Gabor filter based fingerprint image enhancement

Science.gov (United States)

Wang, Jin-Xiang

2013-03-01

Fingerprint recognition technology has become the most reliable biometric technology due to its uniqueness and invariance, which has been most convenient and most reliable technique for personal authentication. The development of Automated Fingerprint Identification System is an urgent need for modern information security. Meanwhile, fingerprint preprocessing algorithm of fingerprint recognition technology has played an important part in Automatic Fingerprint Identification System. This article introduces the general steps in the fingerprint recognition technology, namely the image input, preprocessing, feature recognition, and fingerprint image enhancement. As the key to fingerprint identification technology, fingerprint image enhancement affects the accuracy of the system. It focuses on the characteristics of the fingerprint image, Gabor filters algorithm for fingerprint image enhancement, the theoretical basis of Gabor filters, and demonstration of the filter. The enhancement algorithm for fingerprint image is in the windows XP platform with matlab.65 as a development tool for the demonstration. The result shows that the Gabor filter is effective in fingerprint image enhancement technology.

Touchless fingerprint biometrics

CERN Document Server

Labati, Ruggero Donida; Scotti, Fabio

2015-01-01

Offering 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 hardw

Improved fingercode alignment for accurate and compact fingerprint recognition

CSIR Research Space (South Africa)

Brown, Dane

2016-05-01

Full Text Available Alignment for Accurate and Compact Fingerprint Recognition Dane Brown∗† and Karen Bradshaw∗ ∗Department of Computer Science Rhodes University Grahamstown, South Africa †Council for Scientific and Industrial Research Modelling and Digital Sciences Pretoria.... The experimental analysis and results are discussed in Section IV. Section V concludes the paper. II. RELATED STUDIES FingerCode [1] uses circular tessellation of filtered finger- print images centered at the reference point, which results in a circular ROI...

Method for modeling post-mortem biometric 3D fingerprints

Science.gov (United States)

Rajeev, Srijith; Shreyas, Kamath K. M.; Agaian, Sos S.

2016-05-01

Despite the advancements of fingerprint recognition in 2-D and 3-D domain, authenticating deformed/post-mortem fingerprints continue to be an important challenge. Prior cleansing and reconditioning of the deceased finger is required before acquisition of the fingerprint. The victim's finger needs to be precisely and carefully operated by a medium to record the fingerprint impression. This process may damage the structure of the finger, which subsequently leads to higher false rejection rates. This paper proposes a non-invasive method to perform 3-D deformed/post-mortem finger modeling, which produces a 2-D rolled equivalent fingerprint for automated verification. The presented novel modeling method involves masking, filtering, and unrolling. Computer simulations were conducted on finger models with different depth variations obtained from Flashscan3D LLC. Results illustrate that the modeling scheme provides a viable 2-D fingerprint of deformed models for automated verification. The quality and adaptability of the obtained unrolled 2-D fingerprints were analyzed using NIST fingerprint software. Eventually, the presented method could be extended to other biometric traits such as palm, foot, tongue etc. for security and administrative applications.

Fingerprint multicast in secure video streaming.

Science.gov (United States)

Zhao, H Vicky; Liu, K J Ray

2006-01-01

Digital fingerprinting is an emerging technology to protect multimedia content from illegal redistribution, where each distributed copy is labeled with unique identification information. In video streaming, huge amount of data have to be transmitted to a large number of users under stringent latency constraints, so the bandwidth-efficient distribution of uniquely fingerprinted copies is crucial. This paper investigates the secure multicast of anticollusion fingerprinted video in streaming applications and analyzes their performance. We first propose a general fingerprint multicast scheme that can be used with most spread spectrum embedding-based multimedia fingerprinting systems. To further improve the bandwidth efficiency, we explore the special structure of the fingerprint design and propose a joint fingerprint design and distribution scheme. From our simulations, the two proposed schemes can reduce the bandwidth requirement by 48% to 87%, depending on the number of users, the characteristics of video sequences, and the network and computation constraints. We also show that under the constraint that all colluders have the same probability of detection, the embedded fingerprints in the two schemes have approximately the same collusion resistance. Finally, we propose a fingerprint drift compensation scheme to improve the quality of the reconstructed sequences at the decoder's side without introducing extra communication overhead.

Authentication and distinction of Shenmai injection with HPLC fingerprint analysis assisted by pattern recognition techniques

Directory of Open Access Journals (Sweden)

Xue-Feng Lu

2012-10-01

Full Text Available In this paper, the feasibility and advantages of employing high performance liquid chromatographic (HPLC fingerprints combined with pattern recognition techniques for quality control of Shenmai injection were investigated and demonstrated. The Similarity Evaluation System was employed to evaluate the similarities of samples of Shenmai injection, and the HPLC generated chromatographic data were analyzed using hierarchical clustering analysis (HCA and soft independent modeling of class analogy (SIMCA. Consistent results were obtained to show that the authentic samples and the blended samples were successfully classified by SIMCA, which could be applied to accurate discrimination and quality control of Shenmai injection. Furthermore, samples could also be grouped in accordance with manufacturers. Our results revealed that the developed method has potential perspective for the original discrimination and quality control of Shenmai injection. Keywords: Shenmai injection, High performance liquid chromatography, Fingerprint, Pattern recognition

Case study of 3D fingerprints applications.

Directory of Open Access Journals (Sweden)

Feng Liu

Full Text Available Human fingers are 3D objects. More information will be provided if three dimensional (3D fingerprints are available compared with two dimensional (2D fingerprints. Thus, this paper firstly collected 3D finger point cloud data by Structured-light Illumination method. Additional features from 3D fingerprint images are then studied and extracted. The applications of these features are finally discussed. A series of experiments are conducted to demonstrate the helpfulness of 3D information to fingerprint recognition. Results show that a quick alignment can be easily implemented under the guidance of 3D finger shape feature even though this feature does not work for fingerprint recognition directly. The newly defined distinctive 3D shape ridge feature can be used for personal authentication with Equal Error Rate (EER of ~8.3%. Also, it is helpful to remove false core point. Furthermore, a promising of EER ~1.3% is realized by combining this feature with 2D features for fingerprint recognition which indicates the prospect of 3D fingerprint recognition.

Comparative study of multimodal biometric recognition by fusion of iris and fingerprint.

Science.gov (United States)

Benaliouche, Houda; Touahria, Mohamed

2014-01-01

This research investigates the comparative performance from three different approaches for multimodal recognition of combined iris and fingerprints: classical sum rule, weighted sum rule, and fuzzy logic method. The scores from the different biometric traits of iris and fingerprint are fused at the matching score and the decision levels. The scores combination approach is used after normalization of both scores using the min-max rule. Our experimental results suggest that the fuzzy logic method for the matching scores combinations at the decision level is the best followed by the classical weighted sum rule and the classical sum rule in order. The performance evaluation of each method is reported in terms of matching time, error rates, and accuracy after doing exhaustive tests on the public CASIA-Iris databases V1 and V2 and the FVC 2004 fingerprint database. Experimental results prior to fusion and after fusion are presented followed by their comparison with related works in the current literature. The fusion by fuzzy logic decision mimics the human reasoning in a soft and simple way and gives enhanced results.

Comparative Study of Multimodal Biometric Recognition by Fusion of Iris and Fingerprint

Directory of Open Access Journals (Sweden)

Houda Benaliouche

2014-01-01

Full Text Available This research investigates the comparative performance from three different approaches for multimodal recognition of combined iris and fingerprints: classical sum rule, weighted sum rule, and fuzzy logic method. The scores from the different biometric traits of iris and fingerprint are fused at the matching score and the decision levels. The scores combination approach is used after normalization of both scores using the min-max rule. Our experimental results suggest that the fuzzy logic method for the matching scores combinations at the decision level is the best followed by the classical weighted sum rule and the classical sum rule in order. The performance evaluation of each method is reported in terms of matching time, error rates, and accuracy after doing exhaustive tests on the public CASIA-Iris databases V1 and V2 and the FVC 2004 fingerprint database. Experimental results prior to fusion and after fusion are presented followed by their comparison with related works in the current literature. The fusion by fuzzy logic decision mimics the human reasoning in a soft and simple way and gives enhanced results.

Comparative Study of Multimodal Biometric Recognition by Fusion of Iris and Fingerprint

Science.gov (United States)

Benaliouche, Houda; Touahria, Mohamed

2014-01-01

This research investigates the comparative performance from three different approaches for multimodal recognition of combined iris and fingerprints: classical sum rule, weighted sum rule, and fuzzy logic method. The scores from the different biometric traits of iris and fingerprint are fused at the matching score and the decision levels. The scores combination approach is used after normalization of both scores using the min-max rule. Our experimental results suggest that the fuzzy logic method for the matching scores combinations at the decision level is the best followed by the classical weighted sum rule and the classical sum rule in order. The performance evaluation of each method is reported in terms of matching time, error rates, and accuracy after doing exhaustive tests on the public CASIA-Iris databases V1 and V2 and the FVC 2004 fingerprint database. Experimental results prior to fusion and after fusion are presented followed by their comparison with related works in the current literature. The fusion by fuzzy logic decision mimics the human reasoning in a soft and simple way and gives enhanced results. PMID:24605065

An investigation of fake fingerprint detection approaches

Science.gov (United States)

Ahmad, Asraful Syifaa'; Hassan, Rohayanti; Othman, Razib M.

2017-10-01

The most reliable biometrics technology, fingerprint recognition is widely used in terms of security due to its permanence and uniqueness. However, it is also vulnerable to the certain type of attacks including presenting fake fingerprints to the sensor which requires the development of new and efficient protection measures. Particularly, the aim is to identify the most recent literature related to the fake fingerprint recognition and only focus on software-based approaches. A systematic review is performed by analyzing 146 primary studies from the gross collection of 34 research papers to determine the taxonomy, approaches, online public databases, and limitations of the fake fingerprint. Fourteen software-based approaches have been briefly described, four limitations of fake fingerprint image were revealed and two known fake fingerprint databases were addressed briefly in this review. Therefore this work provides an overview of an insight into the current understanding of fake fingerprint recognition besides identifying future research possibilities.

An enhanced feature set for pattern recognition based contrast enhancement of contact-less captured latent fingerprints in digitized crime scene forensics

Science.gov (United States)

Hildebrandt, Mario; Kiltz, Stefan; Dittmann, Jana; Vielhauer, Claus

2014-02-01

In crime scene forensics latent fingerprints are found on various substrates. Nowadays primarily physical or chemical preprocessing techniques are applied for enhancing the visibility of the fingerprint trace. In order to avoid altering the trace it has been shown that contact-less sensors offer a non-destructive acquisition approach. Here, the exploitation of fingerprint or substrate properties and the utilization of signal processing techniques are an essential requirement to enhance the fingerprint visibility. However, especially the optimal sensory is often substrate-dependent. An enhanced generic pattern recognition based contrast enhancement approach for scans of a chromatic white light sensor is introduced in Hildebrandt et al.1 using statistical, structural and Benford's law2 features for blocks of 50 micron. This approach achieves very good results for latent fingerprints on cooperative, non-textured, smooth substrates. However, on textured and structured substrates the error rates are very high and the approach thus unsuitable for forensic use cases. We propose the extension of the feature set with semantic features derived from known Gabor filter based exemplar fingerprint enhancement techniques by suggesting an Epsilon-neighborhood of each block in order to achieve an improved accuracy (called fingerprint ridge orientation semantics). Furthermore, we use rotation invariant Hu moments as an extension of the structural features and two additional preprocessing methods (separate X- and Y Sobel operators). This results in a 408-dimensional feature space. In our experiments we investigate and report the recognition accuracy for eight substrates, each with ten latent fingerprints: white furniture surface, veneered plywood, brushed stainless steel, aluminum foil, "Golden-Oak" veneer, non-metallic matte car body finish, metallic car body finish and blued metal. In comparison to Hildebrandt et al.,1 our evaluation shows a significant reduction of the error rates

Security and matching of partial fingerprint recognition systems

Science.gov (United States)

Jea, Tsai-Yang; Chavan, Viraj S.; Govindaraju, Venu; Schneider, John K.

2004-08-01

Despite advances in fingerprint identification techniques, matching incomplete or partial fingerprints still poses a difficult challenge. While the introduction of compact silicon chip-based sensors that capture only a part of the fingerprint area have made this problem important from a commercial perspective, there is also considerable interest on the topic for processing partial and latent fingerprints obtained at crime scenes. Attempts to match partial fingerprints using singular ridge structures-based alignment techniques fail when the partial print does not include such structures (e.g., core or delta). We present a multi-path fingerprint matching approach that utilizes localized secondary features derived using only the relative information of minutiae. Since the minutia-based fingerprint representation, is an ANSI-NIST standard, our approach has the advantage of being directly applicable to already existing databases. We also analyze the vulnerability of partial fingerprint identification systems to brute force attacks. The described matching approach has been tested on one of FVC2002"s DB1 database11. The experimental results show that our approach achieves an equal error rate of 1.25% and a total error rate of 1.8% (with FAR at 0.2% and FRR at 1.6%).

[Research on the application of grey system theory in the pattern recognition for chromatographic fingerprints of traditional Chinese medicine].

Science.gov (United States)

Wei, Hang; Lin, Li; Zhang, Yuan; Wang, Lianjing; Chen, Qinqun

2013-02-01

A model based on grey system theory was proposed for pattern recognition in chromatographic fingerprints (CF) of traditional Chinese medicine (TCM). The grey relational grade among the data series of each testing CF and the ideal CF was obtained by entropy and norm respectively, then the principle of "maximal matching degree" was introduced to make judgments, so as to achieve the purpose of variety identification and quality evaluation. A satisfactory result in the high performance liquid chromatographic (HPLC) analysis of 56 batches of different varieties of Exocarpium Citrus Grandis was achieved with this model. The errors in the chromatographic fingerprint analysis caused by traditional similarity method or grey correlation method were overcome, as the samples of Citrus grandis 'Tomentosa' and Citrus grandis (L.) Osbeck were correctly distinguished in the experiment. Furthermore in the study on the variety identification of Citrus grandis 'Tomentosa', the recognition rates were up to 92.85%, although the types and the contents of the chemical compositions of the samples were very close. At the same time, the model had the merits of low computation complexity and easy operation by computer programming. The research indicated that the grey system theory has good applicability to pattern recognition in the chromatographic fingerprints of TCM.

Reference point detection for improved fingerprint matching

NARCIS (Netherlands)

Ignatenko, T.; Kalker, A.A.C.M.; Veen, van der M.; Bazen, A.; Delp, E.J.; Wong, P.W.

2006-01-01

One of the important stages of fingerprint recognition is the registration of the fingerprints with respect to the original template. This is not a straightforward task as fingerprint images may have been subject to rotations and translations. Popular techniques for fingerprint registration use a

Three-dimensional imaging of artificial fingerprint by optical coherence tomography

Science.gov (United States)

Larin, Kirill V.; Cheng, Yezeng

2008-03-01

Fingerprint recognition is one of the popular used methods of biometrics. However, due to the surface topography limitation, fingerprint recognition scanners are easily been spoofed, e.g. using artificial fingerprint dummies. Thus, biometric fingerprint identification devices need to be more accurate and secure to deal with different fraudulent methods including dummy fingerprints. Previously, we demonstrated that Optical Coherence Tomography (OCT) images revealed the presence of the artificial fingerprints (made from different household materials, such as cement and liquid silicone rubber) at all times, while the artificial fingerprints easily spoofed the commercial fingerprint reader. Also we demonstrated that an analysis of the autocorrelation of the OCT images could be used in automatic recognition systems. Here, we exploited the three-dimensional (3D) imaging of the artificial fingerprint by OCT to generate vivid 3D image for both the artificial fingerprint layer and the real fingerprint layer beneath. With the reconstructed 3D image, it could not only point out whether there exists an artificial material, which is intended to spoof the scanner, above the real finger, but also could provide the hacker's fingerprint. The results of these studies suggested that Optical Coherence Tomography could be a powerful real-time noninvasive method for accurate identification of artificial fingerprints real fingerprints as well.

Uniform Local Binary Pattern for Fingerprint Liveness Detection in the Gaussian Pyramid

Directory of Open Access Journals (Sweden)

Yujia Jiang

2018-01-01

Full Text Available Fingerprint recognition schemas are widely used in our daily life, such as Door Security, Identification, and Phone Verification. However, the existing problem is that fingerprint recognition systems are easily tricked by fake fingerprints for collaboration. Therefore, designing a fingerprint liveness detection module in fingerprint recognition systems is necessary. To solve the above problem and discriminate true fingerprint from fake ones, a novel software-based liveness detection approach using uniform local binary pattern (ULBP in spatial pyramid is applied to recognize fingerprint liveness in this paper. Firstly, preprocessing operation for each fingerprint is necessary. Then, to solve image rotation and scale invariance, three-layer spatial pyramids of fingerprints are introduced in this paper. Next, texture information for three layers spatial pyramids is described by using uniform local binary pattern to extract features of given fingerprints. The accuracy of our proposed method has been compared with several state-of-the-art methods in fingerprint liveness detection. Experiments based on standard databases, taken from Liveness Detection Competition 2013 composed of four different fingerprint sensors, have been carried out. Finally, classifier model based on extracted features is trained using SVM classifier. Experimental results present that our proposed method can achieve high recognition accuracy compared with other methods.

Fingerprint matching with optical coherence tomography

CSIR Research Space (South Africa)

Moolla, Y

2015-12-01

Full Text Available Fingerprint recognition is an important security technique with a steadily growing usage for the identification and verification of individuals. However, current fingerprint acquisition systems have certain disadvantages, which include...

A fingerprint classification algorithm based on combination of local and global information

Science.gov (United States)

Liu, Chongjin; Fu, Xiang; Bian, Junjie; Feng, Jufu

2011-12-01

Fingerprint recognition is one of the most important technologies in biometric identification and has been wildly applied in commercial and forensic areas. Fingerprint classification, as the fundamental procedure in fingerprint recognition, can sharply decrease the quantity for fingerprint matching and improve the efficiency of fingerprint recognition. Most fingerprint classification algorithms are based on the number and position of singular points. Because the singular points detecting method only considers the local information commonly, the classification algorithms are sensitive to noise. In this paper, we propose a novel fingerprint classification algorithm combining the local and global information of fingerprint. Firstly we use local information to detect singular points and measure their quality considering orientation structure and image texture in adjacent areas. Furthermore the global orientation model is adopted to measure the reliability of singular points group. Finally the local quality and global reliability is weighted to classify fingerprint. Experiments demonstrate the accuracy and effectivity of our algorithm especially for the poor quality fingerprint images.

Data Compression of Fingerprint Minutiae

OpenAIRE

VISHAL SHRIVASTAVA; SUMIT SHARMA

2012-01-01

Biometric techniques have usual advantages over conventional personal identification technique. Among various commercially available biometric techniques such as face, fingerprint, Iris etc., fingerprint-based techniques are the most accepted recognition system. Fingerprints are trace or impression of patterns created byfriction ridges of the skin in the fingers and thumbs. Steganography usually used in smart card is a safe technique for authenticating a person. In steganography, biometric ch...

Self-Organizing Maps for Fingerprint Image Quality Assessment

DEFF Research Database (Denmark)

Olsen, Martin Aastrup; Tabassi, Elham; Makarov, Anton

2013-01-01

Fingerprint quality assessment is a crucial task which needs to be conducted accurately in various phases in the biometric enrolment and recognition processes. Neglecting quality measurement will adversely impact accuracy and efficiency of biometric recognition systems (e.g. verification and iden......Fingerprint quality assessment is a crucial task which needs to be conducted accurately in various phases in the biometric enrolment and recognition processes. Neglecting quality measurement will adversely impact accuracy and efficiency of biometric recognition systems (e.g. verification...... machine learning techniques. We train a self-organizing map (SOM) to cluster blocks of fingerprint images based on their spatial information content. The output of the SOM is a high-level representation of the finger image, which forms the input to a Random Forest trained to learn the relationship between...

Clarification of nuclear risk recognition scheme through dialogue forum

International Nuclear Information System (INIS)

Yagi, Ekou; Takahashi, Makoto; Kitamura, Masaharu

2007-01-01

The design framework and operational guidelines for conducting repetitive dialogue between public and nuclear engineers are described in this paper. An action research project named repetitive dialogue forum has been conducted in two municipalities where nuclear facilities were sited. The qualitative evaluation by public participants indicated that the public trust in the nuclear experts, known as the crucial factor for meaningful communication, was successfully established through the dialogue forum. In addition, the expert showed a marked psychological change from distrust to trust in public. Through a detailed analysis of the comments of the participants raised during the forums, the nuclear risk recognition scheme of the public was clarified. The constituents of the risk recognition scheme about nuclear facilities were identified as follows. The first is related to the technical risk recognition factor including purely technical risk, organizational elements and regulatory elements. The second is the social risk recognition factor including economical and mental elements. The last is the communication factor including the influence of mass media, difficulty in frank communication in local community etc. It became clear that the information provision activities conducted by the government and the nuclear industry were lack of in-depth understanding of actual information needs in the public. Provision of information contents consistent with our observations is recommended for reestablishment of public trust in expert and for more informative dialogical interactions. (author)

Fingerprint start the next generation of payment method : Fingerprint payment: a new mode of mobile payment

OpenAIRE

Wu, Chong

2016-01-01

In the generation of mobile internet, fingerprint payment is one of the most popular topics at the moment. China has a big market and many users are using the mobile payment methods. There are a large number of mobile phones equipped with fingerprint recognition technology. As we know, fingerprint payment brings us more convenience and safety. We do not need to use many bankcards, and fingerprint also eliminates the users from the trouble of queuing to pay. However, users send traditional dig...

Hierarchical Recognition Scheme for Human Facial Expression Recognition Systems

Directory of Open Access Journals (Sweden)

Muhammad Hameed Siddiqi

2013-12-01

Full Text Available Over the last decade, human facial expressions recognition (FER has emerged as an important research area. Several factors make FER a challenging research problem. These include varying light conditions in training and test images; need for automatic and accurate face detection before feature extraction; and high similarity among different expressions that makes it difficult to distinguish these expressions with a high accuracy. This work implements a hierarchical linear discriminant analysis-based facial expressions recognition (HL-FER system to tackle these problems. Unlike the previous systems, the HL-FER uses a pre-processing step to eliminate light effects, incorporates a new automatic face detection scheme, employs methods to extract both global and local features, and utilizes a HL-FER to overcome the problem of high similarity among different expressions. Unlike most of the previous works that were evaluated using a single dataset, the performance of the HL-FER is assessed using three publicly available datasets under three different experimental settings: n-fold cross validation based on subjects for each dataset separately; n-fold cross validation rule based on datasets; and, finally, a last set of experiments to assess the effectiveness of each module of the HL-FER separately. Weighted average recognition accuracy of 98.7% across three different datasets, using three classifiers, indicates the success of employing the HL-FER for human FER.

