for each of the basic ridge pattern types. The ridges and the ridge pattern details are enhanced by filters generated from these spectral models. Experimental results are shown.
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Igaki, Seigo, Shin Eguchi, Hiroyuki Ikeda, and Takefumi Inagaki. "Real-time fingerprint sensor using a hologram." In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1985. http://dx.doi.org/10.1364/oam.1985.thl1.

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We have developed a real-time fingerprint sensor using a flat glass plate with hologram. Personal identification by fingerprint validation will be widely used to maintain security of a computer system because of its high reliability. Such real-time sensors must be distortion free, high contrast, compact, and insensitive to residual fingerprints. The conventional prism-type fingerprint sensors have problems with distortion compensation and compactness.
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Ford, Kerry, Casimer De Cusatis, and Michael Otis. "Bypassing Fingerprint Scanners Using Artifical Fingerprints." In 2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON). IEEE, 2021. http://dx.doi.org/10.1109/uemcon53757.2021.9666631.

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Liu, Kaiyu, Danming Huang, Chengzhe Tang, Lei Deng, Qi Yang, Xiaoxiao Dai, Deming Liu, and Mengfan Cheng. "A physical-layer Rogue ONU identification method based on hardware fingerprint technology." In Optical Fiber Communication Conference. Washington, D.C.: Optica Publishing Group, 2024. http://dx.doi.org/10.1364/ofc.2024.m4d.1.

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We propose a method for identifying rogue ONUs based on hardware fingerprint technology. By directly detecting waveform fingerprints, the experimental results show that the average identification accuracy within 16 ONUs can reach 96.74%.
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Zheng, Wenhan, Diana Lee, and Jun Xia. "High-resolution photoacoustic tomography for fingerprint and vascular imaging." In Frontiers in Optics. Washington, D.C.: Optica Publishing Group, 2022. http://dx.doi.org/10.1364/fio.2022.fw7d.5.

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We developed a new fingerprint imaging system which can capture both fingerprints and underlying vascular structures at a high spatial resolution. A 3D image was obtained by scanning the linear array over the fingertip.
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Tisinger, Louis, Enrique Lozano Diz, Rosalind Wolstenholme, Leesa Ferguson, P. M. Champion, and L. D. Ziegler. "Fingerprints..[ellipsis (horizontal)] Fingerprinted by SERS!!!" In XXII INTERNATIONAL CONFERENCE ON RAMAN SPECTROSCOPY. AIP, 2010. http://dx.doi.org/10.1063/1.3482472.

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Younan, Hua, Lo Keng Foo, N. Ramesh Rao, and Z. Q. Mo. "Studies on Fingerprints of EDX, FTIR, XPS and TOF-SIMS Techniques and Applications in Failure Analysis of Wafer Fabrication." In ISTFA 2004. ASM International, 2004. http://dx.doi.org/10.31399/asm.cp.istfa2004p0474.

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Abstract In failure analysis of wafer fabrication it is difficult to identify possible sources of carbon-related contaminants as most of them are from polymers, organic and complex compounds. In this paper, the fingerprints of EDX, FTIR, XPS and TOFSIMS techniques will be introduced so as to identify sources of carbon-related contaminants. For example, Si peak (1.740 keV) can be used as a fingerprint of EDX technique to identify the ink-related contaminant from the other carbon-related contaminants. FTIR spectra of more than 10 possible materials from wafer fab and assembly processes are discussed, which may be used as the fingerprints of FTIR technique to identify carbon-related contaminants. The C=O functional group and the PDMS (PolyDimethylSiloxane) are recommended as the fingerprints of XPS and TOF-SIMS techniques to identify source of carbon-related contaminants, respectively. In this paper, some application cases will be also discussed.
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Baek, Young-Hyun. "Robust optical fingerprint sensor to moisture fingerprints." In 2016 International SoC Design Conference (ISOCC). IEEE, 2016. http://dx.doi.org/10.1109/isocc.2016.7799851.

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Mil'shtein, S., A. Pillai, A. Shendye, C. Liessner, and M. Baier. "Fingerprint Recognition Algorithms for Partial and Full Fingerprints." In 2008 IEEE Conference on Technologies for Homeland Security. IEEE, 2008. http://dx.doi.org/10.1109/ths.2008.4534494.

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Wang, Yunlong, Le Duan, Simon Butscher, Jens Mueller, and Harald Reiterer. "Fingerprints." In MobileHCI '16: 18th International Conference on Human-Computer Interaction with Mobile Devices and Services. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2957265.2965006.

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Reports on the topic "Fingerprints"

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Chang, Jien. Capturing Cognitive Fingerprints for Active Authentication. Fort Belvoir, VA: Defense Technical Information Center, October 2014. http://dx.doi.org/10.21236/ada611005.

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Smith, Joshua E. Climate Signatures Fingerprints of a Dynamic Planet. Office of Scientific and Technical Information (OSTI), June 2015. http://dx.doi.org/10.2172/1184613.

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Armbrust, E. V. Analysis of Diatom Blooms Using DNA Fingerprints. Fort Belvoir, VA: Defense Technical Information Center, September 2001. http://dx.doi.org/10.21236/ada627659.

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Armbrust, E. V. Analysis of Diatom Blooms Using DNA Fingerprints. Fort Belvoir, VA: Defense Technical Information Center, September 1999. http://dx.doi.org/10.21236/ada629750.

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Lamont, Stephen Philip. Nuclear forensics: The fingerprints of mass destruction [PowerPoint]. Office of Scientific and Technical Information (OSTI), September 2018. http://dx.doi.org/10.2172/1471299.

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Button, Julie M. Analysis of cellular and extracellular DNA in fingerprints. Office of Scientific and Technical Information (OSTI), September 2014. http://dx.doi.org/10.2172/1169860.

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Libert, John M., John Grantham, and Shahram Orandi. A 1D spectral image validationverification metric for fingerprints. Gaithersburg, MD: National Institute of Standards and Technology, 2009. http://dx.doi.org/10.6028/nist.ir.7599.

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Wagman, Benjamin, Laura Swiler, Kamaljit Chowdhary, and Benjamin Hillman. The Fingerprints of Stratospheric Aerosol Injection in E3SM. Office of Scientific and Technical Information (OSTI), September 2021. http://dx.doi.org/10.2172/1821542.

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SEDLACEK, III, A. J. FINFROCK,C. ULTRAVIOLET RAMAN SPECTRAL SIGNATURE ACQUISITION: UV RAMAN SPECTRAL FINGERPRINTS. Office of Scientific and Technical Information (OSTI), September 2002. http://dx.doi.org/10.2172/15006636.

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Chellappa, Rama. Screen Fingerprints as a Novel Modality for Active Authentication. Fort Belvoir, VA: Defense Technical Information Center, March 2014. http://dx.doi.org/10.21236/ada598425.

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