Hierarchical Recognition Scheme for Human Facial Expression Recognition Systems

Science.gov (United States)

Siddiqi, Muhammad Hameed; Lee, Sungyoung; Lee, Young-Koo; Khan, Adil Mehmood; Truc, Phan Tran Ho

2013-01-01

Over the last decade, human facial expressions recognition (FER) has emerged as an important research area. Several factors make FER a challenging research problem. These include varying light conditions in training and test images; need for automatic and accurate face detection before feature extraction; and high similarity among different expressions that makes it difficult to distinguish these expressions with a high accuracy. This work implements a hierarchical linear discriminant analysis-based facial expressions recognition (HL-FER) system to tackle these problems. Unlike the previous systems, the HL-FER uses a pre-processing step to eliminate light effects, incorporates a new automatic face detection scheme, employs methods to extract both global and local features, and utilizes a HL-FER to overcome the problem of high similarity among different expressions. Unlike most of the previous works that were evaluated using a single dataset, the performance of the HL-FER is assessed using three publicly available datasets under three different experimental settings: n-fold cross validation based on subjects for each dataset separately; n-fold cross validation rule based on datasets; and, finally, a last set of experiments to assess the effectiveness of each module of the HL-FER separately. Weighted average recognition accuracy of 98.7% across three different datasets, using three classifiers, indicates the success of employing the HL-FER for human FER. PMID:24316568

Extended pattern recognition scheme for self-learning kinetic Monte Carlo simulations

International Nuclear Information System (INIS)

Shah, Syed Islamuddin; Nandipati, Giridhar; Kara, Abdelkader; Rahman, Talat S

2012-01-01

We report the development of a pattern recognition scheme that takes into account both fcc and hcp adsorption sites in performing self-learning kinetic Monte Carlo (SLKMC-II) simulations on the fcc(111) surface. In this scheme, the local environment of every under-coordinated atom in an island is uniquely identified by grouping fcc sites, hcp sites and top-layer substrate atoms around it into hexagonal rings. As the simulation progresses, all possible processes, including those such as shearing, reptation and concerted gliding, which may involve fcc-fcc, hcp-hcp and fcc-hcp moves are automatically found, and their energetics calculated on the fly. In this article we present the results of applying this new pattern recognition scheme to the self-diffusion of 9-atom islands (M 9 ) on M(111), where M = Cu, Ag or Ni.

Smartphone-Based Patients' Activity Recognition by Using a Self-Learning Scheme for Medical Monitoring.

Science.gov (United States)

Guo, Junqi; Zhou, Xi; Sun, Yunchuan; Ping, Gong; Zhao, Guoxing; Li, Zhuorong

2016-06-01

Smartphone based activity recognition has recently received remarkable attention in various applications of mobile health such as safety monitoring, fitness tracking, and disease prediction. To achieve more accurate and simplified medical monitoring, this paper proposes a self-learning scheme for patients' activity recognition, in which a patient only needs to carry an ordinary smartphone that contains common motion sensors. After the real-time data collection though this smartphone, we preprocess the data using coordinate system transformation to eliminate phone orientation influence. A set of robust and effective features are then extracted from the preprocessed data. Because a patient may inevitably perform various unpredictable activities that have no apriori knowledge in the training dataset, we propose a self-learning activity recognition scheme. The scheme determines whether there are apriori training samples and labeled categories in training pools that well match with unpredictable activity data. If not, it automatically assembles these unpredictable samples into different clusters and gives them new category labels. These clustered samples combined with the acquired new category labels are then merged into the training dataset to reinforce recognition ability of the self-learning model. In experiments, we evaluate our scheme using the data collected from two postoperative patient volunteers, including six labeled daily activities as the initial apriori categories in the training pool. Experimental results demonstrate that the proposed self-learning scheme for activity recognition works very well for most cases. When there exist several types of unseen activities without any apriori information, the accuracy reaches above 80 % after the self-learning process converges.

Carbon nuclear magnetic resonance spectroscopic fingerprinting of commercial gasoline: pattern-recognition analyses for screening quality control purposes.

Science.gov (United States)

Flumignan, Danilo Luiz; Boralle, Nivaldo; Oliveira, José Eduardo de

2010-06-30

In this work, the combination of carbon nuclear magnetic resonance ((13)C NMR) fingerprinting with pattern-recognition analyses provides an original and alternative approach to screening commercial gasoline quality. Soft Independent Modelling of Class Analogy (SIMCA) was performed on spectroscopic fingerprints to classify representative commercial gasoline samples, which were selected by Hierarchical Cluster Analyses (HCA) over several months in retails services of gas stations, into previously quality-defined classes. Following optimized (13)C NMR-SIMCA algorithm, sensitivity values were obtained in the training set (99.0%), with leave-one-out cross-validation, and external prediction set (92.0%). Governmental laboratories could employ this method as a rapid screening analysis to discourage adulteration practices. Copyright 2010 Elsevier B.V. All rights reserved.

SVD compression for magnetic resonance fingerprinting in the time domain.

Science.gov (United States)

McGivney, Debra F; Pierre, Eric; Ma, Dan; Jiang, Yun; Saybasili, Haris; Gulani, Vikas; Griswold, Mark A

2014-12-01

Magnetic resonance (MR) fingerprinting is a technique for acquiring and processing MR data that simultaneously provides quantitative maps of different tissue parameters through a pattern recognition algorithm. A predefined dictionary models the possible signal evolutions simulated using the Bloch equations with different combinations of various MR parameters and pattern recognition is completed by computing the inner product between the observed signal and each of the predicted signals within the dictionary. Though this matching algorithm has been shown to accurately predict the MR parameters of interest, one desires a more efficient method to obtain the quantitative images. We propose to compress the dictionary using the singular value decomposition, which will provide a low-rank approximation. By compressing the size of the dictionary in the time domain, we are able to speed up the pattern recognition algorithm, by a factor of between 3.4-4.8, without sacrificing the high signal-to-noise ratio of the original scheme presented previously.

SU-E-I-75: Development of New Biological Fingerprints for Patient Recognition to Identify Misfiled Images in a PACS Server

Energy Technology Data Exchange (ETDEWEB)

Shimizu, Y; Yoon, Y; Iwase, K; Yasumatsu, S; Matsunobu, Y [Department of Health Sciences, Graduate School of Medical Sciences, Kyushu University, Fukuoka, JP (Japan); Morishita, J [Department of Health Sciences, Faculty of Medical Sciences, Kyushu University, Fukuoka, JP (Japan)

2015-06-15

Purpose: We are trying to develop an image-searching technique to identify misfiled images in a picture archiving and communication system (PACS) server by using five biological fingerprints: the whole lung field, cardiac shadow, superior mediastinum, lung apex, and right lower lung. Each biological fingerprint in a chest radiograph includes distinctive anatomical structures to identify misfiled images. The whole lung field was less effective for evaluating the similarity between two images than the other biological fingerprints. This was mainly due to the variation in the positioning for chest radiographs. The purpose of this study is to develop new biological fingerprints that could reduce influence of differences in the positioning for chest radiography. Methods: Two hundred patients were selected randomly from our database (36,212 patients). These patients had two images each (current and previous images). Current images were used as the misfiled images in this study. A circumscribed rectangular area of the lung and the upper half of the rectangle were selected automatically as new biological fingerprints. These biological fingerprints were matched to all previous images in the database. The degrees of similarity between the two images were calculated for the same and different patients. The usefulness of new the biological fingerprints for automated patient recognition was examined in terms of receiver operating characteristic (ROC) analysis. Results: Area under the ROC curves (AUCs) for the circumscribed rectangle of the lung, upper half of the rectangle, and whole lung field were 0.980, 0.994, and 0.950, respectively. The new biological fingerprints showed better performance in identifying the patients correctly than the whole lung field. Conclusion: We have developed new biological fingerprints: circumscribed rectangle of the lung and upper half of the rectangle. These new biological fingerprints would be useful for automated patient identification system

SU-E-I-75: Development of New Biological Fingerprints for Patient Recognition to Identify Misfiled Images in a PACS Server

International Nuclear Information System (INIS)

Shimizu, Y; Yoon, Y; Iwase, K; Yasumatsu, S; Matsunobu, Y; Morishita, J

2015-01-01

Purpose: We are trying to develop an image-searching technique to identify misfiled images in a picture archiving and communication system (PACS) server by using five biological fingerprints: the whole lung field, cardiac shadow, superior mediastinum, lung apex, and right lower lung. Each biological fingerprint in a chest radiograph includes distinctive anatomical structures to identify misfiled images. The whole lung field was less effective for evaluating the similarity between two images than the other biological fingerprints. This was mainly due to the variation in the positioning for chest radiographs. The purpose of this study is to develop new biological fingerprints that could reduce influence of differences in the positioning for chest radiography. Methods: Two hundred patients were selected randomly from our database (36,212 patients). These patients had two images each (current and previous images). Current images were used as the misfiled images in this study. A circumscribed rectangular area of the lung and the upper half of the rectangle were selected automatically as new biological fingerprints. These biological fingerprints were matched to all previous images in the database. The degrees of similarity between the two images were calculated for the same and different patients. The usefulness of new the biological fingerprints for automated patient recognition was examined in terms of receiver operating characteristic (ROC) analysis. Results: Area under the ROC curves (AUCs) for the circumscribed rectangle of the lung, upper half of the rectangle, and whole lung field were 0.980, 0.994, and 0.950, respectively. The new biological fingerprints showed better performance in identifying the patients correctly than the whole lung field. Conclusion: We have developed new biological fingerprints: circumscribed rectangle of the lung and upper half of the rectangle. These new biological fingerprints would be useful for automated patient identification system

Impact of Finger Type in Fingerprint Authentication

Science.gov (United States)

Gafurov, Davrondzhon; Bours, Patrick; Yang, Bian; Busch, Christoph

Nowadays fingerprint verification system is the most widespread and accepted biometric technology that explores various features of the human fingers for this purpose. In general, every normal person has 10 fingers with different size. Although it is claimed that recognition performance with little fingers can be less accurate compared to other finger types, to our best knowledge, this has not been investigated yet. This paper presents our study on the topic of influence of the finger type into fingerprint recognition performance. For analysis we employ two fingerprint verification software packages (one public and one commercial). We conduct test on GUC100 multi sensor fingerprint database which contains fingerprint images of all 10 fingers from 100 subjects. Our analysis indeed confirms that performance with small fingers is less accurate than performance with the others fingers of the hand. It also appears that best performance is being obtained with thumb or index fingers. For example, performance deterioration from the best finger (i.e. index or thumb) to the worst fingers (i.e. small ones) can be in the range of 184%-1352%.

Fingerprint Change: Not Visible, But Tangible.

Science.gov (United States)

Negri, Francesca V; De Giorgi, Annamaria; Bozzetti, Cecilia; Squadrilli, Anna; Petronini, Pier Giorgio; Leonardi, Francesco; Bisogno, Luigi; Garofano, Luciano

2017-09-01

Hand-foot syndrome, a chemotherapy-induced cutaneous toxicity, can cause an alteration in fingerprints causing a setback for cancer patients due to the occurrence of false rejections. A colon cancer patient was fingerprinted after not having been able to use fingerprint recognition devices after 6 months of adjuvant chemotherapy. The fingerprint images were digitally processed to improve fingerprint definition without altering the papillary design. No evidence of skin toxicity was present. Two months later, the situation returned to normal. The fingerprint evaluation conducted on 15 identification points highlighted the quantitative and qualitative fingerprint alteration details detected after the end of chemotherapy and 2 months later. Fingerprint alteration during chemotherapy has been reported, but to our knowledge, this particular case is the first ever reported without evident clinical signs. Alternative fingerprint identification methods as well as improved biometric identification systems are needed in case of unexpected situations. © 2017 American Academy of Forensic Sciences.

Information Theoretical Analysis of Identification based on Active Content Fingerprinting

OpenAIRE

Farhadzadeh, Farzad; Willems, Frans M. J.; Voloshinovskiy, Sviatoslav

2014-01-01

Content fingerprinting and digital watermarking are techniques that are used for content protection and distribution monitoring. Over the past few years, both techniques have been well studied and their shortcomings understood. Recently, a new content fingerprinting scheme called {\\em active content fingerprinting} was introduced to overcome these shortcomings. Active content fingerprinting aims to modify a content to extract robuster fingerprints than the conventional content fingerprinting....

A Robust Multimodal Bio metric Authentication Scheme with Voice and Face Recognition

International Nuclear Information System (INIS)

Kasban, H.

2017-01-01

This paper proposes a multimodal biometric scheme for human authentication based on fusion of voice and face recognition. For voice recognition, three categories of features (statistical coefficients, cepstral coefficients and voice timbre) are used and compared. The voice identification modality is carried out using Gaussian Mixture Model (GMM). For face recognition, three recognition methods (Eigenface, Linear Discriminate Analysis (LDA), and Gabor filter) are used and compared. The combination of voice and face biometrics systems into a single multimodal biometrics system is performed using features fusion and scores fusion. This study shows that the best results are obtained using all the features (cepstral coefficients, statistical coefficients and voice timbre features) for voice recognition, LDA face recognition method and scores fusion for the multimodal biometrics system

Fingerprint Recognition using Fuzzy Logic with Triangular Pattern Template

DEFF Research Database (Denmark)

Hussain, Dil Muhammad Akbar

2006-01-01

A fingerprint is a pattern of ridges and valleys that exist on the surface of the finger. The uniqueness of a fingerprint is typically determined by the overall pattern of ridges and valleys as well as the local ridge structures e.g., a ridge bifurcation or a ridge ending, which are called minutiae...

Recognition of explosives fingerprints on objects for courier services using machine learning methods and laser-induced breakdown spectroscopy.

Science.gov (United States)

Moros, J; Serrano, J; Gallego, F J; Macías, J; Laserna, J J

2013-06-15

During recent years laser-induced breakdown spectroscopy (LIBS) has been considered one of the techniques with larger ability for trace detection of explosives. However, despite of the high sensitivity exhibited for this application, LIBS suffers from a limited selectivity due to difficulties in assigning the molecular origin of the spectral emissions observed. This circumstance makes the recognition of fingerprints a latent challenging problem. In the present manuscript the sorting of six explosives (chloratite, ammonal, DNT, TNT, RDX and PETN) against a broad list of potential harmless interferents (butter, fuel oil, hand cream, olive oil, …), all of them in the form of fingerprints deposited on the surfaces of objects for courier services, has been carried out. When LIBS information is processed through a multi-stage architecture algorithm built from a suitable combination of 3 learning classifiers, an unknown fingerprint may be labeled into a particular class. Neural network classifiers trained by the Levenberg-Marquardt rule were decided within 3D scatter plots projected onto the subspace of the most useful features extracted from the LIBS spectra. Experimental results demonstrate that the presented algorithm sorts fingerprints according to their hazardous character, although its spectral information is virtually identical in appearance, with rates of false negatives and false positives not beyond of 10%. These reported achievements mean a step forward in the technology readiness level of LIBS for this complex application related to defense, homeland security and force protection. Copyright © 2013 Elsevier B.V. All rights reserved.

Fingerprint Sensors: Liveness Detection Issue and Hardware based Solutions

Directory of Open Access Journals (Sweden)

Shahzad Memon

2012-01-01

Full Text Available Securing an automated and unsupervised fingerprint recognition system is one of the most critical and challenging tasks in government and commercial applications. In these systems, the detection of liveness of a finger placed on a fingerprint sensor is a major issue that needs to be addressed in order to ensure the credibility of the system. The main focus of this paper is to review the existing fingerprint sensing technologies in terms of liveness detection and discusses hardware based ‘liveness detection’ techniques reported in the literature for automatic fingerprint biometrics.

3D fingerprint imaging system based on full-field fringe projection profilometry

Science.gov (United States)

Huang, Shujun; Zhang, Zonghua; Zhao, Yan; Dai, Jie; Chen, Chao; Xu, Yongjia; Zhang, E.; Xie, Lili

2014-01-01

As an unique, unchangeable and easily acquired biometrics, fingerprint has been widely studied in academics and applied in many fields over the years. The traditional fingerprint recognition methods are based on the obtained 2D feature of fingerprint. However, fingerprint is a 3D biological characteristic. The mapping from 3D to 2D loses 1D information and causes nonlinear distortion of the captured fingerprint. Therefore, it is becoming more and more important to obtain 3D fingerprint information for recognition. In this paper, a novel 3D fingerprint imaging system is presented based on fringe projection technique to obtain 3D features and the corresponding color texture information. A series of color sinusoidal fringe patterns with optimum three-fringe numbers are projected onto a finger surface. From another viewpoint, the fringe patterns are deformed by the finger surface and captured by a CCD camera. 3D shape data of the finger can be obtained from the captured fringe pattern images. This paper studies the prototype of the 3D fingerprint imaging system, including principle of 3D fingerprint acquisition, hardware design of the 3D imaging system, 3D calibration of the system, and software development. Some experiments are carried out by acquiring several 3D fingerprint data. The experimental results demonstrate the feasibility of the proposed 3D fingerprint imaging system.

An Efficient Automatic Attendance System Using Fingerprint Reconstruction Technique

OpenAIRE

Ramakrishnan, Josphineleela; Ramakrishnan, M.

2012-01-01

Biometric time and attendance system is one of the most successful applications of biometric technology. One of the main advantage of a biometric time and attendance system is it avoids "buddy-punching". Buddy punching was a major loophole which will be exploiting in the traditional time attendance systems. Fingerprint recognition is an established field today, but still identifying individual from a set of enrolled fingerprints is a time taking process. Most fingerprint-based biometric syste...

Oriented diffusion filtering for enhancing low-quality fingerprint images

KAUST Repository

Gottschlich, C.; Schönlieb, C.-B.

2012-01-01

To enhance low-quality fingerprint images, we present a novel method that first estimates the local orientation of the fingerprint ridge and valley flow and next performs oriented diffusion filtering, followed by a locally adaptive contrast enhancement step. By applying the authors' new approach to low-quality images of the FVC2004 fingerprint databases, the authors are able to show its competitiveness with other state-of-the-art enhancement methods for fingerprints like curved Gabor filtering. A major advantage of oriented diffusion filtering over those is its computational efficiency. Combining oriented diffusion filtering with curved Gabor filters led to additional improvements and, to the best of the authors' knowledge, the lowest equal error rates achieved so far using MINDTCT and BOZORTH3 on the FVC2004 databases. The recognition performance and the computational efficiency of the method suggest to include oriented diffusion filtering as a standard image enhancement add-on module for real-time fingerprint recognition systems. In order to facilitate the reproduction of these results, an implementation of the oriented diffusion filtering for Matlab and GNU Octave is made available for download. © 2012 The Institution of Engineering and Technology.

Oriented diffusion filtering for enhancing low-quality fingerprint images

KAUST Repository

Gottschlich, C.

2012-01-01

To enhance low-quality fingerprint images, we present a novel method that first estimates the local orientation of the fingerprint ridge and valley flow and next performs oriented diffusion filtering, followed by a locally adaptive contrast enhancement step. By applying the authors\\' new approach to low-quality images of the FVC2004 fingerprint databases, the authors are able to show its competitiveness with other state-of-the-art enhancement methods for fingerprints like curved Gabor filtering. A major advantage of oriented diffusion filtering over those is its computational efficiency. Combining oriented diffusion filtering with curved Gabor filters led to additional improvements and, to the best of the authors\\' knowledge, the lowest equal error rates achieved so far using MINDTCT and BOZORTH3 on the FVC2004 databases. The recognition performance and the computational efficiency of the method suggest to include oriented diffusion filtering as a standard image enhancement add-on module for real-time fingerprint recognition systems. In order to facilitate the reproduction of these results, an implementation of the oriented diffusion filtering for Matlab and GNU Octave is made available for download. © 2012 The Institution of Engineering and Technology.

A fingerprint key binding algorithm based on vector quantization and error correction

Science.gov (United States)

Li, Liang; Wang, Qian; Lv, Ke; He, Ning

2012-04-01

In recent years, researches on seamless combination cryptosystem with biometric technologies, e.g. fingerprint recognition, are conducted by many researchers. In this paper, we propose a binding algorithm of fingerprint template and cryptographic key to protect and access the key by fingerprint verification. In order to avoid the intrinsic fuzziness of variant fingerprints, vector quantization and error correction technique are introduced to transform fingerprint template and then bind with key, after a process of fingerprint registration and extracting global ridge pattern of fingerprint. The key itself is secure because only hash value is stored and it is released only when fingerprint verification succeeds. Experimental results demonstrate the effectiveness of our ideas.

Fuzzy tricentric pharmacophore fingerprints. 1. Topological fuzzy pharmacophore triplets and adapted molecular similarity scoring schemes.

Science.gov (United States)

Bonachéra, Fanny; Parent, Benjamin; Barbosa, Frédérique; Froloff, Nicolas; Horvath, Dragos

2006-01-01

This paper introduces a novel molecular description--topological (2D) fuzzy pharmacophore triplets, 2D-FPT--using the number of interposed bonds as the measure of separation between the atoms representing pharmacophore types (hydrophobic, aromatic, hydrogen-bond donor and acceptor, cation, and anion). 2D-FPT features three key improvements with respect to the state-of-the-art pharmacophore fingerprints: (1) The first key novelty is fuzzy mapping of molecular triplets onto the basis set of pharmacophore triplets: unlike in the binary scheme where an atom triplet is set to highlight the bit of a single, best-matching basis triplet, the herein-defined fuzzy approach allows for gradual mapping of each atom triplet onto several related basis triplets, thus minimizing binary classification artifacts. (2) The second innovation is proteolytic equilibrium dependence, by explicitly considering all of the conjugated acids and bases (microspecies). 2D-FPTs are concentration-weighted (as predicted at pH=7.4) averages of microspecies fingerprints. Therefore, small structural modifications, not affecting the overall pharmacophore pattern (in the sense of classical rule-based assignment), but nevertheless triggering a pKa shift, will have a major impact on 2D-FPT. Pairs of almost identical compounds with significantly differing activities ("activity cliffs" in classical descriptor spaces) were in many cases predictable by 2D-FPT. (3) The third innovation is a new similarity scoring formula, acknowledging that the simultaneous absence of a triplet in two molecules is a less-constraining indicator of similarity than its simultaneous presence. It displays excellent neighborhood behavior, outperforming 2D or 3D two-point pharmacophore descriptors or chemical fingerprints. The 2D-FPT calculator was developed using the chemoinformatics toolkit of ChemAxon (www.chemaxon.com).

Similarity score computation for minutiae-based fingerprint recognition

CSIR Research Space (South Africa)

Khanyile, NP

2014-09-01

Full Text Available This paper identifies and analyses the factors that contribute to the similarity between two sets of minutiae points as well as the probability that two sets of minutiae points were extracted from fingerprints of the same finger. Minutiae...

Enhancing of chemical compound and drug name recognition using representative tag scheme and fine-grained tokenization.

Science.gov (United States)

Dai, Hong-Jie; Lai, Po-Ting; Chang, Yung-Chun; Tsai, Richard Tzong-Han

2015-01-01

The functions of chemical compounds and drugs that affect biological processes and their particular effect on the onset and treatment of diseases have attracted increasing interest with the advancement of research in the life sciences. To extract knowledge from the extensive literatures on such compounds and drugs, the organizers of BioCreative IV administered the CHEMical Compound and Drug Named Entity Recognition (CHEMDNER) task to establish a standard dataset for evaluating state-of-the-art chemical entity recognition methods. This study introduces the approach of our CHEMDNER system. Instead of emphasizing the development of novel feature sets for machine learning, this study investigates the effect of various tag schemes on the recognition of the names of chemicals and drugs by using conditional random fields. Experiments were conducted using combinations of different tokenization strategies and tag schemes to investigate the effects of tag set selection and tokenization method on the CHEMDNER task. This study presents the performance of CHEMDNER of three more representative tag schemes-IOBE, IOBES, and IOB12E-when applied to a widely utilized IOB tag set and combined with the coarse-/fine-grained tokenization methods. The experimental results thus reveal that the fine-grained tokenization strategy performance best in terms of precision, recall and F-scores when the IOBES tag set was utilized. The IOBES model with fine-grained tokenization yielded the best-F-scores in the six chemical entity categories other than the "Multiple" entity category. Nonetheless, no significant improvement was observed when a more representative tag schemes was used with the coarse or fine-grained tokenization rules. The best F-scores that were achieved using the developed system on the test dataset of the CHEMDNER task were 0.833 and 0.815 for the chemical documents indexing and the chemical entity mention recognition tasks, respectively. The results herein highlight the importance

A SCHEME FOR TEMPLATE SECURITY AT FEATURE FUSION LEVEL IN MULTIMODAL BIOMETRIC SYSTEM

Directory of Open Access Journals (Sweden)

Arvind Selwal

2016-09-01

Full Text Available Biometric is the science of human recognition based upon using their biological, chemical or behavioural traits. These systems are used in many real life applications simply from biometric based attendance system to providing security at very sophisticated level. A biometric system deals with raw data captured using a sensor and feature template extracted from raw image. One of the challenges being faced by designers of these systems is to secure template data extracted from the biometric modalities of the user and protect the raw images. To minimize spoof attacks on biometric systems by unauthorised users one of the solutions is to use multi-biometric systems. Multi-modal biometric system works by using fusion technique to merge feature templates generated from different modalities of the human. In this work a new scheme is proposed to secure template during feature fusion level. Scheme is based on union operation of fuzzy relations of templates of modalities during fusion process of multimodal biometric systems. This approach serves dual purpose of feature fusion as well as transformation of templates into a single secured non invertible template. The proposed technique is cancelable and experimentally tested on a bimodal biometric system comprising of fingerprint and hand geometry. Developed scheme removes the problem of an attacker learning the original minutia position in fingerprint and various measurements of hand geometry. Given scheme provides improved performance of the system with reduction in false accept rate and improvement in genuine accept rate.

Pseudo Identities Based on Fingerprint Characteristics

NARCIS (Netherlands)

Delvaux, Nicolas; Chabanne, Herve; Bringer, Julien; Kindarji, Bruno; Lindeberg, Patrik; Midgren, Johannes; Breebaart, Jeroen; Akkermans, Ton; van der Veen, M.; Veldhuis, Raymond N.J.; Kindt, Els; Simoens, Koen; Busch, Christoph; Bours, Patrick; Gafurov, Davrondzhon; Yang, Bian; Stern, Julien; Rust, Carsten; Cucinelli, Bruno; Skepastianos, Dimitrios

2008-01-01

This paper presents the integrated project TURBINE which is funded under the EU 7th research framework programme. This research is a multi-disciplinary effort on privacy enhancing technology, combining innovative developments in cryptography and fingerprint recognition. The objective of this project

Recognition of Activities of Daily Living Based on Environmental Analyses Using Audio Fingerprinting Techniques: A Systematic Review

Directory of Open Access Journals (Sweden)

Ivan Miguel Pires

2018-01-01

Full Text Available An increase in the accuracy of identification of Activities of Daily Living (ADL is very important for different goals of Enhanced Living Environments and for Ambient Assisted Living (AAL tasks. This increase may be achieved through identification of the surrounding environment. Although this is usually used to identify the location, ADL recognition can be improved with the identification of the sound in that particular environment. This paper reviews audio fingerprinting techniques that can be used with the acoustic data acquired from mobile devices. A comprehensive literature search was conducted in order to identify relevant English language works aimed at the identification of the environment of ADLs using data acquired with mobile devices, published between 2002 and 2017. In total, 40 studies were analyzed and selected from 115 citations. The results highlight several audio fingerprinting techniques, including Modified discrete cosine transform (MDCT, Mel-frequency cepstrum coefficients (MFCC, Principal Component Analysis (PCA, Fast Fourier Transform (FFT, Gaussian mixture models (GMM, likelihood estimation, logarithmic moduled complex lapped transform (LMCLT, support vector machine (SVM, constant Q transform (CQT, symmetric pairwise boosting (SPB, Philips robust hash (PRH, linear discriminant analysis (LDA and discrete cosine transform (DCT.

A novel interaction fingerprint derived from per atom score contributions: exhaustive evaluation of interaction fingerprint performance in docking based virtual screening.

Science.gov (United States)

Jasper, Julia B; Humbeck, Lina; Brinkjost, Tobias; Koch, Oliver

2018-03-16

Protein ligand interaction fingerprints are a powerful approach for the analysis and assessment of docking poses to improve docking performance in virtual screening. In this study, a novel interaction fingerprint approach (PADIF, protein per atom score contributions derived interaction fingerprint) is presented which was specifically designed for utilising the GOLD scoring functions' atom contributions together with a specific scoring scheme. This allows the incorporation of known protein-ligand complex structures for a target-specific scoring. Unlike many other methods, this approach uses weighting factors reflecting the relative frequency of a specific interaction in the references and penalizes destabilizing interactions. In addition, and for the first time, an exhaustive validation study was performed that assesses the performance of PADIF and two other interaction fingerprints in virtual screening. Here, PADIF shows superior results, and some rules of thumb for a successful use of interaction fingerprints could be identified.

Rapid Discrimination for Traditional Complex Herbal Medicines from Different Parts, Collection Time, and Origins Using High-Performance Liquid Chromatography and Near-Infrared Spectral Fingerprints with Aid of Pattern Recognition Methods

Directory of Open Access Journals (Sweden)

Haiyan Fu

2015-01-01

Full Text Available As an effective method, the fingerprint technique, which emphasized the whole compositions of samples, has already been used in various fields, especially in identifying and assessing the quality of herbal medicines. High-performance liquid chromatography (HPLC and near-infrared (NIR, with their unique characteristics of reliability, versatility, precision, and simple measurement, played an important role among all the fingerprint techniques. In this paper, a supervised pattern recognition method based on PLSDA algorithm by HPLC and NIR has been established to identify the information of Hibiscus mutabilis L. and Berberidis radix, two common kinds of herbal medicines. By comparing component analysis (PCA, linear discriminant analysis (LDA, and particularly partial least squares discriminant analysis (PLSDA with different fingerprint preprocessing of NIR spectra variables, PLSDA model showed perfect functions on the analysis of samples as well as chromatograms. Most important, this pattern recognition method by HPLC and NIR can be used to identify different collection parts, collection time, and different origins or various species belonging to the same genera of herbal medicines which proved to be a promising approach for the identification of complex information of herbal medicines.

Human ear recognition by computer

CERN Document Server

Bhanu, Bir; Chen, Hui

2010-01-01

Biometrics deals with recognition of individuals based on their physiological or behavioral characteristics. The human ear is a new feature in biometrics that has several merits over the more common face, fingerprint and iris biometrics. Unlike the fingerprint and iris, it can be easily captured from a distance without a fully cooperative subject, although sometimes it may be hidden with hair, scarf and jewellery. Also, unlike a face, the ear is a relatively stable structure that does not change much with the age and facial expressions. ""Human Ear Recognition by Computer"" is the first book o

Implementation of Minutiae Based Fingerprint Identification System Using Crossing Number Concept

Directory of Open Access Journals (Sweden)

Atul S. CHAUDHARI

2014-01-01

Full Text Available Biometric system is essentially a pattern recognition system which recognizes a person by determining the authenticity of a specific physiological (e.g., fingerprints, face, retina, iris or behavioral (e.g., gait, signature characteristic possessed by that person. Among all the presently employed biometric techniques, fingerprint identification systems have received the most attention due to the long history of fingerprints and its extensive use in forensics. Fingerprint is reliable biometric characteristic as it is unique and persistence. Fingerprint is the pattern of ridges and valleys on the surface of fingertip. However, recognizing fingerprints in poor quality images is still a very complex job, so the fingerprint image must be preprocessed before matching. It is very difficult to extract fingerprint features directly from gray scale fingerprint image. In this paper we have proposed the system which uses minutiae based matching algorithm for fingerprint identification. There are three main phases in proposed algorithm. First phase enhance the input fingerprint image by preprocessing it. The enhanced fingerprint image is converted into thinned binary image and then minutiae are extracted by using Crossing Number Concept in second phase. Third stage compares input fingerprint image (after preprocessing and minutiae extraction with fingerprint images enrolled in database and makes decision whether the input fingerprint is matched with the fingerprint stored in database or not.

Optical image encryption using QR code and multilevel fingerprints in gyrator transform domains

Science.gov (United States)

Wei, Yang; Yan, Aimin; Dong, Jiabin; Hu, Zhijuan; Zhang, Jingtao

2017-11-01

A new concept of GT encryption scheme is proposed in this paper. We present a novel optical image encryption method by using quick response (QR) code and multilevel fingerprint keys in gyrator transform (GT) domains. In this method, an original image is firstly transformed into a QR code, which is placed in the input plane of cascaded GTs. Subsequently, the QR code is encrypted into the cipher-text by using multilevel fingerprint keys. The original image can be obtained easily by reading the high-quality retrieved QR code with hand-held devices. The main parameters used as private keys are GTs' rotation angles and multilevel fingerprints. Biometrics and cryptography are integrated with each other to improve data security. Numerical simulations are performed to demonstrate the validity and feasibility of the proposed encryption scheme. In the future, the method of applying QR codes and fingerprints in GT domains possesses much potential for information security.

Off-lattice pattern recognition scheme for kinetic Monte Carlo simulations

International Nuclear Information System (INIS)

Nandipati, Giridhar; Kara, Abdelkader; Shah, Syed Islamuddin; Rahman, Talat S.

2012-01-01

We report the development of a pattern-recognition scheme for the off-lattice self-learning kinetic Monte Carlo (KMC) method, one that is simple and flexible enough that it can be applied to all types of surfaces. In this scheme, to uniquely identify the local environment and associated processes involving three-dimensional (3D) motion of an atom or atoms, space around a central atom is divided into 3D rectangular boxes. The dimensions and the number of 3D boxes are determined by the accuracy with which a process needs to be identified and a process is described as the central atom moving to a neighboring vacant box accompanied by the motion of any other atom or atoms in its surrounding boxes. As a test of this method to we apply it to examine the decay of 3D Cu islands on the Cu(100) and to the surface diffusion of a Cu monomer and a dimer on Cu(111) and compare the results and computational efficiency to those available in the literature.

The Development Of Mathematical Model For Automated Fingerprint Identification Systems Analysis

International Nuclear Information System (INIS)

Ardisasmita, M. Syamsa

2001-01-01

Fingerprint has a strong oriented and periodic structure composed of dark lines of raised skin (ridges) and clear lines of lowered skin (furrows)that twist to form a distinct pattern. Although the manner in which the ridges flow is distinctive, other characteristics of the fingerprint called m inutiae a re what are most unique to the individual. These features are particular patterns consisting of terminations or bifurcations of the ridges. To assert if two fingerprints are from the same finger or not, experts detect those minutiae. AFIS (Automated Fingerprint Identification Systems) extract and compare these features for determining a match. The classic methods of fingerprints recognition are not suitable for direct implementation in form of computer algorithms. The creation of a finger's model was however the necessity of development of new, better algorithms of analysis. This paper presents a new numerical methods of fingerprints' simulation based on mathematical model of arrangement of dermatoglyphics and creation of minutiae. This paper describes also the design and implementation of an automated fingerprint identification systems which operates in two stages: minutiae extraction and minutiae matching

Sensor Interoperability and Fusion in Fingerprint Verification: A Case Study using Minutiae-and Ridge-Based Matchers

NARCIS (Netherlands)

Alonso-Fernandez, F.; Veldhuis, Raymond N.J.; Bazen, A.M.; Fierrez-Aguilar, J.; Ortega-Garcia, J.

2006-01-01

Information fusion in fingerprint recognition has been studied in several papers. However, only a few papers have been focused on sensor interoperability and sensor fusion. In this paper, these two topics are studied using a multisensor database acquired with three different fingerprint sensors.

Large-scale systematic analysis of 2D fingerprint methods and parameters to improve virtual screening enrichments.

Science.gov (United States)

Sastry, Madhavi; Lowrie, Jeffrey F; Dixon, Steven L; Sherman, Woody

2010-05-24

A systematic virtual screening study on 11 pharmaceutically relevant targets has been conducted to investigate the interrelation between 8 two-dimensional (2D) fingerprinting methods, 13 atom-typing schemes, 13 bit scaling rules, and 12 similarity metrics using the new cheminformatics package Canvas. In total, 157 872 virtual screens were performed to assess the ability of each combination of parameters to identify actives in a database screen. In general, fingerprint methods, such as MOLPRINT2D, Radial, and Dendritic that encode information about local environment beyond simple linear paths outperformed other fingerprint methods. Atom-typing schemes with more specific information, such as Daylight, Mol2, and Carhart were generally superior to more generic atom-typing schemes. Enrichment factors across all targets were improved considerably with the best settings, although no single set of parameters performed optimally on all targets. The size of the addressable bit space for the fingerprints was also explored, and it was found to have a substantial impact on enrichments. Small bit spaces, such as 1024, resulted in many collisions and in a significant degradation in enrichments compared to larger bit spaces that avoid collisions.

Re-docking scheme for generating near-native protein complexes by assembling residue interaction fingerprints.

Directory of Open Access Journals (Sweden)

Nobuyuki Uchikoga

Full Text Available Interaction profile method is a useful method for processing rigid-body docking. After the docking process, the resulting set of docking poses could be classified by calculating similarities among them using these interaction profiles to search for near-native poses. However, there are some cases where the near-native poses are not included in this set of docking poses even when the bound-state structures are used. Therefore, we have developed a method for generating near-native docking poses by introducing a re-docking process. We devised a method for calculating the profile of interaction fingerprints by assembling protein complexes after determining certain core-protein complexes. For our analysis, we used 44 bound-state protein complexes selected from the ZDOCK benchmark dataset ver. 2.0, including some protein pairs none of which generated near-native poses in the docking process. Consequently, after the re-docking process we obtained profiles of interaction fingerprints, some of which yielded near-native poses. The re-docking process involved searching for possible docking poses in a restricted area using the profile of interaction fingerprints. If the profile includes interactions identical to those in the native complex, we obtained near-native docking poses. Accordingly, near-native poses were obtained for all bound-state protein complexes examined here. Application of interaction fingerprints to the re-docking process yielded structures with more native interactions, even when a docking pose, obtained following the initial docking process, contained only a small number of native amino acid interactions. Thus, utilization of the profile of interaction fingerprints in the re-docking process yielded more near-native poses.

Re-docking scheme for generating near-native protein complexes by assembling residue interaction fingerprints.

Science.gov (United States)

Uchikoga, Nobuyuki; Matsuzaki, Yuri; Ohue, Masahito; Hirokawa, Takatsugu; Akiyama, Yutaka

2013-01-01

Interaction profile method is a useful method for processing rigid-body docking. After the docking process, the resulting set of docking poses could be classified by calculating similarities among them using these interaction profiles to search for near-native poses. However, there are some cases where the near-native poses are not included in this set of docking poses even when the bound-state structures are used. Therefore, we have developed a method for generating near-native docking poses by introducing a re-docking process. We devised a method for calculating the profile of interaction fingerprints by assembling protein complexes after determining certain core-protein complexes. For our analysis, we used 44 bound-state protein complexes selected from the ZDOCK benchmark dataset ver. 2.0, including some protein pairs none of which generated near-native poses in the docking process. Consequently, after the re-docking process we obtained profiles of interaction fingerprints, some of which yielded near-native poses. The re-docking process involved searching for possible docking poses in a restricted area using the profile of interaction fingerprints. If the profile includes interactions identical to those in the native complex, we obtained near-native docking poses. Accordingly, near-native poses were obtained for all bound-state protein complexes examined here. Application of interaction fingerprints to the re-docking process yielded structures with more native interactions, even when a docking pose, obtained following the initial docking process, contained only a small number of native amino acid interactions. Thus, utilization of the profile of interaction fingerprints in the re-docking process yielded more near-native poses.

Laser speckle decorrelation for fingerprint acquisition

International Nuclear Information System (INIS)

Schirripa Spagnolo, Giuseppe; Cozzella, Lorenzo

2012-01-01

Biometry is gaining popularity as a physical security approach in situations where a high level of security is necessary. Currently, biometric solutions are embedded in a very large and heterogeneous group of applications. One of the most sensible is for airport security access to boarding gates. More airports are introducing biometric solutions based on face, fingerprint or iris recognition for passenger identification. In particular, fingerprints are the most widely used biometric, and they are mandatorily included in electronic identification documents. One important issue, which is difficult to address in traditional fingerprint acquisition systems, is preventing contact between subsequent users; sebum, which can be a potential vector for contagious diseases. Currently, non-contact devices are used to overcome this problem. In this paper, a new contact device based on laser speckle decorrelation is presented. Our system has the advantage of being compact and low-cost compared with an actual contactless system, allowing enhancement of the sebum pattern imaging contrast in a simple and low-cost way. Furthermore, it avoids the spreading of contagious diseases. (paper)

Holistic processing of fingerprints by expert forensic examiners.

Science.gov (United States)

Vogelsang, Macgregor D; Palmeri, Thomas J; Busey, Thomas A

2017-01-01

Holistic processing is often characterized as a process by which objects are perceived as a whole rather than a compilation of individual features. This mechanism may play an important role in the development of perceptual expertise because it allows for rapid integration across image regions. The present work explores whether holistic processing is present in latent fingerprint examiners, who compare fingerprints collected from crime scenes against a set of standards taken from a suspect. We adapted a composite task widely used in the face recognition and perceptual expertise literatures, in which participants were asked to match only a particular half of a fingerprint with a previous image while ignoring the other half. We tested both experts and novices, using both upright and inverted fingerprints. For upright fingerprints, we found weak evidence for holistic processing, but with no differences between experts and novices with respect to holistic processing. For inverted fingerprints, we found stronger evidence of holistic processing, with weak evidence for differences between experts and novices. These relatively weak holistic processing effects contrast with robust evidence for holistic processing with faces and with objects in other domains of perceptual expertise. The data constrain models of holistic processing by demonstrating that latent fingerprint experts and novices may not substantively differ in terms of the amount of holistic processing and that inverted stimuli actually produced more evidence for holistic processing than upright stimuli. Important differences between the present fingerprint stimuli and those in the literature include the lack of verbal labels for experts and the absence of strong vertical asymmetries, both of which might contribute to stronger holistic processing signatures in other stimulus domains.

Transparent Fingerprint Sensor System for Large Flat Panel Display.

Science.gov (United States)

Seo, Wonkuk; Pi, Jae-Eun; Cho, Sung Haeung; Kang, Seung-Youl; Ahn, Seong-Deok; Hwang, Chi-Sun; Jeon, Ho-Sik; Kim, Jong-Uk; Lee, Myunghee

2018-01-19

In this paper, we introduce a transparent fingerprint sensing system using a thin film transistor (TFT) sensor panel, based on a self-capacitive sensing scheme. An armorphousindium gallium zinc oxide (a-IGZO) TFT sensor array and associated custom Read-Out IC (ROIC) are implemented for the system. The sensor panel has a 200 × 200 pixel array and each pixel size is as small as 50 μm × 50 μm. The ROIC uses only eight analog front-end (AFE) amplifier stages along with a successive approximation analog-to-digital converter (SAR ADC). To get the fingerprint image data from the sensor array, the ROIC senses a capacitance, which is formed by a cover glass material between a human finger and an electrode of each pixel of the sensor array. Three methods are reviewed for estimating the self-capacitance. The measurement result demonstrates that the transparent fingerprint sensor system has an ability to differentiate a human finger's ridges and valleys through the fingerprint sensor array.

Advertisement recognition using mode voting acoustic fingerprint

Science.gov (United States)

Fahmi, Reza; Abedi Firouzjaee, Hosein; Janalizadeh Choobbasti, Ali; Mortazavi Najafabadi, S. H. E.; Safavi, Saeid

2017-12-01

Emergence of media outlets and public relations tools such as TV, radio and the Internet since the 20th century provided the companies with a good platform for advertising their goods and services. Advertisement recognition is an important task that can help companies measure the efficiency of their advertising campaigns in the market and make it possible to compare their performance with competitors in order to get better business insights. Advertisement recognition is usually performed manually with help of human labor or is done through automated methods that are mainly based on heuristics features, these methods usually lack abilities such as scalability, being able to be generalized and be used in different situations. In this paper, we present an automated method for advertisement recognition based on audio processing method that could make this process fairly simple and eliminate the human factor out of the equation. This method has ultimately been used in Miras information technology in order to monitor 56 TV channels to detect all ad video clips broadcast over some networks.

FINGERPRINT VERIFICATION IN PERSONAL IDENTIFICATION BY APPLYING LOCAL WALSH HADAMARD TRANSFORM AND GABOR COEFFICIENTS

Directory of Open Access Journals (Sweden)

K N Pushpalatha

2017-05-01

Full Text Available In an era of advanced computer technology world where innumerable services such as access to bank accounts, or access to secured data or entry to some national important organizations require authentication of genuine individual. Among all biometric personal identification systems, fingerprint recognition system is most accurate and economical technology. In this paper we have proposed fingerprint recognition system using Local Walsh Hadamard Transform (LWHT with Phase Magnitude Histograms (PMHs for feature extraction. Fingerprints display oriented texture-like patterns. Gabor filters have the property of capturing global and local texture information from blur or unclear images and filter bank provides the orientation features which are robust to image distortion and rotation. The LWHT algorithm is compared with other two approaches viz., Gabor Coefficients and Directional Features. The three methods are compared using FVC 2006 Finger print database images. It is found from the observation that the values of TSR, FAR and FRR have improved results compared to existing algorithm.

High Resolution Ultrasonic Method for 3D Fingerprint Representation in Biometrics

Science.gov (United States)

Maev, R. Gr.; Bakulin, E. Y.; Maeva, E. Y.; Severin, F. M.

Biometrics is an important field which studies different possible ways of personal identification. Among a number of existing biometric techniques fingerprint recognition stands alone - because very large database of fingerprints has already been acquired. Also, fingerprints are an important evidence that can be collected at a crime scene. Therefore, of all automated biometric techniques, especially in the field of law enforcement, fingerprint identification seems to be the most promising. Ultrasonic method of fingerprint imaging was originally introduced over a decade as the mapping of the reflection coefficient at the interface between the finger and a covering plate and has shown very good reliability and free from imperfections of previous two methods. This work introduces a newer development of the ultrasonic fingerprint imaging, focusing on the imaging of the internal structures of fingerprints (including sweat pores) with raw acoustic resolution of about 500 dpi (0.05 mm) using a scanning acoustic microscope to obtain images and acoustic data in the form of 3D data array. C-scans from different depths inside the fingerprint area of fingers of several volunteers were obtained and showed good contrast of ridges-and-valleys patterns and practically exact correspondence to the standard ink-and-paper prints of the same areas. Important feature reveled on the acoustic images was the clear appearance of the sweat pores, which could provide additional means of identification.

A Large-Scale Study of Fingerprint Matching Systems for Sensor Interoperability Problem

Directory of Open Access Journals (Sweden)

Helala AlShehri

2018-03-01

Full Text Available The fingerprint is a commonly used biometric modality that is widely employed for authentication by law enforcement agencies and commercial applications. The designs of existing fingerprint matching methods are based on the hypothesis that the same sensor is used to capture fingerprints during enrollment and verification. Advances in fingerprint sensor technology have raised the question about the usability of current methods when different sensors are employed for enrollment and verification; this is a fingerprint sensor interoperability problem. To provide insight into this problem and assess the status of state-of-the-art matching methods to tackle this problem, we first analyze the characteristics of fingerprints captured with different sensors, which makes cross-sensor matching a challenging problem. We demonstrate the importance of fingerprint enhancement methods for cross-sensor matching. Finally, we conduct a comparative study of state-of-the-art fingerprint recognition methods and provide insight into their abilities to address this problem. We performed experiments using a public database (FingerPass that contains nine datasets captured with different sensors. We analyzed the effects of different sensors and found that cross-sensor matching performance deteriorates when different sensors are used for enrollment and verification. In view of our analysis, we propose future research directions for this problem.

A Large-Scale Study of Fingerprint Matching Systems for Sensor Interoperability Problem.

Science.gov (United States)

AlShehri, Helala; Hussain, Muhammad; AboAlSamh, Hatim; AlZuair, Mansour

2018-03-28

The fingerprint is a commonly used biometric modality that is widely employed for authentication by law enforcement agencies and commercial applications. The designs of existing fingerprint matching methods are based on the hypothesis that the same sensor is used to capture fingerprints during enrollment and verification. Advances in fingerprint sensor technology have raised the question about the usability of current methods when different sensors are employed for enrollment and verification; this is a fingerprint sensor interoperability problem. To provide insight into this problem and assess the status of state-of-the-art matching methods to tackle this problem, we first analyze the characteristics of fingerprints captured with different sensors, which makes cross-sensor matching a challenging problem. We demonstrate the importance of fingerprint enhancement methods for cross-sensor matching. Finally, we conduct a comparative study of state-of-the-art fingerprint recognition methods and provide insight into their abilities to address this problem. We performed experiments using a public database (FingerPass) that contains nine datasets captured with different sensors. We analyzed the effects of different sensors and found that cross-sensor matching performance deteriorates when different sensors are used for enrollment and verification. In view of our analysis, we propose future research directions for this problem.

Binary spectral minutiae representation with multi-sample fusion for fingerprint recognition

NARCIS (Netherlands)

Xu, H.; Veldhuis, Raymond N.J.

Biometric fusion is the approach to improve the biometric system performance by combining multiple sources of biometric information. The binary spectral minutiae representation is a method to represent a fingerprint minutiae set as a fixed-length binary string. This binary representation has the

Image encryption using fingerprint as key based on phase retrieval algorithm and public key cryptography

Science.gov (United States)

Zhao, Tieyu; Ran, Qiwen; Yuan, Lin; Chi, Yingying; Ma, Jing

2015-09-01

In this paper, a novel image encryption system with fingerprint used as a secret key is proposed based on the phase retrieval algorithm and RSA public key algorithm. In the system, the encryption keys include the fingerprint and the public key of RSA algorithm, while the decryption keys are the fingerprint and the private key of RSA algorithm. If the users share the fingerprint, then the system will meet the basic agreement of asymmetric cryptography. The system is also applicable for the information authentication. The fingerprint as secret key is used in both the encryption and decryption processes so that the receiver can identify the authenticity of the ciphertext by using the fingerprint in decryption process. Finally, the simulation results show the validity of the encryption scheme and the high robustness against attacks based on the phase retrieval technique.

Transparent Fingerprint Sensor System for Large Flat Panel Display

Directory of Open Access Journals (Sweden)

Wonkuk Seo

2018-01-01

Full Text Available In this paper, we introduce a transparent fingerprint sensing system using a thin film transistor (TFT sensor panel, based on a self-capacitive sensing scheme. An armorphousindium gallium zinc oxide (a-IGZO TFT sensor array and associated custom Read-Out IC (ROIC are implemented for the system. The sensor panel has a 200 × 200 pixel array and each pixel size is as small as 50 μm × 50 μm. The ROIC uses only eight analog front-end (AFE amplifier stages along with a successive approximation analog-to-digital converter (SAR ADC. To get the fingerprint image data from the sensor array, the ROIC senses a capacitance, which is formed by a cover glass material between a human finger and an electrode of each pixel of the sensor array. Three methods are reviewed for estimating the self-capacitance. The measurement result demonstrates that the transparent fingerprint sensor system has an ability to differentiate a human finger’s ridges and valleys through the fingerprint sensor array.

A novel patterning control strategy based on real-time fingerprint recognition and adaptive wafer level scanner optimization

Science.gov (United States)

Cekli, Hakki Ergun; Nije, Jelle; Ypma, Alexander; Bastani, Vahid; Sonntag, Dag; Niesing, Henk; Zhang, Linmiao; Ullah, Zakir; Subramony, Venky; Somasundaram, Ravin; Susanto, William; Matsunobu, Masazumi; Johnson, Jeff; Tabery, Cyrus; Lin, Chenxi; Zou, Yi

2018-03-01

In addition to lithography process and equipment induced variations, processes like etching, annealing, film deposition and planarization exhibit variations, each having their own intrinsic characteristics and leaving an effect, a `fingerprint', on the wafers. With ever tighter requirements for CD and overlay, controlling these process induced variations is both increasingly important and increasingly challenging in advanced integrated circuit (IC) manufacturing. For example, the on-product overlay (OPO) requirement for future nodes is approaching process induced variance to become extremely small. Process variance control is seen as an bottleneck to further shrink which drives the need for more sophisticated process control strategies. In this context we developed a novel `computational process control strategy' which provides the capability of proactive control of each individual wafer with aim to maximize the yield, without introducing a significant impact on metrology requirements, cycle time or productivity. The complexity of the wafer process is approached by characterizing the full wafer stack building a fingerprint library containing key patterning performance parameters like Overlay, Focus, etc. Historical wafer metrology is decomposed into dominant fingerprints using Principal Component Analysis. By associating observed fingerprints with their origin e.g. process steps, tools and variables, we can give an inline assessment of the strength and origin of the fingerprints on every wafer. Once the fingerprint library is established, a wafer specific fingerprint correction recipes can be determined based on its processing history. Data science techniques are used in real-time to ensure that the library is adaptive. To realize this concept, ASML TWINSCAN scanners play a vital role with their on-board full wafer detection and exposure correction capabilities. High density metrology data is created by the scanner for each wafer and on every layer during the

Efficient iris recognition by characterizing key local variations.

Science.gov (United States)

Ma, Li; Tan, Tieniu; Wang, Yunhong; Zhang, Dexin

2004-06-01

Unlike other biometrics such as fingerprints and face, the distinct aspect of iris comes from randomly distributed features. This leads to its high reliability for personal identification, and at the same time, the difficulty in effectively representing such details in an image. This paper describes an efficient algorithm for iris recognition by characterizing key local variations. The basic idea is that local sharp variation points, denoting the appearing or vanishing of an important image structure, are utilized to represent the characteristics of the iris. The whole procedure of feature extraction includes two steps: 1) a set of one-dimensional intensity signals is constructed to effectively characterize the most important information of the original two-dimensional image; 2) using a particular class of wavelets, a position sequence of local sharp variation points in such signals is recorded as features. We also present a fast matching scheme based on exclusive OR operation to compute the similarity between a pair of position sequences. Experimental results on 2255 iris images show that the performance of the proposed method is encouraging and comparable to the best iris recognition algorithm found in the current literature.

Image Quality Assessment for Fake Biometric Detection: Application to Iris, Fingerprint, and Face Recognition.

Science.gov (United States)

Galbally, Javier; Marcel, Sébastien; Fierrez, Julian

2014-02-01

To ensure the actual presence of a real legitimate trait in contrast to a fake self-manufactured synthetic or reconstructed sample is a significant problem in biometric authentication, which requires the development of new and efficient protection measures. In this paper, we present a novel software-based fake detection method that can be used in multiple biometric systems to detect different types of fraudulent access attempts. The objective of the proposed system is to enhance the security of biometric recognition frameworks, by adding liveness assessment in a fast, user-friendly, and non-intrusive manner, through the use of image quality assessment. The proposed approach presents a very low degree of complexity, which makes it suitable for real-time applications, using 25 general image quality features extracted from one image (i.e., the same acquired for authentication purposes) to distinguish between legitimate and impostor samples. The experimental results, obtained on publicly available data sets of fingerprint, iris, and 2D face, show that the proposed method is highly competitive compared with other state-of-the-art approaches and that the analysis of the general image quality of real biometric samples reveals highly valuable information that may be very efficiently used to discriminate them from fake traits.

High Resolution Ultrasonic Method for 3D Fingerprint Recognizable Characteristics in Biometrics Identification

Science.gov (United States)

Maev, R. Gr.; Bakulin, E. Yu.; Maeva, A.; Severin, F.

Biometrics is a rapidly evolving scientific and applied discipline that studies possible ways of personal identification by means of unique biological characteristics. Such identification is important in various situations requiring restricted access to certain areas, information and personal data and for cases of medical emergencies. A number of automated biometric techniques have been developed, including fingerprint, hand shape, eye and facial recognition, thermographic imaging, etc. All these techniques differ in the recognizable parameters, usability, accuracy and cost. Among these, fingerprint recognition stands alone since a very large database of fingerprints has already been acquired. Also, fingerprints are key evidence left at a crime scene and can be used to indentify suspects. Therefore, of all automated biometric techniques, especially in the field of law enforcement, fingerprint identification seems to be the most promising. We introduce a newer development of the ultrasonic fingerprint imaging. The proposed method obtains a scan only once and then varies the C-scan gate position and width to visualize acoustic reflections from any appropriate depth inside the skin. Also, B-scans and A-scans can be recreated from any position using such data array, which gives the control over the visualization options. By setting the C-scan gate deeper inside the skin, distribution of the sweat pores (which are located along the ridges) can be easily visualized. This distribution should be unique for each individual so this provides a means of personal identification, which is not affected by any changes (accidental or intentional) of the fingers' surface conditions. This paper discusses different setups, acoustic parameters of the system, signal and image processing options and possible ways of 3-dimentional visualization that could be used as a recognizable characteristic in biometric identification.

SURVEY OF BIOMETRIC SYSTEMS USING IRIS RECOGNITION

OpenAIRE

S.PON SANGEETHA; DR.M.KARNAN

2014-01-01

The security plays an important role in any type of organization in today’s life. Iris recognition is one of the leading automatic biometric systems in the area of security which is used to identify the individual person. Biometric systems include fingerprints, facial features, voice recognition, hand geometry, handwriting, the eye retina and the most secured one presented in this paper, the iris recognition. Biometric systems has become very famous in security systems because it is not possi...

Person recognition using fingerprints and top-view finger images

Directory of Open Access Journals (Sweden)

Panyayot Chaikan

2010-03-01

Full Text Available Our multimodal biometric system combines fingerprinting with a top-view finger image captured by a CCD camera without user intervention. The greyscale image is preprocessed to enhance its edges, skin furrows, and the nail shape before being manipulated by a bank of oriented filters. A square tessellation is applied to the filtered image to create a feature map, called a NailCode, which is employed in Euclidean distance computations. The NailCode reduces system errors by 17.68% in the verification mode, and by 6.82% in the identification mode.

Efficient and Secure Fingerprint Verification for Embedded Devices

Directory of Open Access Journals (Sweden)

Sakiyama Kazuo

2006-01-01

Full Text Available This paper describes a secure and memory-efficient embedded fingerprint verification system. It shows how a fingerprint verification module originally developed to run on a workstation can be transformed and optimized in a systematic way to run real-time on an embedded device with limited memory and computation power. A complete fingerprint recognition module is a complex application that requires in the order of 1000 M unoptimized floating-point instruction cycles. The goal is to run both the minutiae extraction and the matching engines on a small embedded processor, in our case a 50 MHz LEON-2 softcore. It does require optimization and acceleration techniques at each design step. In order to speed up the fingerprint signal processing phase, we propose acceleration techniques at the algorithm level, at the software level to reduce the execution cycle number, and at the hardware level to distribute the system work load. Thirdly, a memory trace map-based memory reduction strategy is used for lowering the system memory requirement. Lastly, at the hardware level, it requires the development of specialized coprocessors. As results of these optimizations, we achieve a 65% reduction on the execution time and a 67% reduction on the memory storage requirement for the minutiae extraction process, compared against the reference implementation. The complete operation, that is, fingerprint capture, feature extraction, and matching, can be done in real-time of less than 4 seconds

Traceability and Quality Control in Traditional Chinese Medicine: From Chemical Fingerprint to Two-Dimensional Barcode

Directory of Open Access Journals (Sweden)

Yong Cai

2015-01-01

Full Text Available Chemical fingerprinting is currently a widely used tool that enables rapid and accurate quality evaluation of Traditional Chinese Medicine (TCM. However, chemical fingerprints are not amenable to information storage, recognition, and retrieval, which limit their use in Chinese medicine traceability. In this study, samples of three kinds of Chinese medicines were randomly selected and chemical fingerprints were then constructed by using high performance liquid chromatography. Based on chemical data, the process of converting the TCM chemical fingerprint into two-dimensional code is presented; preprocess and filtering algorithm are also proposed aiming at standardizing the large amount of original raw data. In order to know which type of two-dimensional code (2D is suitable for storing data of chemical fingerprints, current popular types of 2D codes are analyzed and compared. Results show that QR Code is suitable for recording the TCM chemical fingerprint. The fingerprint information of TCM can be converted into data format that can be stored as 2D code for traceability and quality control.

An SDN-Based Fingerprint Hopping Method to Prevent Fingerprinting Attacks

Directory of Open Access Journals (Sweden)

Zheng Zhao

2017-01-01

Full Text Available Fingerprinting attacks are one of the most severe threats to the security of networks. Fingerprinting attack aims to obtain the operating system information of target hosts to make preparations for future attacks. In this paper, a fingerprint hopping method (FPH is proposed based on software-defined networks to defend against fingerprinting attacks. FPH introduces the idea of moving target defense to show a hopping fingerprint toward the fingerprinting attackers. The interaction of the fingerprinting attack and its defense is modeled as a signal game, and the equilibriums of the game are analyzed to develop an optimal defense strategy. Experiments show that FPH can resist fingerprinting attacks effectively.

On the use of spectral minutiae in high-resolution palmprint recognition

NARCIS (Netherlands)

Wang, Ruifang; Veldhuis, Raymond N.J.; Ramos, Daniel; Spreeuwers, Lieuwe Jan; Fierrez, Julian; Xu, H.

2013-01-01

The spectral minutiae representation has been proposed as a novel method to minutiae-based fingerprint recognition, which can handle minutiae translation and rotation and improve matching speed. As high-resolution palmprint recognition is also mainly based on minutiae sets, we apply spectral

Advanced Fingerprint Analysis Project Fingerprint Constituents

Energy Technology Data Exchange (ETDEWEB)

GM Mong; CE Petersen; TRW Clauss

1999-10-29

The work described in this report was focused on generating fundamental data on fingerprint components which will be used to develop advanced forensic techniques to enhance fluorescent detection, and visualization of latent fingerprints. Chemical components of sweat gland secretions are well documented in the medical literature and many chemical techniques are available to develop latent prints, but there have been no systematic forensic studies of fingerprint sweat components or of the chemical and physical changes these substances undergo over time.

2011 Mars - Refresher presentation - General principles of the Merit, Appraisal and Recognition Scheme

CERN Multimedia

HR Department

2010-01-01

Staff members are invited to attend one of the following three information sessions that shall outline the general principles of the 2011 annual Merit, Appraisal and Recognition Scheme (MARS). Monday 10 January at 16:00-17:00 BE Auditorium Prévessin (864-1-D-02) – French;   Tuesday 11 January at 15:00-16:00 – Council Chamber (503-1-001) – English;   Thursday 13 January at 15:00-16:00 - Kjell Johnsen Auditorium (30-7-018) – French. General information on the MARS exercise may also be found on the Human Resources website: https://hr-eguide.web.cern.ch/hr-eguide/mars/mars.asp Tel. 70674 / 72728

Can soft biometric traits assist user recognition?

Science.gov (United States)

Jain, Anil K.; Dass, Sarat C.; Nandakumar, Karthik

2004-08-01

Biometrics is rapidly gaining acceptance as the technology that can meet the ever increasing need for security in critical applications. Biometric systems automatically recognize individuals based on their physiological and behavioral characteristics. Hence, the fundamental requirement of any biometric recognition system is a human trait having several desirable properties like universality, distinctiveness, permanence, collectability, acceptability, and resistance to circumvention. However, a human characteristic that possesses all these properties has not yet been identified. As a result, none of the existing biometric systems provide perfect recognition and there is a scope for improving the performance of these systems. Although characteristics like gender, ethnicity, age, height, weight and eye color are not unique and reliable, they provide some information about the user. We refer to these characteristics as "soft" biometric traits and argue that these traits can complement the identity information provided by the primary biometric identifiers like fingerprint and face. This paper presents the motivation for utilizing soft biometric information and analyzes how the soft biometric traits can be automatically extracted and incorporated in the decision making process of the primary biometric system. Preliminary experiments were conducted on a fingerprint database of 160 users by synthetically generating soft biometric traits like gender, ethnicity, and height based on known statistics. The results show that the use of additional soft biometric user information significantly improves (approximately 6%) the recognition performance of the fingerprint biometric system.

Assessing the varietal origin of extra-virgin olive oil using liquid chromatography fingerprints of phenolic compound, data fusion and chemometrics.

Science.gov (United States)

Bajoub, Aadil; Medina-Rodríguez, Santiago; Gómez-Romero, María; Ajal, El Amine; Bagur-González, María Gracia; Fernández-Gutiérrez, Alberto; Carrasco-Pancorbo, Alegría

2017-01-15

High Performance Liquid Chromatography (HPLC) with diode array (DAD) and fluorescence (FLD) detection was used to acquire the fingerprints of the phenolic fraction of monovarietal extra-virgin olive oils (extra-VOOs) collected over three consecutive crop seasons (2011/2012-2013/2014). The chromatographic fingerprints of 140 extra-VOO samples processed from olive fruits of seven olive varieties, were recorded and statistically treated for varietal authentication purposes. First, DAD and FLD chromatographic-fingerprint datasets were separately processed and, subsequently, were joined using "Low-level" and "Mid-Level" data fusion methods. After the preliminary examination by principal component analysis (PCA), three supervised pattern recognition techniques, Partial Least Squares Discriminant Analysis (PLS-DA), Soft Independent Modeling of Class Analogies (SIMCA) and K-Nearest Neighbors (k-NN) were applied to the four chromatographic-fingerprinting matrices. The classification models built were very sensitive and selective, showing considerably good recognition and prediction abilities. The combination "chromatographic dataset+chemometric technique" allowing the most accurate classification for each monovarietal extra-VOO was highlighted. Copyright © 2016 Elsevier Ltd. All rights reserved.

CSI Frequency Domain Fingerprint-Based Passive Indoor Human Detection

Directory of Open Access Journals (Sweden)

Chong Han

2018-04-01

Full Text Available Passive indoor personnel detection technology is now a hot topic. Existing methods have been greatly influenced by environmental changes, and there are problems with the accuracy and robustness of detection. Passive personnel detection based on Wi-Fi not only solves the above problems, but also has the advantages of being low cost and easy to implement, and can be better applied to elderly care and safety monitoring. In this paper, we propose a passive indoor personnel detection method based on Wi-Fi, which we call FDF-PIHD (Frequency Domain Fingerprint-based Passive Indoor Human Detection. Through this method, fine-grained physical layer Channel State Information (CSI can be extracted to generate feature fingerprints so as to help determine the state in the scene by matching online fingerprints with offline fingerprints. In order to improve accuracy, we combine the detection results of three receiving antennas to obtain the final test result. The experimental results show that the detection rates of our proposed scheme all reach above 90%, no matter whether the scene is human-free, stationary or a moving human presence. In addition, it can not only detect whether there is a target indoors, but also determine the current state of the target.

Fingerprint authentication via joint transform correlator and its application in remote access control of a 3D microscopic system

Science.gov (United States)

He, Wenqi; Lai, Hongji; Wang, Meng; Liu, Zeyi; Yin, Yongkai; Peng, Xiang

2014-05-01

We present a fingerprint authentication scheme based on the optical joint transform correlator (JTC) and further describe its application to the remote access control of a Network-based Remote Laboratory (NRL). It is built to share a 3D microscopy system of our realistic laboratory in Shenzhen University with the remote co-researchers in Stuttgart University. In this article, we would like to focus on the involved security issues, mainly on the verification of various remote visitors to our NRL. By making use of the JTC-based optical pattern recognition technique as well as the Personal Identification Number (PIN), we are able to achieve the aim of authentication and access control for any remote visitors. Note that only the authorized remote visitors could be guided to the Virtual Network Computer (VNC), a cross-platform software, which allows the remote visitor to access the desktop applications and visually manipulate the instruments of our NRL through the internet. Specifically to say, when a remote visitor attempts to access to our NRL, a PIN is mandatory required in advance, which is followed by fingerprint capturing and verification. Only if both the PIN and the fingerprint are correct, can one be regarded as an authorized visitor, and then he/she would get the authority to visit our NRL by the VNC. It is also worth noting that the aforementioned "two-step verification" strategy could be further applied to verify the identity levels of various remote visitors, and therefore realize the purpose of diversified visitor management.

Towards secondary fingerprint classification

CSIR Research Space (South Africa)

Msiza, IS

2011-07-01

Full Text Available an accuracy figure of 76.8%. This small difference between the two figures is indicative of the validity of the proposed secondary classification module. Keywords?fingerprint core; fingerprint delta; primary classifi- cation; secondary classification I..., namely, the fingerprint core and the fingerprint delta. Forensically, a fingerprint core is defined as the innermost turning point where the fingerprint ridges form a loop, while the fingerprint delta is defined as the point where these ridges form a...

Chemical fingerprints encode mother–offspring similarity, colony membership, relatedness, and genetic quality in fur seals

Science.gov (United States)

Stoffel, Martin A.; Caspers, Barbara A.; Forcada, Jaume; Giannakara, Athina; Baier, Markus; Eberhart-Phillips, Luke; Müller, Caroline; Hoffman, Joseph I.

2015-01-01

Chemical communication underpins virtually all aspects of vertebrate social life, yet remains poorly understood because of its highly complex mechanistic basis. We therefore used chemical fingerprinting of skin swabs and genetic analysis to explore the chemical cues that may underlie mother–offspring recognition in colonially breeding Antarctic fur seals. By sampling mother–offspring pairs from two different colonies, using a variety of statistical approaches and genotyping a large panel of microsatellite loci, we show that colony membership, mother–offspring similarity, heterozygosity, and genetic relatedness are all chemically encoded. Moreover, chemical similarity between mothers and offspring reflects a combination of genetic and environmental influences, the former partly encoded by substances resembling known pheromones. Our findings reveal the diversity of information contained within chemical fingerprints and have implications for understanding mother–offspring communication, kin recognition, and mate choice. PMID:26261311

Machine-assisted verification of latent fingerprints: first results for nondestructive contact-less optical acquisition techniques with a CWL sensor

Science.gov (United States)

Hildebrandt, Mario; Kiltz, Stefan; Krapyvskyy, Dmytro; Dittmann, Jana; Vielhauer, Claus; Leich, Marcus

2011-11-01

A machine-assisted analysis of traces from crime scenes might be possible with the advent of new high-resolution non-destructive contact-less acquisition techniques for latent fingerprints. This requires reliable techniques for the automatic extraction of fingerprint features from latent and exemplar fingerprints for matching purposes using pattern recognition approaches. Therefore, we evaluate the NIST Biometric Image Software for the feature extraction and verification of contact-lessly acquired latent fingerprints to determine potential error rates. Our exemplary test setup includes 30 latent fingerprints from 5 people in two test sets that are acquired from different surfaces using a chromatic white light sensor. The first test set includes 20 fingerprints on two different surfaces. It is used to determine the feature extraction performance. The second test set includes one latent fingerprint on 10 different surfaces and an exemplar fingerprint to determine the verification performance. This utilized sensing technique does not require a physical or chemical visibility enhancement of the fingerprint residue, thus the original trace remains unaltered for further investigations. No particular feature extraction and verification techniques have been applied to such data, yet. Hence, we see the need for appropriate algorithms that are suitable to support forensic investigations.

2013 MARS – Refresher presentation | General principles of the Merit, Appraisal and Recognition Scheme

CERN Multimedia

2013-01-01

Staff members are invited to attend one of the three following information sessions that shall outline the general principles of the 2013 annual Merit, Appraisal and Recognition Scheme (MARS).   Monday 14 January at 10:00-11:30 – Filtration Plant (222-R-001) Thursday 17 January at 10:00-11:30 – Kjell Johnsen Auditorium (30-7-018) Monday 21 January at 10:00-11:30 - BE Amphitheatre Prévessin (864-1-D02)   General information on the MARS exercise may also be found in the CERN admin e-guide: https://admin-eguide.web.cern.ch/admin-eguide/mars/mars.asp. Human Resources Department Tel. 72728

Low-effort place recognition with WiFi fingerprints using deep learning

OpenAIRE

Nowicki, Michał; Wietrzykowski, Jan

2016-01-01

Using WiFi signals for indoor localization is the main localization modality of the existing personal indoor localization systems operating on mobile devices. WiFi fingerprinting is also used for mobile robots, as WiFi signals are usually available indoors and can provide rough initial position estimate or can be used together with other positioning systems. Currently, the best solutions rely on filtering, manual data analysis, and time-consuming parameter tuning to achieve reliable and accur...

Optimal Face-Iris Multimodal Fusion Scheme

Directory of Open Access Journals (Sweden)

Omid Sharifi

2016-06-01

Full Text Available Multimodal biometric systems are considered a way to minimize the limitations raised by single traits. This paper proposes new schemes based on score level, feature level and decision level fusion to efficiently fuse face and iris modalities. Log-Gabor transformation is applied as the feature extraction method on face and iris modalities. At each level of fusion, different schemes are proposed to improve the recognition performance and, finally, a combination of schemes at different fusion levels constructs an optimized and robust scheme. In this study, CASIA Iris Distance database is used to examine the robustness of all unimodal and multimodal schemes. In addition, Backtracking Search Algorithm (BSA, a novel population-based iterative evolutionary algorithm, is applied to improve the recognition accuracy of schemes by reducing the number of features and selecting the optimized weights for feature level and score level fusion, respectively. Experimental results on verification rates demonstrate a significant improvement of proposed fusion schemes over unimodal and multimodal fusion methods.

Performance Assessment Method for a Forged Fingerprint Detection Algorithm

Science.gov (United States)

Shin, Yong Nyuo; Jun, In-Kyung; Kim, Hyun; Shin, Woochang

The threat of invasion of privacy and of the illegal appropriation of information both increase with the expansion of the biometrics service environment to open systems. However, while certificates or smart cards can easily be cancelled and reissued if found to be missing, there is no way to recover the unique biometric information of an individual following a security breach. With the recognition that this threat factor may disrupt the large-scale civil service operations approaching implementation, such as electronic ID cards and e-Government systems, many agencies and vendors around the world continue to develop forged fingerprint detection technology, but no objective performance assessment method has, to date, been reported. Therefore, in this paper, we propose a methodology designed to evaluate the objective performance of the forged fingerprint detection technology that is currently attracting a great deal of attention.

Iris image recognition wavelet filter-banks based iris feature extraction schemes

CERN Document Server

Rahulkar, Amol D

2014-01-01

This book provides the new results in wavelet filter banks based feature extraction, and the classifier in the field of iris image recognition. It provides the broad treatment on the design of separable, non-separable wavelets filter banks, and the classifier. The design techniques presented in the book are applied on iris image analysis for person authentication. This book also brings together the three strands of research (wavelets, iris image analysis, and classifier). It compares the performance of the presented techniques with state-of-the-art available schemes. This book contains the compilation of basic material on the design of wavelets that avoids reading many different books. Therefore, it provide an easier path for the new-comers, researchers to master the contents. In addition, the designed filter banks and classifier can also be effectively used than existing filter-banks in many signal processing applications like pattern classification, data-compression, watermarking, denoising etc.  that will...

An application of viola jones method for face recognition for absence process efficiency

Science.gov (United States)

Rizki Damanik, Rudolfo; Sitanggang, Delima; Pasaribu, Hendra; Siagian, Hendrik; Gulo, Frisman

2018-04-01

Absence was a list of documents that the company used to record the attendance time of each employee. The most common problem in a fingerprint machine is the identification of a slow sensor or a sensor not recognizing a finger. The employees late to work because they get difficulties at fingerprint system, they need about 3 – 5 minutes to absence when the condition of finger is wet or not fit. To overcome this problem, this research tried to utilize facial recognition for attendance process. The method used for facial recognition was Viola Jones. Through the processing phase of the RGB face image was converted into a histogram equalization face image for the next stage of recognition. The result of this research was the absence process could be done less than 1 second with a maximum slope of ± 700 and a distance of 20-200 cm. After implement facial recognition the process of absence is more efficient, just take less 1 minute to absence.

Evaluating the change in fingerprint directional patterns under variation of rotation and number of regions

CSIR Research Space (South Africa)

Dorasamy, K

2015-09-01

Full Text Available Directional Patterns, which are formed by grouping regions of orientation fields falling within a specific range, vary under rotation and the number of regions. For fingerprint classification schemes, this can result in missclassification due...

A Support Vector Machine Approach for Truncated Fingerprint Image Detection from Sweeping Fingerprint Sensors

Science.gov (United States)

Chen, Chi-Jim; Pai, Tun-Wen; Cheng, Mox

2015-01-01

A sweeping fingerprint sensor converts fingerprints on a row by row basis through image reconstruction techniques. However, a built fingerprint image might appear to be truncated and distorted when the finger was swept across a fingerprint sensor at a non-linear speed. If the truncated fingerprint images were enrolled as reference targets and collected by any automated fingerprint identification system (AFIS), successful prediction rates for fingerprint matching applications would be decreased significantly. In this paper, a novel and effective methodology with low time computational complexity was developed for detecting truncated fingerprints in a real time manner. Several filtering rules were implemented to validate existences of truncated fingerprints. In addition, a machine learning method of supported vector machine (SVM), based on the principle of structural risk minimization, was applied to reject pseudo truncated fingerprints containing similar characteristics of truncated ones. The experimental result has shown that an accuracy rate of 90.7% was achieved by successfully identifying truncated fingerprint images from testing images before AFIS enrollment procedures. The proposed effective and efficient methodology can be extensively applied to all existing fingerprint matching systems as a preliminary quality control prior to construction of fingerprint templates. PMID:25835186

A Support Vector Machine Approach for Truncated Fingerprint Image Detection from Sweeping Fingerprint Sensors

Directory of Open Access Journals (Sweden)

Chi-Jim Chen

2015-03-01

Full Text Available A sweeping fingerprint sensor converts fingerprints on a row by row basis through image reconstruction techniques. However, a built fingerprint image might appear to be truncated and distorted when the finger was swept across a fingerprint sensor at a non-linear speed. If the truncated fingerprint images were enrolled as reference targets and collected by any automated fingerprint identification system (AFIS, successful prediction rates for fingerprint matching applications would be decreased significantly. In this paper, a novel and effective methodology with low time computational complexity was developed for detecting truncated fingerprints in a real time manner. Several filtering rules were implemented to validate existences of truncated fingerprints. In addition, a machine learning method of supported vector machine (SVM, based on the principle of structural risk minimization, was applied to reject pseudo truncated fingerprints containing similar characteristics of truncated ones. The experimental result has shown that an accuracy rate of 90.7% was achieved by successfully identifying truncated fingerprint images from testing images before AFIS enrollment procedures. The proposed effective and efficient methodology can be extensively applied to all existing fingerprint matching systems as a preliminary quality control prior to construction of fingerprint templates.

The biometric recognition on contactless multi-spectrum finger images

Science.gov (United States)

Kang, Wenxiong; Chen, Xiaopeng; Wu, Qiuxia

2015-01-01

This paper presents a novel multimodal biometric system based on contactless multi-spectrum finger images, which aims to deal with the limitations of unimodal biometrics. The chief merits of the system are the richness of the permissible texture and the ease of data access. We constructed a multi-spectrum instrument to simultaneously acquire three different types of biometrics from a finger: contactless fingerprint, finger vein, and knuckleprint. On the basis of the samples with these characteristics, a moderate database was built for the evaluation of our system. Considering the real-time requirements and the respective characteristics of the three biometrics, the block local binary patterns algorithm was used to extract features and match for the fingerprints and finger veins, while the Oriented FAST and Rotated BRIEF algorithm was applied for knuckleprints. Finally, score-level fusion was performed on the matching results from the aforementioned three types of biometrics. The experiments showed that our proposed multimodal biometric recognition system achieves an equal error rate of 0.109%, which is 88.9%, 94.6%, and 89.7% lower than the individual fingerprint, knuckleprint, and finger vein recognitions, respectively. Nevertheless, our proposed system also satisfies the real-time requirements of the applications.

FingerScanner: Embedding a Fingerprint Scanner in a Raspberry Pi

Directory of Open Access Journals (Sweden)

Jordi Sapes

2016-02-01

Full Text Available Nowadays, researchers are paying increasing attention to embedding systems. Cost reduction has lead to an increase in the number of platforms supporting the operating system Linux, jointly with the Raspberry Pi motherboard. Thus, embedding devices on Raspberry-Linux systems is a goal in order to make competitive commercial products. This paper presents a low-cost fingerprint recognition system embedded into a Raspberry Pi with Linux.

Anti-spoof touchless 3D fingerprint recognition system using single shot fringe projection and biospeckle analysis

Science.gov (United States)

Chatterjee, Amit; Bhatia, Vimal; Prakash, Shashi

2017-08-01

Fingerprint is a unique, un-alterable and easily collected biometric of a human being. Although it is a 3D biological characteristic, traditional methods are designed to provide only a 2D image. This touch based mapping of 3D shape to 2D image losses information and leads to nonlinear distortions. Moreover, as only topographic details are captured, conventional systems are potentially vulnerable to spoofing materials (e.g. artificial fingers, dead fingers, false prints, etc.). In this work, we demonstrate an anti-spoof touchless 3D fingerprint detection system using a combination of single shot fringe projection and biospeckle analysis. For fingerprint detection using fringe projection, light from a low power LED source illuminates a finger through a sinusoidal grating. The fringe pattern modulated because of features on the fingertip is captured using a CCD camera. Fourier transform method based frequency filtering is used for the reconstruction of 3D fingerprint from the captured fringe pattern. In the next step, for spoof detection using biospeckle analysis a visuo-numeric algorithm based on modified structural function and non-normalized histogram is proposed. High activity biospeckle patterns are generated because of interaction of collimated laser light with internal fluid flow of the real finger sample. This activity reduces abruptly in case of layered fake prints, and is almost absent in dead or fake fingers. Furthermore, the proposed setup is fast, low-cost, involves non-mechanical scanning and is highly stable.

Development of oil hydrocarbon fingerprinting and identification techniques

International Nuclear Information System (INIS)

Wang Zhendi; Fingas, Merv F.

2003-01-01

Oil, refined product, and pyrogenic hydrocarbons are the most frequently discovered contaminants in the environment. To effectively determine the fate of spilled oil in the environment and to successfully identify source(s) of spilled oil and petroleum products is, therefore, extremely important in many oil-related environmental studies and liability cases. This article briefly reviews the recent development of chemical analysis methodologies which are most frequently used in oil spill characterization and identification studies and environmental forensic investigations. The fingerprinting and data interpretation techniques discussed include oil spill identification protocol, tiered analytical approach, generic features and chemical composition of oils, effects of weathering on hydrocarbon fingerprinting, recognition of distribution patterns of petroleum hydrocarbons, oil type screening and differentiation, analysis of 'source-specific marker' compounds, determination of diagnostic ratios of specific oil constituents, stable isotopic analysis, application of various statistical and numerical analysis tools, and application of other analytical techniques. The issue of how biogenic and pyrogenic hydrocarbons are distinguished from petrogenic hydrocarbons is also addressed

Angstrom-Resolution Magnetic Resonance Imaging of Single Molecules via Wave-Function Fingerprints of Nuclear Spins

Science.gov (United States)

Ma, Wen-Long; Liu, Ren-Bao

2016-08-01

Single-molecule sensitivity of nuclear magnetic resonance (NMR) and angstrom resolution of magnetic resonance imaging (MRI) are the highest challenges in magnetic microscopy. Recent development in dynamical-decoupling- (DD) enhanced diamond quantum sensing has enabled single-nucleus NMR and nanoscale NMR. Similar to conventional NMR and MRI, current DD-based quantum sensing utilizes the "frequency fingerprints" of target nuclear spins. The frequency fingerprints by their nature cannot resolve different nuclear spins that have the same noise frequency or differentiate different types of correlations in nuclear-spin clusters, which limit the resolution of single-molecule MRI. Here we show that this limitation can be overcome by using "wave-function fingerprints" of target nuclear spins, which is much more sensitive than the frequency fingerprints to the weak hyperfine interaction between the targets and a sensor under resonant DD control. We demonstrate a scheme of angstrom-resolution MRI that is capable of counting and individually localizing single nuclear spins of the same frequency and characterizing the correlations in nuclear-spin clusters. A nitrogen-vacancy-center spin sensor near a diamond surface, provided that the coherence time is improved by surface engineering in the near future, may be employed to determine with angstrom resolution the positions and conformation of single molecules that are isotope labeled. The scheme in this work offers an approach to breaking the resolution limit set by the "frequency gradients" in conventional MRI and to reaching the angstrom-scale resolution.

Fingerprint pores extractor

CSIR Research Space (South Africa)

Mngenge, NA

2012-11-01

Full Text Available , this is not always the case because of diseases and hash working conditions that affect fingerprints. In order to maintain high level of security independent of varying fingerprint image quality research suggests the use of other fingerprint features to compliment...

Magnetic Resonance Fingerprinting with short relaxation intervals.

Science.gov (United States)

Amthor, Thomas; Doneva, Mariya; Koken, Peter; Sommer, Karsten; Meineke, Jakob; Börnert, Peter

2017-09-01

The aim of this study was to investigate a technique for improving the performance of Magnetic Resonance Fingerprinting (MRF) in repetitive sampling schemes, in particular for 3D MRF acquisition, by shortening relaxation intervals between MRF pulse train repetitions. A calculation method for MRF dictionaries adapted to short relaxation intervals and non-relaxed initial spin states is presented, based on the concept of stationary fingerprints. The method is applicable to many different k-space sampling schemes in 2D and 3D. For accuracy analysis, T 1 and T 2 values of a phantom are determined by single-slice Cartesian MRF for different relaxation intervals and are compared with quantitative reference measurements. The relevance of slice profile effects is also investigated in this case. To further illustrate the capabilities of the method, an application to in-vivo spiral 3D MRF measurements is demonstrated. The proposed computation method enables accurate parameter estimation even for the shortest relaxation intervals, as investigated for different sampling patterns in 2D and 3D. In 2D Cartesian measurements, we achieved a scan acceleration of more than a factor of two, while maintaining acceptable accuracy: The largest T 1 values of a sample set deviated from their reference values by 0.3% (longest relaxation interval) and 2.4% (shortest relaxation interval). The largest T 2 values showed systematic deviations of up to 10% for all relaxation intervals, which is discussed. The influence of slice profile effects for multislice acquisition is shown to become increasingly relevant for short relaxation intervals. In 3D spiral measurements, a scan time reduction of 36% was achieved, maintaining the quality of in-vivo T1 and T2 maps. Reducing the relaxation interval between MRF sequence repetitions using stationary fingerprint dictionaries is a feasible method to improve the scan efficiency of MRF sequences. The method enables fast implementations of 3D spatially

A New Approach for Fingerprint Image Compression

Energy Technology Data Exchange (ETDEWEB)

Mazieres, Bertrand

1997-12-01

The FBI has been collecting fingerprint cards since 1924 and now has over 200 million of them. Digitized with 8 bits of grayscale resolution at 500 dots per inch, it means 2000 terabytes of information. Also, without any compression, transmitting a 10 Mb card over a 9600 baud connection will need 3 hours. Hence we need a compression and a compression as close to lossless as possible: all fingerprint details must be kept. A lossless compression usually do not give a better compression ratio than 2:1, which is not sufficient. Compressing these images with the JPEG standard leads to artefacts which appear even at low compression rates. Therefore the FBI has chosen in 1993 a scheme of compression based on a wavelet transform, followed by a scalar quantization and an entropy coding : the so-called WSQ. This scheme allows to achieve compression ratios of 20:1 without any perceptible loss of quality. The publication of the FBI specifies a decoder, which means that many parameters can be changed in the encoding process: the type of analysis/reconstruction filters, the way the bit allocation is made, the number of Huffman tables used for the entropy coding. The first encoder used 9/7 filters for the wavelet transform and did the bit allocation using a high-rate bit assumption. Since the transform is made into 64 subbands, quite a lot of bands receive only a few bits even at an archival quality compression rate of 0.75 bit/pixel. Thus, after a brief overview of the standard, we will discuss a new approach for the bit-allocation that seems to make more sense where theory is concerned. Then we will talk about some implementation aspects, particularly for the new entropy coder and the features that allow other applications than fingerprint image compression. Finally, we will compare the performances of the new encoder to those of the first encoder.

Distorted Fingerprint Verification System

Directory of Open Access Journals (Sweden)

Divya KARTHIKAESHWARAN

2011-01-01

Full Text Available Fingerprint verification is one of the most reliable personal identification methods. Fingerprint matching is affected by non-linear distortion introduced in fingerprint impression during the image acquisition process. This non-linear deformation changes both the position and orientation of minutiae. The proposed system operates in three stages: alignment based fingerprint matching, fuzzy clustering and classifier framework. First, an enhanced input fingerprint image has been aligned with the template fingerprint image and matching score is computed. To improve the performance of the system, a fuzzy clustering based on distance and density has been used to cluster the feature set obtained from the fingerprint matcher. Finally a classifier framework has been developed and found that cost sensitive classifier produces better results. The system has been evaluated on fingerprint database and the experimental result shows that system produces a verification rate of 96%. This system plays an important role in forensic and civilian applications.

A cancelable biometric scheme based on multi-lead ECGs.

Science.gov (United States)

Peng-Tzu Chen; Shun-Chi Wu; Jui-Hsuan Hsieh

2017-07-01

Biometric technologies offer great advantages over other recognition methods, but there are concerns that they may compromise the privacy of individuals. In this paper, an electrocardiogram (ECG)-based cancelable biometric scheme is proposed to relieve such concerns. In this scheme, distinct biometric templates for a given beat bundle are constructed via "subspace collapsing." To determine the identity of any unknown beat bundle, the multiple signal classification (MUSIC) algorithm, incorporating a "suppression and poll" strategy, is adopted. Unlike the existing cancelable biometric schemes, knowledge of the distortion transform is not required for recognition. Experiments with real ECGs from 285 subjects are presented to illustrate the efficacy of the proposed scheme. The best recognition rate of 97.58 % was achieved under the test condition N train = 10 and N test = 10.

Photogrammetric fingerprint unwrapping

Science.gov (United States)

Paar, Gerhard; del Pilar Caballo Perucha, Maria; Bauer, Arnold; Nauschnegg, Bernhard

2008-04-01

Fingerprints are important biometric cues. Compared to conventional fingerprint sensors the use of contact-free stereoscopic image acquisition of the front-most finger segment has a set of advantages: Finger deformation is avoided, the entire relevant area for biometric use is covered, some technical aspects like sensor maintenance and cleaning are facilitated, and access to a three-dimensional reconstruction of the covered area is possible. We describe a photogrammetric workflow for nail-to-nail fingerprint reconstruction: A calibrated sensor setup with typically 5 cameras and dedicated illumination acquires adjacent stereo pairs. Using the silhouettes of the segmented finger a raw cylindrical model is generated. After preprocessing (shading correction, dust removal, lens distortion correction), each individual camera texture is projected onto the model. Image-to-image matching on these pseudo ortho images and dense 3D reconstruction obtains a textured cylindrical digital surface model with radial distances around the major axis and a grid size in the range of 25-50 µm. The model allows for objective fingerprint unwrapping and novel fingerprint matching algorithms since 3D relations between fingerprint features are available as additional cues. Moreover, covering the entire region with relevant fingerprint texture is particularly important for establishing a comprehensive forensic database. The workflow has been implemented in portable C and is ready for industrial exploitation. Further improvement issues are code optimization, unwrapping method, illumination strategy to avoid highlights and to improve the initial segmentation, and the comparison of the unwrapping result to conventional fingerprint acquisition technology.

Physics and fingerprints

Science.gov (United States)

Voss-de Haan, Patrick

2006-08-01

This article discusses a variety of aspects in the detection and development of fingerprints and the physics involved in it. It gives an introduction to some basic issues like composition and properties of fingerprint deposits and a rudimentary framework of dactyloscopy; it covers various techniques for the visualization of latent fingerprints; and it concludes with a view of current research topics. The techniques range from very common procedures, such as powdering and cyanoacrylate fuming, to more demanding methods, for example luminescence and vacuum metal deposition, to fairly unusual approaches like autoradiography. The emphasis is placed on the physical rather than the forensic aspects of these topics while trying to give the physicist—who is not dealing with fingerprinting and forensic science on a daily basis—a feeling for the problems and solutions in the visualization of latent fingerprints.

Fingerprints in cancer cells

International Nuclear Information System (INIS)

Servomaa, K.

1994-01-01

Gene research has shown that factors causing cancer, or carcinogens, may leave marks typical of each particular carcinogen (fingerprints) in the genotype of the cell. Radiation, for instance, may leave such fingerprints in a cancer cell. In particular, the discovery of a gene called p53 has yielded much new information on fingerprints. It has been discovered, for example, that toxic fungus and UV-radiation each leave fingerprints in the p53 gene. Based on the detection of fingerprints, it may be possible in the future to tell a cancer patient what factor had trigged the maglinancy

Schemes of detecting nuclear spin correlations by dynamical decoupling based quantum sensing

Science.gov (United States)

Ma, Wen-Long Ma; Liu, Ren-Bao

Single-molecule sensitivity of nuclear magnetic resonance (NMR) and angstrom resolution of magnetic resonance imaging (MRI) are the highest challenges in magnetic microscopy. Recent development in dynamical decoupling (DD) enhanced diamond quantum sensing has enabled NMR of single nuclear spins and nanoscale NMR. Similar to conventional NMR and MRI, current DD-based quantum sensing utilizes the frequency fingerprints of target nuclear spins. Such schemes, however, cannot resolve different nuclear spins that have the same noise frequency or differentiate different types of correlations in nuclear spin clusters. Here we show that the first limitation can be overcome by using wavefunction fingerprints of target nuclear spins, which is much more sensitive than the ''frequency fingerprints'' to weak hyperfine interaction between the targets and a sensor, while the second one can be overcome by a new design of two-dimensional DD sequences composed of two sets of periodic DD sequences with different periods, which can be independently set to match two different transition frequencies. Our schemes not only offer an approach to breaking the resolution limit set by ''frequency gradients'' in conventional MRI, but also provide a standard approach to correlation spectroscopy for single-molecule NMR.

Dorsal finger texture recognition: Investigating fixed-length SURF

DEFF Research Database (Denmark)

Hartung, Daniel; Kückelhahn, Jesper

2012-01-01

We seek to create fixed-length features from dorsal finger skin images extracted by the SURF interest point detector to combine it in the privacy enhancing helper data scheme. The source of the biometric samples is the GUC45 database which features finger vein, fingerprint and dorsal finger skin...

Improvement of an algorithm for recognition of liveness using perspiration in fingerprint devices

Science.gov (United States)

Parthasaradhi, Sujan T.; Derakhshani, Reza; Hornak, Lawrence A.; Schuckers, Stephanie C.

2004-08-01

Previous work in our laboratory and others have demonstrated that spoof fingers made of a variety of materials including silicon, Play-Doh, clay, and gelatin (gummy finger) can be scanned and verified when compared to a live enrolled finger. Liveness, i.e. to determine whether the introduced biometric is coming from a live source, has been suggested as a means to circumvent attacks using spoof fingers. We developed a new liveness method based on perspiration changes in the fingerprint image. Recent results showed approximately 90% classification rate using different classification methods for various technologies including optical, electro-optical, and capacitive DC, a shorter time window and a diverse dataset. This paper focuses on improvement of the live classification rate by using a weight decay method during the training phase in order to improve the generalization and reduce the variance of the neural network based classifier. The dataset included fingerprint images from 33 live subjects, 33 spoofs created with dental impression material and Play-Doh, and fourteen cadaver fingers. 100% live classification was achieved with 81.8 to 100% spoof classification, depending on the device technology. The weight-decay method improves upon past reports by increasing the live and spoof classification rate.

A Multimodal Technique for an Embedded Fingerprint Recognizer in Mobile Payment Systems

Directory of Open Access Journals (Sweden)

V. Conti

2009-01-01

Full Text Available The development and the diffusion of distributed systems, directly connected to recent communication technologies, move people towards the era of mobile and ubiquitous systems. Distributed systems make merchant-customer relationships closer and more flexible, using reliable e-commerce technologies. These systems and environments need many distributed access points, for the creation and management of secure identities and for the secure recognition of users. Traditionally, these access points can be made possible by a software system with a main central server. This work proposes the study and implementation of a multimodal technique, based on biometric information, for identity management and personal ubiquitous authentication. The multimodal technique uses both fingerprint micro features (minutiae and fingerprint macro features (singularity points for robust user authentication. To strengthen the security level of electronic payment systems, an embedded hardware prototype has been also created: acting as self-contained sensors, it performs the entire authentication process on the same device, so that all critical information (e.g. biometric data, account transactions and cryptographic keys, are managed and stored inside the sensor, without any data transmission. The sensor has been prototyped using the Celoxica RC203E board, achieving fast execution time, low working frequency, and good recognition performance.

Dealing with Insufficient Location Fingerprints in Wi-Fi Based Indoor Location Fingerprinting

Directory of Open Access Journals (Sweden)

Kai Dong

2017-01-01

Full Text Available The development of the Internet of Things has accelerated research in the indoor location fingerprinting technique, which provides value-added localization services for existing WLAN infrastructures without the need for any specialized hardware. The deployment of a fingerprinting based localization system requires an extremely large amount of measurements on received signal strength information to generate a location fingerprint database. Nonetheless, this requirement can rarely be satisfied in most indoor environments. In this paper, we target one but common situation when the collected measurements on received signal strength information are insufficient, and show limitations of existing location fingerprinting methods in dealing with inadequate location fingerprints. We also introduce a novel method to reduce noise in measuring the received signal strength based on the maximum likelihood estimation, and compute locations from inadequate location fingerprints by using the stochastic gradient descent algorithm. Our experiment results show that our proposed method can achieve better localization performance even when only a small quantity of RSS measurements is available. Especially when the number of observations at each location is small, our proposed method has evident superiority in localization accuracy.

Low-Speed Fingerprint Image Capture System User`s Guide, June 1, 1993

Energy Technology Data Exchange (ETDEWEB)

Whitus, B.R.; Goddard, J.S.; Jatko, W.B.; Manges, W.W.; Treece, D.A.

1993-06-01

The Low-Speed Fingerprint Image Capture System (LS-FICS) uses a Sun workstation controlling a Lenzar ElectroOptics Opacity 1000 imaging system to digitize fingerprint card images to support the Federal Bureau of Investigation`s (FBI`s) Automated Fingerprint Identification System (AFIS) program. The system also supports the operations performed by the Oak Ridge National Laboratory- (ORNL-) developed Image Transmission Network (ITN) prototype card scanning system. The input to the system is a single FBI fingerprint card of the agreed-upon standard format and a user-specified identification number. The output is a file formatted to be compatible with the National Institute of Standards and Technology (NIST) draft standard for fingerprint data exchange dated June 10, 1992. These NIST compatible files contain the required print and text images. The LS-FICS is designed to provide the FBI with the capability of scanning fingerprint cards into a digital format. The FBI will replicate the system to generate a data base of test images. The Host Workstation contains the image data paths and the compression algorithm. A local area network interface, disk storage, and tape drive are used for the image storage and retrieval, and the Lenzar Opacity 1000 scanner is used to acquire the image. The scanner is capable of resolving 500 pixels/in. in both x and y directions. The print images are maintained in full 8-bit gray scale and compressed with an FBI-approved wavelet-based compression algorithm. The text fields are downsampled to 250 pixels/in. and 2-bit gray scale. The text images are then compressed using a lossless Huffman coding scheme. The text fields retrieved from the output files are easily interpreted when displayed on the screen. Detailed procedures are provided for system calibration and operation. Software tools are provided to verify proper system operation.

Families of quantum fingerprinting protocols

Science.gov (United States)

Lovitz, Benjamin; Lütkenhaus, Norbert

2018-03-01

We introduce several families of quantum fingerprinting protocols to evaluate the equality function on two n -bit strings in the simultaneous message passing model. The original quantum fingerprinting protocol uses a tensor product of a small number of O (logn ) -qubit high-dimensional signals [H. Buhrman et al., Phys. Rev. Lett. 87, 167902 (2001), 10.1103/PhysRevLett.87.167902], whereas a recently proposed optical protocol uses a tensor product of O (n ) single-qubit signals, while maintaining the O (logn ) information leakage of the original protocol [J. M. Arazola and N. Lütkenhaus, Phys. Rev. A 89, 062305 (2014), 10.1103/PhysRevA.89.062305]. We find a family of protocols which interpolate between the original and optical protocols while maintaining the O (logn ) information leakage, thus demonstrating a tradeoff between the number of signals sent and the dimension of each signal. There has been interest in experimental realization of the recently proposed optical protocol using coherent states [F. Xu et al., Nat. Commun. 6, 8735 (2015), 10.1038/ncomms9735; J.-Y. Guan et al., Phys. Rev. Lett. 116, 240502 (2016), 10.1103/PhysRevLett.116.240502], but as the required number of laser pulses grows linearly with the input size n , eventual challenges for the long-time stability of experimental setups arise. We find a coherent state protocol which reduces the number of signals by a factor 1/2 while also reducing the information leakage. Our reduction makes use of a simple modulation scheme in optical phase space, and we find that more complex modulation schemes are not advantageous. Using a similar technique, we improve a recently proposed coherent state protocol for evaluating the Euclidean distance between two real unit vectors [N. Kumar et al., Phys. Rev. A 95, 032337 (2017), 10.1103/PhysRevA.95.032337] by reducing the number of signals by a factor 1/2 and also reducing the information leakage.

Magnetic Resonance Fingerprinting - a promising new approach to obtain standardized imaging biomarkers from MRI.

Science.gov (United States)

2015-04-01

Current routine MRI examinations rely on the acquisition of qualitative images that have a contrast "weighted" for a mixture of (magnetic) tissue properties. Recently, a novel approach was introduced, namely MR Fingerprinting (MRF) with a completely different approach to data acquisition, post-processing and visualization. Instead of using a repeated, serial acquisition of data for the characterization of individual parameters of interest, MRF uses a pseudo randomized acquisition that causes the signals from different tissues to have a unique signal evolution or 'fingerprint' that is simultaneously a function of the multiple material properties under investigation. The processing after acquisition involves a pattern recognition algorithm to match the fingerprints to a predefined dictionary of predicted signal evolutions. These can then be translated into quantitative maps of the magnetic parameters of interest. MR Fingerprinting (MRF) is a technique that could theoretically be applied to most traditional qualitative MRI methods and replaces them with acquisition of truly quantitative tissue measures. MRF is, thereby, expected to be much more accurate and reproducible than traditional MRI and should improve multi-center studies and significantly reduce reader bias when diagnostic imaging is performed. Key Points • MR fingerprinting (MRF) is a new approach to data acquisition, post-processing and visualization.• MRF provides highly accurate quantitative maps of T1, T2, proton density, diffusion.• MRF may offer multiparametric imaging with high reproducibility, and high potential for multicenter/ multivendor studies.

Forensic comparison and matching of fingerprints: using quantitative image measures for estimating error rates through understanding and predicting difficulty.

Directory of Open Access Journals (Sweden)

Philip J Kellman

Full Text Available Latent fingerprint examination is a complex task that, despite advances in image processing, still fundamentally depends on the visual judgments of highly trained human examiners. Fingerprints collected from crime scenes typically contain less information than fingerprints collected under controlled conditions. Specifically, they are often noisy and distorted and may contain only a portion of the total fingerprint area. Expertise in fingerprint comparison, like other forms of perceptual expertise, such as face recognition or aircraft identification, depends on perceptual learning processes that lead to the discovery of features and relations that matter in comparing prints. Relatively little is known about the perceptual processes involved in making comparisons, and even less is known about what characteristics of fingerprint pairs make particular comparisons easy or difficult. We measured expert examiner performance and judgments of difficulty and confidence on a new fingerprint database. We developed a number of quantitative measures of image characteristics and used multiple regression techniques to discover objective predictors of error as well as perceived difficulty and confidence. A number of useful predictors emerged, and these included variables related to image quality metrics, such as intensity and contrast information, as well as measures of information quantity, such as the total fingerprint area. Also included were configural features that fingerprint experts have noted, such as the presence and clarity of global features and fingerprint ridges. Within the constraints of the overall low error rates of experts, a regression model incorporating the derived predictors demonstrated reasonable success in predicting objective difficulty for print pairs, as shown both in goodness of fit measures to the original data set and in a cross validation test. The results indicate the plausibility of using objective image metrics to predict expert

Forensic comparison and matching of fingerprints: using quantitative image measures for estimating error rates through understanding and predicting difficulty.

Science.gov (United States)

Kellman, Philip J; Mnookin, Jennifer L; Erlikhman, Gennady; Garrigan, Patrick; Ghose, Tandra; Mettler, Everett; Charlton, David; Dror, Itiel E

2014-01-01

Latent fingerprint examination is a complex task that, despite advances in image processing, still fundamentally depends on the visual judgments of highly trained human examiners. Fingerprints collected from crime scenes typically contain less information than fingerprints collected under controlled conditions. Specifically, they are often noisy and distorted and may contain only a portion of the total fingerprint area. Expertise in fingerprint comparison, like other forms of perceptual expertise, such as face recognition or aircraft identification, depends on perceptual learning processes that lead to the discovery of features and relations that matter in comparing prints. Relatively little is known about the perceptual processes involved in making comparisons, and even less is known about what characteristics of fingerprint pairs make particular comparisons easy or difficult. We measured expert examiner performance and judgments of difficulty and confidence on a new fingerprint database. We developed a number of quantitative measures of image characteristics and used multiple regression techniques to discover objective predictors of error as well as perceived difficulty and confidence. A number of useful predictors emerged, and these included variables related to image quality metrics, such as intensity and contrast information, as well as measures of information quantity, such as the total fingerprint area. Also included were configural features that fingerprint experts have noted, such as the presence and clarity of global features and fingerprint ridges. Within the constraints of the overall low error rates of experts, a regression model incorporating the derived predictors demonstrated reasonable success in predicting objective difficulty for print pairs, as shown both in goodness of fit measures to the original data set and in a cross validation test. The results indicate the plausibility of using objective image metrics to predict expert performance and

An HMM-Like Dynamic Time Warping Scheme for Automatic Speech Recognition

Directory of Open Access Journals (Sweden)

Ing-Jr Ding

2014-01-01

Full Text Available In the past, the kernel of automatic speech recognition (ASR is dynamic time warping (DTW, which is feature-based template matching and belongs to the category technique of dynamic programming (DP. Although DTW is an early developed ASR technique, DTW has been popular in lots of applications. DTW is playing an important role for the known Kinect-based gesture recognition application now. This paper proposed an intelligent speech recognition system using an improved DTW approach for multimedia and home automation services. The improved DTW presented in this work, called HMM-like DTW, is essentially a hidden Markov model- (HMM- like method where the concept of the typical HMM statistical model is brought into the design of DTW. The developed HMM-like DTW method, transforming feature-based DTW recognition into model-based DTW recognition, will be able to behave as the HMM recognition technique and therefore proposed HMM-like DTW with the HMM-like recognition model will have the capability to further perform model adaptation (also known as speaker adaptation. A series of experimental results in home automation-based multimedia access service environments demonstrated the superiority and effectiveness of the developed smart speech recognition system by HMM-like DTW.

A topology based approach to categorization of fingerprint images

DEFF Research Database (Denmark)

Aabrandt, A.; Olsen, M. A.; Busch, C.

2012-01-01

, an image is viewed as a triangulated point cloud and the topology associated with this construct is summarized using its first betti number - a number that indicates the number of distinct cycles in the triangulation associated to the particular image. This number is then compared against the first betti...... numbers of “n” prototype images in order to perform classification (“fingerprint” vs “non-fingerprint”). The proposed method is compared against SIVV (a tool provided by NIST). Experimental results on fingerprint and iris databases demonstrate the potential of the scheme....

Recognition Errors Control in Biometric Identification Cryptosystems

Directory of Open Access Journals (Sweden)

Vladimir Ivanovich Vasilyev

2015-06-01

Full Text Available The method of biometric cryptosystem designed on the basis of fuzzy extractor, in which main disadvantages of biometric and cryptographic systems are absent, is considered. The main idea of this work is a control of identity recognition errors with use of fuzzy extractor which operates with Reed – Solomon correcting code. The fingerprint features vector is considered as a biometric user identifier.

Online fingerprint verification.

Science.gov (United States)

Upendra, K; Singh, S; Kumar, V; Verma, H K

2007-01-01

As organizations search for more secure authentication methods for user access, e-commerce, and other security applications, biometrics is gaining increasing attention. With an increasing emphasis on the emerging automatic personal identification applications, fingerprint based identification is becoming more popular. The most widely used fingerprint representation is the minutiae based representation. The main drawback with this representation is that it does not utilize a significant component of the rich discriminatory information available in the fingerprints. Local ridge structures cannot be completely characterized by minutiae. Also, it is difficult quickly to match two fingerprint images containing different number of unregistered minutiae points. In this study filter bank based representation, which eliminates these weakness, is implemented and the overall performance of the developed system is tested. The results have shown that this system can be used effectively for secure online verification applications.

Digital holographic-based cancellable biometric for personal authentication

International Nuclear Information System (INIS)

Verma, Gaurav; Sinha, Aloka

2016-01-01

In this paper, we propose a new digital holographic-based cancellable biometric scheme for personal authentication and verification. The realization of cancellable biometric is presented by using an optoelectronic experimental approach, in which an optically recorded hologram of the fingerprint of a person is numerically reconstructed. Each reconstructed feature has its own perspective, which is utilized to generate user-specific fingerprint features by using a feature-extraction process. New representations of the user-specific fingerprint features can be obtained from the same hologram, by changing the reconstruction distance (d) by an amount Δd between the recording plane and the reconstruction plane. This parameter is the key to make the cancellable user-specific fingerprint features using a digital holographic technique, which allows us to choose different reconstruction distances when reissuing the user-specific fingerprint features in the event of compromise. We have shown theoretically that each user-specific fingerprint feature has a unique identity with a high discrimination ability, and the chances of a match between them are minimal. In this aspect, a recognition system has also been demonstrated using the fingerprint biometric of the enrolled person at a particular reconstruction distance. For the performance evaluation of a fingerprint recognition system—the false acceptance ratio, the false rejection ratio and the equal error rate are calculated using correlation. The obtained results show good discrimination ability between the genuine and the impostor populations with the highest recognition rate of 98.23%. (paper)

Magnetic resonance fingerprinting.

Science.gov (United States)

Ma, Dan; Gulani, Vikas; Seiberlich, Nicole; Liu, Kecheng; Sunshine, Jeffrey L; Duerk, Jeffrey L; Griswold, Mark A

2013-03-14

Magnetic resonance is an exceptionally powerful and versatile measurement technique. The basic structure of a magnetic resonance experiment has remained largely unchanged for almost 50 years, being mainly restricted to the qualitative probing of only a limited set of the properties that can in principle be accessed by this technique. Here we introduce an approach to data acquisition, post-processing and visualization--which we term 'magnetic resonance fingerprinting' (MRF)--that permits the simultaneous non-invasive quantification of multiple important properties of a material or tissue. MRF thus provides an alternative way to quantitatively detect and analyse complex changes that can represent physical alterations of a substance or early indicators of disease. MRF can also be used to identify the presence of a specific target material or tissue, which will increase the sensitivity, specificity and speed of a magnetic resonance study, and potentially lead to new diagnostic testing methodologies. When paired with an appropriate pattern-recognition algorithm, MRF inherently suppresses measurement errors and can thus improve measurement accuracy.

Fingerprint separation: an application of ICA

Science.gov (United States)

Singh, Meenakshi; Singh, Deepak Kumar; Kalra, Prem Kumar

2008-04-01

Among all existing biometric techniques, fingerprint-based identification is the oldest method, which has been successfully used in numerous applications. Fingerprint-based identification is the most recognized tool in biometrics because of its reliability and accuracy. Fingerprint identification is done by matching questioned and known friction skin ridge impressions from fingers, palms, and toes to determine if the impressions are from the same finger (or palm, toe, etc.). There are many fingerprint matching algorithms which automate and facilitate the job of fingerprint matching, but for any of these algorithms matching can be difficult if the fingerprints are overlapped or mixed. In this paper, we have proposed a new algorithm for separating overlapped or mixed fingerprints so that the performance of the matching algorithms will improve when they are fed with these inputs. Independent Component Analysis (ICA) has been used as a tool to separate the overlapped or mixed fingerprints.

Fingerprints in Compressed Strings

DEFF Research Database (Denmark)

Bille, Philip; Cording, Patrick Hagge; Gørtz, Inge Li

2013-01-01

The Karp-Rabin fingerprint of a string is a type of hash value that due to its strong properties has been used in many string algorithms. In this paper we show how to construct a data structure for a string S of size N compressed by a context-free grammar of size n that answers fingerprint queries...... derivative that captures LZ78 compression and its variations) we get O(loglogN) query time. Hence, our data structures has the same time and space complexity as for random access in SLPs. We utilize the fingerprint data structures to solve the longest common extension problem in query time O(logNlogℓ) and O....... That is, given indices i and j, the answer to a query is the fingerprint of the substring S[i,j]. We present the first O(n) space data structures that answer fingerprint queries without decompressing any characters. For Straight Line Programs (SLP) we get O(logN) query time, and for Linear SLPs (an SLP...

Study on internal to surface fingerprint correlation using optical coherence tomography and internal fingerprint extraction

CSIR Research Space (South Africa)

Darlow, LN

2015-11-01

Full Text Available of, the above-mentioned works. Internal fingerprint zone detection is an improvement as it uses fuzzy c-means to improve clustering performance, uses better cluster result postprocessing, and improves upon the fine-tuning procedure through... Internal fingerprint extraction consists of two main parts: fingerprint zone detection and extraction. Zone detection uses fuzzy c-means clustering to approximate the location of the papillary junction (i.e., the internal fingerprint zone). Edge detection...

Modeling Audio Fingerprints : Structure, Distortion, Capacity

NARCIS (Netherlands)

Doets, P.J.O.

2010-01-01

An audio fingerprint is a compact low-level representation of a multimedia signal. An audio fingerprint can be used to identify audio files or fragments in a reliable way. The use of audio fingerprints for identification consists of two phases. In the enrollment phase known content is fingerprinted,

Fingerprint re-alignment: a solution based on the true fingerprint center point

CSIR Research Space (South Africa)

Msiza, IS

2011-02-01

Full Text Available Solution Based on the True Fingerprint Center Point Ishmael S. Msiza, Brain Leke-Betechuoh, and Tendani Malumedzha Biometrics Research Group ? Information Security CSIR, Modelling & Digital Science Unit Pretoria, Republic of South Africa e... with a pattern that belongs to the Tented Arch (TA) fingerprint class. Fingerprints that belong to the TA class have a single core and a single delta, with the core located almost directly above the delta, as depicted in figure 3 (b). Many singular...

Fingerprint fake detection by optical coherence tomography

Science.gov (United States)

Meissner, Sven; Breithaupt, Ralph; Koch, Edmund

2013-03-01

The most established technique for the identification at biometric access control systems is the human fingerprint. While every human fingerprint is unique, fingerprints can be faked very easily by using thin layer fakes. Because commercial fingerprint scanners use only a two-dimensional image acquisition of the finger surface, they can only hardly differentiate between real fingerprints and fingerprint fakes applied on thin layer materials. A Swept Source OCT system with an A-line rate of 20 kHz and a lateral and axial resolution of approximately 13 μm, a centre wavelength of 1320 nm and a band width of 120 nm (FWHM) was used to acquire fingerprints and finger tips with overlying fakes. Three-dimensional volume stacks with dimensions of 4.5 mm x 4 mm x 2 mm were acquired. The layering arrangement of the imaged finger tips and faked finger tips was analyzed and subsequently classified into real and faked fingerprints. Additionally, sweat gland ducts were detected and consulted for the classification. The manual classification between real fingerprints and faked fingerprints results in almost 100 % correctness. The outer as well as the internal fingerprint can be recognized in all real human fingers, whereby this was not possible in the image stacks of the faked fingerprints. Furthermore, in all image stacks of real human fingers the sweat gland ducts were detected. The number of sweat gland ducts differs between the test persons. The typical helix shape of the ducts was observed. In contrast, in images of faked fingerprints we observe abnormal layer arrangements and no sweat gland ducts connecting the papillae of the outer fingerprint and the internal fingerprint. We demonstrated that OCT is a very useful tool to enhance the performance of biometric control systems concerning attacks by thin layer fingerprint fakes.

Classical and quantum fingerprinting strategies

International Nuclear Information System (INIS)

Scott, A.; Walgate, J.; Sanders, B.

2005-01-01

Full text: Fingerprinting enables two parties to infer whether the messages they hold are the same or different when the cost of communication is high: each message is associated with a smaller fingerprint and comparisons between messages are made in terms of their fingerprints alone. When the two parties are forbidden access to a public coin, it is known that fingerprints composed of quantum information can be made exponentially smaller than those composed of classical information. We present specific constructions of classical fingerprinting strategies through the use of constant-weight codes and provide bounds on the worst-case error probability with the help of extremal set theory. These classical strategies are easily outperformed by quantum strategies constructed from line packings and equiangular tight frames. (author)

Multi-Stage Recognition of Speech Emotion Using Sequential Forward Feature Selection

Directory of Open Access Journals (Sweden)

Liogienė Tatjana

2016-07-01

Full Text Available The intensive research of speech emotion recognition introduced a huge collection of speech emotion features. Large feature sets complicate the speech emotion recognition task. Among various feature selection and transformation techniques for one-stage classification, multiple classifier systems were proposed. The main idea of multiple classifiers is to arrange the emotion classification process in stages. Besides parallel and serial cases, the hierarchical arrangement of multi-stage classification is most widely used for speech emotion recognition. In this paper, we present a sequential-forward-feature-selection-based multi-stage classification scheme. The Sequential Forward Selection (SFS and Sequential Floating Forward Selection (SFFS techniques were employed for every stage of the multi-stage classification scheme. Experimental testing of the proposed scheme was performed using the German and Lithuanian emotional speech datasets. Sequential-feature-selection-based multi-stage classification outperformed the single-stage scheme by 12–42 % for different emotion sets. The multi-stage scheme has shown higher robustness to the growth of emotion set. The decrease in recognition rate with the increase in emotion set for multi-stage scheme was lower by 10–20 % in comparison with the single-stage case. Differences in SFS and SFFS employment for feature selection were negligible.

Advances in fingerprint analysis.

Science.gov (United States)

Hazarika, Pompi; Russell, David A

2012-04-10

Fingerprints have been used in forensic investigations for the identification of individuals since the late 19th century. However, it is now clear that fingerprints can provide significantly more information about an individual. Here, we highlight the considerable advances in fingerprinting technology that can simultaneously provide chemical information regarding the drugs ingested and the explosives and drugs handled by a person as well as the identity of that individual. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Image Quality Enhancement Using the Direction and Thickness of Vein Lines for Finger-Vein Recognition

OpenAIRE

Park, Young Ho; Park, Kang Ryoung

2012-01-01

On the basis of the increased emphasis placed on the protection of privacy, biometric recognition systems using physical or behavioural characteristics such as fingerprints, facial characteristics, iris and finger‐vein patterns or the voice have been introduced in applications including door access control, personal certification, Internet banking and ATM machines. Among these, finger‐vein recognition is advantageous in that it involves the use of inexpensive and small devices that are diffic...

The nature of expertise in fingerprint matching: experts can do a lot with a little.

Directory of Open Access Journals (Sweden)

Matthew B Thompson

Full Text Available Expert decision making often seems impressive, even miraculous. People with genuine expertise in a particular domain can perform quickly and accurately, and with little information. In the series of experiments presented here, we manipulate the amount of "information" available to a group of experts whose job it is to identify the source of crime scene fingerprints. In Experiment 1, we reduced the amount of information available to experts by inverting fingerprint pairs and adding visual noise. There was no evidence for an inversion effect-experts were just as accurate for inverted prints as they were for upright prints-but expert performance with artificially noisy prints was impressive. In Experiment 2, we separated matching and nonmatching print pairs in time. Experts were conservative, but they were still able to discriminate pairs of fingerprints that were separated by five-seconds, even though the task was quite different from their everyday experience. In Experiment 3, we separated the print pairs further in time to test the long-term memory of experts compared to novices. Long-term recognition memory for experts and novices was the same, with both performing around chance. In Experiment 4, we presented pairs of fingerprints quickly to experts and novices in a matching task. Experts were more accurate than novices, particularly for similar nonmatching pairs, and experts were generally more accurate when they had more time. It is clear that experts can match prints accurately when there is reduced visual information, reduced opportunity for direct comparison, and reduced time to engage in deliberate reasoning. These findings suggest that non-analytic processing accounts for a substantial portion of the variance in expert fingerprint matching accuracy. Our conclusion is at odds with general wisdom in fingerprint identification practice and formal training, and at odds with the claims and explanations that are offered in court during expert

The nature of expertise in fingerprint matching: experts can do a lot with a little.

Science.gov (United States)

Thompson, Matthew B; Tangen, Jason M

2014-01-01

Expert decision making often seems impressive, even miraculous. People with genuine expertise in a particular domain can perform quickly and accurately, and with little information. In the series of experiments presented here, we manipulate the amount of "information" available to a group of experts whose job it is to identify the source of crime scene fingerprints. In Experiment 1, we reduced the amount of information available to experts by inverting fingerprint pairs and adding visual noise. There was no evidence for an inversion effect-experts were just as accurate for inverted prints as they were for upright prints-but expert performance with artificially noisy prints was impressive. In Experiment 2, we separated matching and nonmatching print pairs in time. Experts were conservative, but they were still able to discriminate pairs of fingerprints that were separated by five-seconds, even though the task was quite different from their everyday experience. In Experiment 3, we separated the print pairs further in time to test the long-term memory of experts compared to novices. Long-term recognition memory for experts and novices was the same, with both performing around chance. In Experiment 4, we presented pairs of fingerprints quickly to experts and novices in a matching task. Experts were more accurate than novices, particularly for similar nonmatching pairs, and experts were generally more accurate when they had more time. It is clear that experts can match prints accurately when there is reduced visual information, reduced opportunity for direct comparison, and reduced time to engage in deliberate reasoning. These findings suggest that non-analytic processing accounts for a substantial portion of the variance in expert fingerprint matching accuracy. Our conclusion is at odds with general wisdom in fingerprint identification practice and formal training, and at odds with the claims and explanations that are offered in court during expert testimony.

Defect Localization Capabilities of a Global Detection Scheme: Spatial Pattern Recognition Using Full-field Vibration Test Data in Plates

Science.gov (United States)

Saleeb, A. F.; Prabhu, M.; Arnold, S. M. (Technical Monitor)

2002-01-01

Recently, a conceptually simple approach, based on the notion of defect energy in material space has been developed and extensively studied (from the theoretical and computational standpoints). The present study focuses on its evaluation from the viewpoint of damage localization capabilities in case of two-dimensional plates; i.e., spatial pattern recognition on surfaces. To this end, two different experimental modal test results are utilized; i.e., (1) conventional modal testing using (white noise) excitation and accelerometer-type sensors and (2) pattern recognition using Electronic speckle pattern interferometry (ESPI), a full field method capable of analyzing the mechanical vibration of complex structures. Unlike the conventional modal testing technique (using contacting accelerometers), these emerging ESPI technologies operate in a non-contacting mode, can be used even under hazardous conditions with minimal or no presence of noise and can simultaneously provide measurements for both translations and rotations. Results obtained have clearly demonstrated the robustness and versatility of the global NDE scheme developed. The vectorial character of the indices used, which enabled the extraction of distinct patterns for localizing damages proved very useful. In the context of the targeted pattern recognition paradigm, two algorithms were developed for the interrogation of test measurements; i.e., intensity contour maps for the damaged index, and the associated defect energy vector field plots.

A Study for Visual Realism of Designed Pictures on Computer Screens by Investigation and Brain-Wave Analyses.

Science.gov (United States)

Wang, Lan-Ting; Lee, Kun-Chou

2016-08-01

In this article, the visual realism of designed pictures on computer screens is studied by investigation and brain-wave analyses. The practical electroencephalogram (EEG) measurement is always time-varying and fluctuating so that conventional statistical techniques are not adequate for analyses. This study proposes a new scheme based on "fingerprinting" to analyze the EEG. Fingerprinting is a technique of probabilistic pattern recognition used in electrical engineering, very like the identification of human fingerprinting in a criminal investigation. The goal of this study was to assess whether subjective preference for pictures could be manifested physiologically by EEG fingerprinting analyses. The most important advantage of the fingerprinting technique is that it does not require accurate measurement. Instead, it uses probabilistic classification. Participants' preference for pictures can be assessed using fingerprinting analyses of physiological EEG measurements. © The Author(s) 2016.

Fingerprint verification prediction model in hand dermatitis.

Science.gov (United States)

Lee, Chew K; Chang, Choong C; Johor, Asmah; Othman, Puwira; Baba, Roshidah

2015-07-01

Hand dermatitis associated fingerprint changes is a significant problem and affects fingerprint verification processes. This study was done to develop a clinically useful prediction model for fingerprint verification in patients with hand dermatitis. A case-control study involving 100 patients with hand dermatitis. All patients verified their thumbprints against their identity card. Registered fingerprints were randomized into a model derivation and model validation group. Predictive model was derived using multiple logistic regression. Validation was done using the goodness-of-fit test. The fingerprint verification prediction model consists of a major criterion (fingerprint dystrophy area of ≥ 25%) and two minor criteria (long horizontal lines and long vertical lines). The presence of the major criterion predicts it will almost always fail verification, while presence of both minor criteria and presence of one minor criterion predict high and low risk of fingerprint verification failure, respectively. When none of the criteria are met, the fingerprint almost always passes the verification. The area under the receiver operating characteristic curve was 0.937, and the goodness-of-fit test showed agreement between the observed and expected number (P = 0.26). The derived fingerprint verification failure prediction model is validated and highly discriminatory in predicting risk of fingerprint verification in patients with hand dermatitis. © 2014 The International Society of Dermatology.

Does Kaniso activate CASINO?: input coding schemes and phonology in visual-word recognition.

Science.gov (United States)

Acha, Joana; Perea, Manuel

2010-01-01

Most recent input coding schemes in visual-word recognition assume that letter position coding is orthographic rather than phonological in nature (e.g., SOLAR, open-bigram, SERIOL, and overlap). This assumption has been drawn - in part - by the fact that the transposed-letter effect (e.g., caniso activates CASINO) seems to be (mostly) insensitive to phonological manipulations (e.g., Perea & Carreiras, 2006, 2008; Perea & Pérez, 2009). However, one could argue that the lack of a phonological effect in prior research was due to the fact that the manipulation always occurred in internal letter positions - note that phonological effects tend to be stronger for the initial syllable (Carreiras, Ferrand, Grainger, & Perea, 2005). To reexamine this issue, we conducted a masked priming lexical decision experiment in which we compared the priming effect for transposed-letter pairs (e.g., caniso-CASINO vs. caviro-CASINO) and for pseudohomophone transposed-letter pairs (kaniso-CASINO vs. kaviro-CASINO). Results showed a transposed-letter priming effect for the correctly spelled pairs, but not for the pseudohomophone pairs. This is consistent with the view that letter position coding is (primarily) orthographic in nature.

An effective one-dimensional anisotropic fingerprint enhancement algorithm

Science.gov (United States)

Ye, Zhendong; Xie, Mei

2012-01-01

Fingerprint identification is one of the most important biometric technologies. The performance of the minutiae extraction and the speed of the fingerprint verification system rely heavily on the quality of the input fingerprint images, so the enhancement of the low fingerprint is a critical and difficult step in a fingerprint verification system. In this paper we proposed an effective algorithm for fingerprint enhancement. Firstly we use normalization algorithm to reduce the variations in gray level values along ridges and valleys. Then we utilize the structure tensor approach to estimate each pixel of the fingerprint orientations. At last we propose a novel algorithm which combines the advantages of onedimensional Gabor filtering method and anisotropic method to enhance the fingerprint in recoverable region. The proposed algorithm has been evaluated on the database of Fingerprint Verification Competition 2004, and the results show that our algorithm performs within less time.

Regression-based Multi-View Facial Expression Recognition

NARCIS (Netherlands)

Rudovic, Ognjen; Patras, Ioannis; Pantic, Maja

2010-01-01

We present a regression-based scheme for multi-view facial expression recognition based on 2蚠D geometric features. We address the problem by mapping facial points (e.g. mouth corners) from non-frontal to frontal view where further recognition of the expressions can be performed using a

An Introduction to DNA Fingerprinting.

Science.gov (United States)

Hepfer, Carol Ely; And Others

1993-01-01

Provides background information on DNA fingerprinting, and describes exercises for introducing general biology students at the high school or college level to the methodology and applications of DNA fingerprinting. (PR)

Predicting the performance of fingerprint similarity searching.

Science.gov (United States)

Vogt, Martin; Bajorath, Jürgen

2011-01-01

Fingerprints are bit string representations of molecular structure that typically encode structural fragments, topological features, or pharmacophore patterns. Various fingerprint designs are utilized in virtual screening and their search performance essentially depends on three parameters: the nature of the fingerprint, the active compounds serving as reference molecules, and the composition of the screening database. It is of considerable interest and practical relevance to predict the performance of fingerprint similarity searching. A quantitative assessment of the potential that a fingerprint search might successfully retrieve active compounds, if available in the screening database, would substantially help to select the type of fingerprint most suitable for a given search problem. The method presented herein utilizes concepts from information theory to relate the fingerprint feature distributions of reference compounds to screening libraries. If these feature distributions do not sufficiently differ, active database compounds that are similar to reference molecules cannot be retrieved because they disappear in the "background." By quantifying the difference in feature distribution using the Kullback-Leibler divergence and relating the divergence to compound recovery rates obtained for different benchmark classes, fingerprint search performance can be quantitatively predicted.

Studies on Chromatographic Fingerprint and Fingerprinting Profile-Efficacy Relationship of Saxifraga stolonifera Meerb.

Directory of Open Access Journals (Sweden)

Xing-Dong Wu

2015-12-01

Full Text Available This work investigated the spectrum-effect relationships between high performance liquid chromatography (HPLC fingerprints and the anti-benign prostatic hyperplasia activities of aqueous extracts from Saxifraga stolonifera. The fingerprints of S. stolonifera from various sources were established by HPLC and evaluated by similarity analysis (SA, hierarchical clustering analysis (HCA and principal component analysis (PCA. Nine samples were obtained from these 24 batches of different origins, according to the results of SA, HCA and the common chromatographic peaks area. A testosterone-induced mouse model of benign prostatic hyperplasia (BPH was used to establish the anti-benign prostatic hyperplasia activities of these nine S. stolonifera samples. The model was evaluated by analyzing prostatic index (PI, serum acid phosphatase (ACP activity, concentrations of serum dihydrotestosterone (DHT, prostatic acid phosphatase (PACP and type II 5α-reductase (SRD5A2. The spectrum-effect relationships between HPLC fingerprints and anti-benign prostatic hyperplasia activities were investigated using Grey Correlation Analysis (GRA and partial least squares regression (PLSR. The results showed that a close correlation existed between the fingerprints and anti-benign prostatic hyperplasia activities, and peak 14 (chlorogenic acid, peak 17 (quercetin 5-O-β-d-glucopyranoside and peak 18 (quercetin 3-O-β-l-rhamno-pyranoside in the HPLC fingerprints might be the main active components against anti-benign prostatic hyperplasia. This work provides a general model for the study of spectrum-effect relationships of S. stolonifera by combing HPLC fingerprints with a testosterone-induced mouse model of BPH, which can be employed to discover the principle components of anti-benign prostatic hyperplasia bioactivity.

Latent fingerprints on different type of screen protective films

Directory of Open Access Journals (Sweden)

Yuttana Sudjaroen

2016-07-01

Full Text Available The purpose of this research was to study the quality of latent fingerprint on different types of screen protective films including screen protector, matte screen protector, anti-fingerprint clear screen protector and anti-fingerprint matte screen protector by using black powder method in developing latent fingerprints. The fingerprints were performed by 10 volunteers whose fingers (right index, right thumb, left index and left thumb were stubbing at different types of screen protective films and subsequently latent fingerprints were developed by brushing with black powder. Automated Fingerprint Identification System (AFIS counted the numbers of minutiae points from 320 latent fingerprints. Anti-fingerprint matte screen protective film produced the best quality of latent fingerprint with an average minutiae point 72.65, followed by matte screen protective film, clear screen protective film and anti-fingerprint clear screen protective film with an average minutiae point of 155.2, 135.0 and 72.65 respectively. The quality of latent fingerprints developed between a clear and a matte surface of screen protective films showed a significant difference (sig>0.05, whereas the coat and the non-coat with anti-fingerprint chemical revealed a non-significant difference (sig<0.05 in their number of minutiae points.

Fingerprints in compressed strings

DEFF Research Database (Denmark)

Bille, Philip; Gørtz, Inge Li; Cording, Patrick Hagge

2017-01-01

In this paper we show how to construct a data structure for a string S of size N compressed into a context-free grammar of size n that supports efficient Karp–Rabin fingerprint queries to any substring of S. That is, given indices i and j, the answer to a query is the fingerprint of the substring S......[i,j]. We present the first O(n) space data structures that answer fingerprint queries without decompressing any characters. For Straight Line Programs (SLP) we get O(log⁡N) query time, and for Linear SLPs (an SLP derivative that captures LZ78 compression and its variations) we get O(log⁡log⁡N) query time...

Fingerprint Analysis with Marked Point Processes

DEFF Research Database (Denmark)

Forbes, Peter G. M.; Lauritzen, Steffen; Møller, Jesper

We present a framework for fingerprint matching based on marked point process models. An efficient Monte Carlo algorithm is developed to calculate the marginal likelihood ratio for the hypothesis that two observed prints originate from the same finger against the hypothesis that they originate from...... different fingers. Our model achieves good performance on an NIST-FBI fingerprint database of 258 matched fingerprint pairs....

Collusion-resistant multimedia fingerprinting: a unified framework

Science.gov (United States)

Wu, Min; Trappe, Wade; Wang, Z. Jane; Liu, K. J. Ray

2004-06-01

Digital fingerprints are unique labels inserted in different copies of the same content before distribution. Each digital fingerprint is assigned to an inteded recipient, and can be used to trace the culprits who use their content for unintended purposes. Attacks mounted by multiple users, known as collusion attacks, provide a cost-effective method for attenuating the identifying fingerprint from each coluder, thus collusion poses a reeal challenge to protect the digital media data and enforce usage policies. This paper examines a few major design methodologies for collusion-resistant fingerprinting of multimedia, and presents a unified framework that helps highlight the common issues and the uniqueness of different fingerprinting techniques.

A Survey of 2D Face Recognition Techniques

Directory of Open Access Journals (Sweden)

Mejda Chihaoui

2016-09-01

Full Text Available Despite the existence of various biometric techniques, like fingerprints, iris scan, as well as hand geometry, the most efficient and more widely-used one is face recognition. This is because it is inexpensive, non-intrusive and natural. Therefore, researchers have developed dozens of face recognition techniques over the last few years. These techniques can generally be divided into three categories, based on the face data processing methodology. There are methods that use the entire face as input data for the proposed recognition system, methods that do not consider the whole face, but only some features or areas of the face and methods that use global and local face characteristics simultaneously. In this paper, we present an overview of some well-known methods in each of these categories. First, we expose the benefits of, as well as the challenges to the use of face recognition as a biometric tool. Then, we present a detailed survey of the well-known methods by expressing each method’s principle. After that, a comparison between the three categories of face recognition techniques is provided. Furthermore, the databases used in face recognition are mentioned, and some results of the applications of these methods on face recognition databases are presented. Finally, we highlight some new promising research directions that have recently appeared.

Dna fingerprinting - review paper

OpenAIRE

Blundell, Renald

2006-01-01

Before the Polymerase Chain Reaction (PCR) was established, DNA fingerprinting technology has relied for years on Restriction Fragment Length Polymorphism (RFLP) and Variable Number of Tandom Repeats (VNTR) analysis, a very efficient technique but quite laborious and not suitable for high throughput mapping. Since its, development, PCR has provided a new and powerful tool for DNA fingerprinting.

Electronic fingerprinting of the dead.

Science.gov (United States)

Rutty, G N; Stringer, K; Turk, E E

2008-01-01

To date, a number of methods exist for the capture of fingerprints from cadavers that can then be used in isolation as a primary method for the identification of the dead. We report the use of a handheld, mobile wireless unit used in conjunction with a personal digital assistant (PDA) device for the capture of fingerprints from the dead. We also consider a handheld single-digit fingerprint scanner that utilises a USB laptop connection for the electronic capture of cadaveric fingerprints. Both are single-operator units that, if ridge detail is preserved, can collect a 10-set of finger pad prints in approximately 45 and 90 s, respectively. We present our observations on the restrictions as to when such devices can be used with cadavers. We do, however, illustrate that the images are of sufficient quality to allow positive identification from finger pad prints of the dead. With the development of mobile, handheld, biometric, PDA-based units for the police, we hypothesize that, under certain circumstances, devices such as these could be used for the accelerated acquisition of fingerprint identification data with the potential for rapid near-patient identification in the future.

Individuality that is unheard of: systematic temporal deviations in scale playing leave an inaudible pianistic fingerprint

Directory of Open Access Journals (Sweden)

Floris Tijmen Van Vugt

2013-03-01

Full Text Available Whatever we do, we do it in our own way, and we recognise master artists by small samples of their work. This study investigates individuality of temporal deviations in musical scales in pianists in the absence of deliberate expressive intention. Note-by-note timing deviations away from regularity form a remarkably consistent "pianistic fingerprint". First, 8 professional pianists played C-major scales in two sessions, separated by fifteen minutes. Euclidian distances between deviation traces originating from different pianists were reliably larger than traces originating from the same pianist. As a result, a simple classifier that matched deviation traces by minimising their distance was able to recognise each pianist with 100% accuracy. Furthermore, within each pianist, fingerprints produced by the same movements were more similar than fingerprints resulting in the same scale sound. This allowed us to conclude that the fingerprints are mostly neuromuscular rather than intentional or expressive in nature. However, human listeners were not able to distinguish the temporal fingerprints by ear. Next, 18 pianists played C-major scales on a normal or muted piano. Recognition rates ranged from 83% to 100%, further supporting the view that auditory feedback is not implicated in the creation of the temporal signature. Finally, 20 pianists were recognised 20 months later at above-chance level, showing signature effects to be long lasting. Our results indicate that even non-expressive playing of scales reveals consistent, partially effector-unspecific, but inaudible inter-individual differences. We suggest that machine learning studies into individuality in performance will need to take into account unintentional but consistent variability below the perceptual threshold.

A Computational Discriminability Analysis on Twin Fingerprints

Science.gov (United States)

Liu, Yu; Srihari, Sargur N.

Sharing similar genetic traits makes the investigation of twins an important study in forensics and biometrics. Fingerprints are one of the most commonly found types of forensic evidence. The similarity between twins’ prints is critical establish to the reliability of fingerprint identification. We present a quantitative analysis of the discriminability of twin fingerprints on a new data set (227 pairs of identical twins and fraternal twins) recently collected from a twin population using both level 1 and level 2 features. Although the patterns of minutiae among twins are more similar than in the general population, the similarity of fingerprints of twins is significantly different from that between genuine prints of the same finger. Twins fingerprints are discriminable with a 1.5%~1.7% higher EER than non-twins. And identical twins can be distinguished by examine fingerprint with a slightly higher error rate than fraternal twins.

Fingerprinting with Wow

Science.gov (United States)

Yu, Eugene; Craver, Scott

2006-02-01

Wow, or time warping caused by speed fluctuations in analog audio equipment, provides a wealth of applications in watermarking. Very subtle temporal distortion has been used to defeat watermarks, and as components in watermarking systems. In the image domain, the analogous warping of an image's canvas has been used both to defeat watermarks and also proposed to prevent collusion attacks on fingerprinting systems. In this paper, we explore how subliminal levels of wow can be used for steganography and fingerprinting. We present both a low-bitrate robust solution and a higher-bitrate solution intended for steganographic communication. As already observed, such a fingerprinting algorithm naturally discourages collusion by averaging, owing to flanging effects when misaligned audio is averaged. Another advantage of warping is that even when imperceptible, it can be beyond the reach of compression algorithms. We use this opportunity to debunk the common misconception that steganography is impossible under "perfect compression."

Tools for quality control of fingerprint databases

Science.gov (United States)

Swann, B. Scott; Libert, John M.; Lepley, Margaret A.

2010-04-01

Integrity of fingerprint data is essential to biometric and forensic applications. Accordingly, the FBI's Criminal Justice Information Services (CJIS) Division has sponsored development of software tools to facilitate quality control functions relative to maintaining its fingerprint data assets inherent to the Integrated Automated Fingerprint Identification System (IAFIS) and Next Generation Identification (NGI). This paper provides an introduction of two such tools. The first FBI-sponsored tool was developed by the National Institute of Standards and Technology (NIST) and examines and detects the spectral signature of the ridge-flow structure characteristic of friction ridge skin. The Spectral Image Validation/Verification (SIVV) utility differentiates fingerprints from non-fingerprints, including blank frames or segmentation failures erroneously included in data; provides a "first look" at image quality; and can identify anomalies in sample rates of scanned images. The SIVV utility might detect errors in individual 10-print fingerprints inaccurately segmented from the flat, multi-finger image acquired by one of the automated collection systems increasing in availability and usage. In such cases, the lost fingerprint can be recovered by re-segmentation from the now compressed multi-finger image record. The second FBI-sponsored tool, CropCoeff was developed by MITRE and thoroughly tested via NIST. CropCoeff enables cropping of the replacement single print directly from the compressed data file, thus avoiding decompression and recompression of images that might degrade fingerprint features necessary for matching.

Presentation Attack Detection for Iris Recognition System Using NIR Camera Sensor

Science.gov (United States)

Nguyen, Dat Tien; Baek, Na Rae; Pham, Tuyen Danh; Park, Kang Ryoung

2018-01-01

Among biometric recognition systems such as fingerprint, finger-vein, or face, the iris recognition system has proven to be effective for achieving a high recognition accuracy and security level. However, several recent studies have indicated that an iris recognition system can be fooled by using presentation attack images that are recaptured using high-quality printed images or by contact lenses with printed iris patterns. As a result, this potential threat can reduce the security level of an iris recognition system. In this study, we propose a new presentation attack detection (PAD) method for an iris recognition system (iPAD) using a near infrared light (NIR) camera image. To detect presentation attack images, we first localized the iris region of the input iris image using circular edge detection (CED). Based on the result of iris localization, we extracted the image features using deep learning-based and handcrafted-based methods. The input iris images were then classified into real and presentation attack categories using support vector machines (SVM). Through extensive experiments with two public datasets, we show that our proposed method effectively solves the iris recognition presentation attack detection problem and produces detection accuracy superior to previous studies. PMID:29695113

Presentation Attack Detection for Iris Recognition System Using NIR Camera Sensor

Directory of Open Access Journals (Sweden)

Dat Tien Nguyen

2018-04-01

Full Text Available Among biometric recognition systems such as fingerprint, finger-vein, or face, the iris recognition system has proven to be effective for achieving a high recognition accuracy and security level. However, several recent studies have indicated that an iris recognition system can be fooled by using presentation attack images that are recaptured using high-quality printed images or by contact lenses with printed iris patterns. As a result, this potential threat can reduce the security level of an iris recognition system. In this study, we propose a new presentation attack detection (PAD method for an iris recognition system (iPAD using a near infrared light (NIR camera image. To detect presentation attack images, we first localized the iris region of the input iris image using circular edge detection (CED. Based on the result of iris localization, we extracted the image features using deep learning-based and handcrafted-based methods. The input iris images were then classified into real and presentation attack categories using support vector machines (SVM. Through extensive experiments with two public datasets, we show that our proposed method effectively solves the iris recognition presentation attack detection problem and produces detection accuracy superior to previous studies.

Presentation Attack Detection for Iris Recognition System Using NIR Camera Sensor.

Science.gov (United States)

Nguyen, Dat Tien; Baek, Na Rae; Pham, Tuyen Danh; Park, Kang Ryoung

2018-04-24

Among biometric recognition systems such as fingerprint, finger-vein, or face, the iris recognition system has proven to be effective for achieving a high recognition accuracy and security level. However, several recent studies have indicated that an iris recognition system can be fooled by using presentation attack images that are recaptured using high-quality printed images or by contact lenses with printed iris patterns. As a result, this potential threat can reduce the security level of an iris recognition system. In this study, we propose a new presentation attack detection (PAD) method for an iris recognition system (iPAD) using a near infrared light (NIR) camera image. To detect presentation attack images, we first localized the iris region of the input iris image using circular edge detection (CED). Based on the result of iris localization, we extracted the image features using deep learning-based and handcrafted-based methods. The input iris images were then classified into real and presentation attack categories using support vector machines (SVM). Through extensive experiments with two public datasets, we show that our proposed method effectively solves the iris recognition presentation attack detection problem and produces detection accuracy superior to previous studies.

ORIENTATION FIELD RECONSTRUCTION OF ALTERED FINGERPRINT USING ORTHOGONAL WAVELETS

Directory of Open Access Journals (Sweden)

Mini M.G.

2016-11-01

Full Text Available Ridge orientation field is an important feature for fingerprint matching and fingerprint reconstruction. Matching of the altered fingerprint against its unaltered mates can be done by extracting the available features in the altered fingerprint and using it along with approximated ridge orientation. This paper presents a method for approximating ridge orientation field of altered fingerprints. In the proposed method, sine and cosine of doubled orientation of the fingerprint is decomposed using orthogonal wavelets and reconstructed back using only the approximation coefficients. No prior information about the singular points is needed for orientation approximation. The method is found suitable for orientation estimation of low quality fingerprint images also.

8 CFR 1236.5 - Fingerprints and photographs.

Science.gov (United States)

2010-01-01

... 8 Aliens and Nationality 1 2010-01-01 2010-01-01 false Fingerprints and photographs. 1236.5... ORDERED REMOVED Detention of Aliens Prior to Order of Removal § 1236.5 Fingerprints and photographs. Every... photographed. Such fingerprints and photographs shall be made available to Federal, State, and local law...

Near-Optimal Fingerprinting with Constraints

Directory of Open Access Journals (Sweden)

Gulyás Gábor György

2016-10-01

Full Text Available Several recent studies have demonstrated that people show large behavioural uniqueness. This has serious privacy implications as most individuals become increasingly re-identifiable in large datasets or can be tracked, while they are browsing the web, using only a couple of their attributes, called as their fingerprints. Often, the success of these attacks depends on explicit constraints on the number of attributes learnable about individuals, i.e., the size of their fingerprints. These constraints can be budget as well as technical constraints imposed by the data holder. For instance, Apple restricts the number of applications that can be called by another application on iOS in order to mitigate the potential privacy threats of leaking the list of installed applications on a device. In this work, we address the problem of identifying the attributes (e.g., smartphone applications that can serve as a fingerprint of users given constraints on the size of the fingerprint. We give the best fingerprinting algorithms in general, and evaluate their effectiveness on several real-world datasets. Our results show that current privacy guards limiting the number of attributes that can be queried about individuals is insufficient to mitigate their potential privacy risks in many practical cases.

Attack Potential Evaluation in Desktop and Smartphone Fingerprint Sensors: Can They Be Attacked by Anyone?

Directory of Open Access Journals (Sweden)

Ines Goicoechea-Telleria

2018-01-01

Full Text Available The use of biometrics keeps growing. Every day, we use biometric recognition to unlock our phones or to have access to places such as the gym or the office, so we rely on the security manufacturers offer when protecting our privileges and private life. It is well known that it is possible to hack into a fingerprint sensor using fake fingers made of Play-Doh and other easy-to-obtain materials but to what extent? Is this true for all users or only for specialists with a deep knowledge on biometrics? Are smartphone fingerprint sensors as reliable as desktop sensors? To answer these questions, we performed 3 separate evaluations. First, we evaluated 4 desktop fingerprint sensors of different technologies by attacking them with 7 different fake finger materials. All of them were successfully attacked by an experienced attacker. Secondly, we carried out a similar test on 5 smartphones with embedded sensors using the most successful materials, which also hacked the 5 sensors. Lastly, we gathered 15 simulated attackers with no background in biometrics to create fake fingers of several materials, and they had one week to attack the fingerprint sensors of the same 5 smartphones, with the starting point of a short video with the techniques to create them. All 5 smartphones were successfully attacked by an inexperienced attacker. This paper will provide the results achieved, as well as an analysis on the attack potential of every case. All results are given following the metrics of the standard ISO/IEC 30107-3.

A Novel Iris Segmentation Scheme

Directory of Open Access Journals (Sweden)

Chen-Chung Liu

2014-01-01

Full Text Available One of the key steps in the iris recognition system is the accurate iris segmentation from its surrounding noises including pupil, sclera, eyelashes, and eyebrows of a captured eye-image. This paper presents a novel iris segmentation scheme which utilizes the orientation matching transform to outline the outer and inner iris boundaries initially. It then employs Delogne-Kåsa circle fitting (instead of the traditional Hough transform to further eliminate the outlier points to extract a more precise iris area from an eye-image. In the extracted iris region, the proposed scheme further utilizes the differences in the intensity and positional characteristics of the iris, eyelid, and eyelashes to detect and delete these noises. The scheme is then applied on iris image database, UBIRIS.v1. The experimental results show that the presented scheme provides a more effective and efficient iris segmentation than other conventional methods.

Olfactory fingerprints for major histocompatibility complex-determined body odors.

Science.gov (United States)

Schaefer, M L; Young, D A; Restrepo, D

2001-04-01

Recognition of individual body odors is analogous to human face recognition in that it provides information about identity. Individual body odors determined by differences at the major histocompatibility complex (MHC or H-2) have been shown to influence mate choice, pregnancy block, and maternal behavior in mice. Unfortunately, the mechanism and extent of the main olfactory bulb (MOB) and accessory olfactory bulb (AOB) involvement in the discrimination of animals according to H-2-type has remained ambiguous. Here we study the neuronal activation patterns evoked in the MOB in different individuals on exposure to these complex, biologically meaningful sensory stimuli. We demonstrate that body odors from H-2 disparate mice evoke overlapping but distinct maps of neuronal activation in the MOB. The spatial patterns of odor-evoked activity are sufficient to be used like fingerprints to predict H-2 identity using a novel computer algorithm. These results provide functional evidence for discrimination of H-2-determined body odors in the MOB, but do not preclude a role for the AOB. These data further our understanding of the neural strategies used to decode socially relevant odors.

Microbial DNA fingerprinting of human fingerprints: dynamic colonization of fingertip microflora challenges human host inferences for forensic purposes.

Science.gov (United States)

Tims, Sebastian; van Wamel, Willem; Endtz, Hubert P; van Belkum, Alex; Kayser, Manfred

2010-09-01

Human fingertip microflora is transferred to touched objects and may provide forensically relevant information on individual hosts, such as on geographic origins, if endogenous microbial skin species/strains would be retrievable from physical fingerprints and would carry geographically restricted DNA diversity. We tested the suitability of physical fingerprints for revealing human host information, with geographic inference as example, via microbial DNA fingerprinting. We showed that the transient exogenous fingertip microflora is frequently different from the resident endogenous bacteria of the same individuals. In only 54% of the experiments, the DNA analysis of the transient fingertip microflora allowed the detection of defined, but often not the major, elements of the resident microflora. Although we found microbial persistency in certain individuals, time-wise variation of transient and resident microflora within individuals was also observed when resampling fingerprints after 3 weeks. While microbial species differed considerably in their frequency spectrum between fingerprint samples from volunteers in Europe and southern Asia, there was no clear geographic distinction between Staphylococcus strains in a cluster analysis, although bacterial genotypes did not overlap between both continental regions. Our results, though limited in quantity, clearly demonstrate that the dynamic fingerprint microflora challenges human host inferences for forensic purposes including geographic ones. Overall, our results suggest that human fingerprint microflora is too dynamic to allow for forensic marker developments for retrieving human information.

Attendance fingerprint identification system using arduino and single board computer

Science.gov (United States)

Muchtar, M. A.; Seniman; Arisandi, D.; Hasanah, S.

2018-03-01

Fingerprint is one of the most unique parts of the human body that distinguishes one person from others and is easily accessed. This uniqueness is supported by technology that can automatically identify or recognize a person called fingerprint sensor. Yet, the existing Fingerprint Sensor can only do fingerprint identification on one machine. For the mentioned reason, we need a method to be able to recognize each user in a different fingerprint sensor. The purpose of this research is to build fingerprint sensor system for fingerprint data management to be centralized so identification can be done in each Fingerprint Sensor. The result of this research shows that by using Arduino and Raspberry Pi, data processing can be centralized so that fingerprint identification can be done in each fingerprint sensor with 98.5 % success rate of centralized server recording.

Entropy based fingerprint for local crystalline order

Science.gov (United States)

Piaggi, Pablo M.; Parrinello, Michele

2017-09-01

We introduce a new fingerprint that allows distinguishing between liquid-like and solid-like atomic environments. This fingerprint is based on an approximate expression for the entropy projected on individual atoms. When combined with local enthalpy, this fingerprint acquires an even finer resolution and it is capable of discriminating between different crystal structures.

Forensic Chemistry: The Revelation of Latent Fingerprints

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Friesen, J. Brent

2015-01-01

The visualization of latent fingerprints often involves the use of a chemical substance that creates a contrast between the fingerprint residues and the surface on which the print was deposited. The chemical-aided visualization techniques can be divided into two main categories: those that chemically react with the fingerprint residue and those…

FINGERPRINT DETECTION AND RECOGNIZATION TECHNIQUES USING GABOR FILTER

OpenAIRE

Yogita Verma*, Prof. Bhagwati Charan Patel

2017-01-01

Fingerprints are most extensively and effectively appropriate for the proof of identity in present days. Mostly because of their uniqueness among the people, public acceptance, originality, stability through life, and their least risk of invasion. Fingerprint technology, which is basically a biometric system, is utilized to identify an individual based on their physical qualities. Fingerprint matching is the trendiest biometric method appropriate to provide authentication. Fingerprint verific...

Interoperability between Fingerprint Biometric Systems: An Empirical Study

OpenAIRE

Gashi, I.; Mason, S.; Lugini, L.; Marasco, E.; Cukic, B.

2014-01-01

Fingerprints are likely the most widely used biometric in commercial as well as law enforcement applications. With the expected rapid growth of fingerprint authentication in mobile devices their importance justifies increased demands for dependability. An increasing number of new sensors,applications and a diverse user population also intensify concerns about the interoperability in fingerprint authentication. In most applications, fingerprints captured for user enrollment with one device may...

A medium resolution fingerprint matching system

Directory of Open Access Journals (Sweden)

Ayman Mohammad Bahaa-Eldin

2013-09-01

Full Text Available In this paper, a novel minutiae based fingerprint matching system is proposed. The system is suitable for medium resolution fingerprint images obtained by low cost commercial sensors. The paper presents a new thinning algorithm, a new features extraction and representation, and a novel feature distance matching algorithm. The proposed system is rotation and translation invariant and is suitable for complete or partial fingerprint matching. The proposed algorithms are optimized to be executed on low resource environments both in CPU power and memory space. The system was evaluated using a standard fingerprint dataset and good performance and accuracy were achieved under certain image quality requirements. In addition, the proposed system was compared favorably to that of the state of the art systems.

Fast 3D magnetic resonance fingerprinting for a whole-brain coverage.

Science.gov (United States)

Ma, Dan; Jiang, Yun; Chen, Yong; McGivney, Debra; Mehta, Bhairav; Gulani, Vikas; Griswold, Mark

2018-04-01

The purpose of this study was to accelerate the acquisition and reconstruction time of 3D magnetic resonance fingerprinting scans. A 3D magnetic resonance fingerprinting scan was accelerated by using a single-shot spiral trajectory with an undersampling factor of 48 in the x-y plane, and an interleaved sampling pattern with an undersampling factor of 3 through plane. Further acceleration came from reducing the waiting time between neighboring partitions. The reconstruction time was accelerated by applying singular value decomposition compression in k-space. Finally, a 3D premeasured B 1 map was used to correct for the B 1 inhomogeneity. The T 1 and T 2 values of the International Society for Magnetic Resonance in Medicine/National Institute of Standards and Technology MRI phantom showed a good agreement with the standard values, with an average concordance correlation coefficient of 0.99, and coefficient of variation of 7% in the repeatability scans. The results from in vivo scans also showed high image quality in both transverse and coronal views. This study applied a fast acquisition scheme for a fully quantitative 3D magnetic resonance fingerprinting scan with a total acceleration factor of 144 as compared with the Nyquist rate, such that 3D T 1 , T 2 , and proton density maps can be acquired with whole-brain coverage at clinical resolution in less than 5 min. Magn Reson Med 79:2190-2197, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Low rank magnetic resonance fingerprinting.

Science.gov (United States)

Mazor, Gal; Weizman, Lior; Tal, Assaf; Eldar, Yonina C

2016-08-01

Magnetic Resonance Fingerprinting (MRF) is a relatively new approach that provides quantitative MRI using randomized acquisition. Extraction of physical quantitative tissue values is preformed off-line, based on acquisition with varying parameters and a dictionary generated according to the Bloch equations. MRF uses hundreds of radio frequency (RF) excitation pulses for acquisition, and therefore high under-sampling ratio in the sampling domain (k-space) is required. This under-sampling causes spatial artifacts that hamper the ability to accurately estimate the quantitative tissue values. In this work, we introduce a new approach for quantitative MRI using MRF, called Low Rank MRF. We exploit the low rank property of the temporal domain, on top of the well-known sparsity of the MRF signal in the generated dictionary domain. We present an iterative scheme that consists of a gradient step followed by a low rank projection using the singular value decomposition. Experiments on real MRI data demonstrate superior results compared to conventional implementation of compressed sensing for MRF at 15% sampling ratio.

Sex Determination from Fingerprint Ridge Density | Gungadin ...

African Journals Online (AJOL)

This study was conducted with an aim to establish a relationship between sex and fingerprint ridge density. The fingerprints were taken from 500 subjects (250 males and 250 females) in the age group of 18-60 years. After taking fingerprints, the ridges were counted in the upper portion of the radial border of each print for all ...

Integrated fingerprinting in secure digital cinema projection

Science.gov (United States)

Delannay, Damien; Delaigle, Jean-Francois; Macq, Benoit M. M.; Quisquater, Jean-Jacques; Mas Ribes, Joan M.; Boucqueau, Jean M.; Nivart, Jean-Francois

2001-12-01

This paper describes the functional model of a combined conditional access and fingerprinting copyright (-or projectionright) protection system in a digital cinema framework. In the cinema industry, a large part of early movie piracy comes from copies made in the theater itself with a camera. The evolution towards digital cinema broadcast enables watermark based fingerprinting protection systems. Besides an appropriate fingerprinting technology, a number of well defined security/cryptographic tools are integrated in order to guaranty the integrity of the whole system. The requirements are two-fold: On one side, we must ensure that the media content is only accessible at exhibition time (under specific authorization obtained after an ad-hoc film rental agreement) and contains the related exhibition fingerprint. At the other end, we must prove our ability to retrieve the fingerprint information from an illegal copy of the media.

Enhancing security of fingerprints through contextual biometric watermarking.

Science.gov (United States)

Noore, Afzel; Singh, Richa; Vatsa, Mayank; Houck, Max M

2007-07-04

This paper presents a novel digital watermarking technique using face and demographic text data as multiple watermarks for verifying the chain of custody and protecting the integrity of a fingerprint image. The watermarks are embedded in selected texture regions of a fingerprint image using discrete wavelet transform. Experimental results show that modifications in these locations are visually imperceptible and maintain the minutiae details. The integrity of the fingerprint image is verified through the high matching scores obtained from an automatic fingerprint identification system. There is also a high degree of visual correlation between the embedded images, and the extracted images from the watermarked fingerprint. The degree of similarity is computed using pixel-based metrics and human visual system metrics. The results also show that the proposed watermarked fingerprint and the extracted images are resilient to common attacks such as compression, filtering, and noise.

Multi-stream face recognition for crime-fighting

Science.gov (United States)

Jassim, Sabah A.; Sellahewa, Harin

2007-04-01

Automatic face recognition (AFR) is a challenging task that is increasingly becoming the preferred biometric trait for identification and has the potential of becoming an essential tool in the fight against crime and terrorism. Closed-circuit television (CCTV) cameras have increasingly been used over the last few years for surveillance in public places such as airports, train stations and shopping centers. They are used to detect and prevent crime, shoplifting, public disorder and terrorism. The work of law-enforcing and intelligence agencies is becoming more reliant on the use of databases of biometric data for large section of the population. Face is one of the most natural biometric traits that can be used for identification and surveillance. However, variations in lighting conditions, facial expressions, face size and pose are a great obstacle to AFR. This paper is concerned with using waveletbased face recognition schemes in the presence of variations of expressions and illumination. In particular, we will investigate the use of a combination of wavelet frequency channels for a multi-stream face recognition using various wavelet subbands as different face signal streams. The proposed schemes extend our recently developed face veri.cation scheme for implementation on mobile devices. We shall present experimental results on the performance of our proposed schemes for a number of face databases including a new AV database recorded on a PDA. By analyzing the various experimental data, we shall demonstrate that the multi-stream approach is robust against variations in illumination and facial expressions than the previous single-stream approach.

Fingerprint and Face Identification for Large User Population

Directory of Open Access Journals (Sweden)

Teddy Ko

2003-06-01

Full Text Available The main objective of this paper is to present the state-of-the-art of the current biometric (fingerprint and face technology, lessons learned during the investigative analysis performed to ascertain the benefits of using combined fingerprint and facial technologies, and recommendations for the use of current available fingerprint and face identification technologies for optimum identification performance for applications using large user population. Prior fingerprint and face identification test study results have shown that their identification accuracies are strongly dependent on the image quality of the biometric inputs. Recommended methodologies for ensuring the capture of acceptable quality fingerprint and facial images of subjects are also presented in this paper.

A Method to Integrate GMM, SVM and DTW for Speaker Recognition

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Ing-Jr Ding

2014-01-01

Full Text Available This paper develops an effective and efficient scheme to integrate Gaussian mixture model (GMM, support vector machine (SVM, and dynamic time wrapping (DTW for automatic speaker recognition. GMM and SVM are two popular classifiers for speaker recognition applications. DTW is a fast and simple template matching method, and it is frequently seen in applications of speech recognition. In this work, DTW does not play a role to perform speech recognition, and it will be employed to be a verifier for verification of valid speakers. The proposed combination scheme of GMM, SVM and DTW, called SVMGMM-DTW, for speaker recognition in this study is a two-phase verification process task including GMM-SVM verification of the first phase and DTW verification of the second phase. By providing a double check to verify the identity of a speaker, it will be difficult for imposters to try to pass the security protection; therefore, the safety degree of speaker recognition systems will be largely increased. A series of experiments designed on door access control applications demonstrated that the superiority of the developed SVMGMM-DTW on speaker recognition accuracy.

A multi-approach feature extractions for iris recognition

Science.gov (United States)

Sanpachai, H.; Settapong, M.

2014-04-01

Biometrics is a promising technique that is used to identify individual traits and characteristics. Iris recognition is one of the most reliable biometric methods. As iris texture and color is fully developed within a year of birth, it remains unchanged throughout a person's life. Contrary to fingerprint, which can be altered due to several aspects including accidental damage, dry or oily skin and dust. Although iris recognition has been studied for more than a decade, there are limited commercial products available due to its arduous requirement such as camera resolution, hardware size, expensive equipment and computational complexity. However, at the present time, technology has overcome these obstacles. Iris recognition can be done through several sequential steps which include pre-processing, features extractions, post-processing, and matching stage. In this paper, we adopted the directional high-low pass filter for feature extraction. A box-counting fractal dimension and Iris code have been proposed as feature representations. Our approach has been tested on CASIA Iris Image database and the results are considered successful.

Fingerprint: A Unique and Reliable Method for Identification

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Palash Kumar Bose

2017-01-01

Full Text Available Fingerprints have been the gold standard for personal identification within the forensic community for more than one hundred years. It is still universal in spite of discovery of DNA fingerprint. The science of fingerprint identification has evolved over time from the early use of finger prints to mark business transactions in ancient Babylonia to their use today as core technology in biometric security devices and as scientific evidence in courts of law throughout the world. The science of fingerprints, dactylography or dermatoglyphics, had long been widely accepted, and well acclaimed and reputed as panacea for individualization, particularly in forensic investigations. Human fingerprints are detailed, unique, difficult to alter, and durable over the life of an individual, making them suitable as lifelong markers of human identity. Fingerprints can be readily used by police or other authorities to identify individuals who wish to conceal their identity, or to identify people who are incapacitated or deceased, as in the aftermath of a natural disaster

OPTIMAL EXPERIMENT DESIGN FOR MAGNETIC RESONANCE FINGERPRINTING

OpenAIRE

Zhao, Bo; Haldar, Justin P.; Setsompop, Kawin; Wald, Lawrence L.

2016-01-01

Magnetic resonance (MR) fingerprinting is an emerging quantitative MR imaging technique that simultaneously acquires multiple tissue parameters in an efficient experiment. In this work, we present an estimation-theoretic framework to evaluate and design MR fingerprinting experiments. More specifically, we derive the Cram��r-Rao bound (CRB), a lower bound on the covariance of any unbiased estimator, to characterize parameter estimation for MR fingerprinting. We then formulate an optimal experi...

Image Processing and Features Extraction of Fingerprint Images ...

African Journals Online (AJOL)

To demonstrate the importance of the image processing of fingerprint images prior to image enrolment or comparison, the set of fingerprint images in databases (a) and (b) of the FVC (Fingerprint Verification Competition) 2000 database were analyzed using a features extraction algorithm. This paper presents the results of ...

FINGERPRINT MATCHING BASED ON PORE CENTROIDS

Directory of Open Access Journals (Sweden)

S. Malathi

2011-05-01

Full Text Available In recent years there has been exponential growth in the use of bio- metrics for user authentication applications. Automated Fingerprint Identification systems have become popular tool in many security and law enforcement applications. Most of these systems rely on minutiae (ridge ending and bifurcation features. With the advancement in sensor technology, high resolution fingerprint images (1000 dpi pro- vide micro level of features (pores that have proven to be useful fea- tures for identification. In this paper, we propose a new strategy for fingerprint matching based on pores by reliably extracting the pore features The extraction of pores is done by Marker Controlled Wa- tershed segmentation method and the centroids of each pore are con- sidered as feature vectors for matching of two fingerprint images. Experimental results shows that the proposed method has better per- formance with lower false rates and higher accuracy.

Fingerprint enhancement using a multispectral sensor

Science.gov (United States)

Rowe, Robert K.; Nixon, Kristin A.

2005-03-01

The level of performance of a biometric fingerprint sensor is critically dependent on the quality of the fingerprint images. One of the most common types of optical fingerprint sensors relies on the phenomenon of total internal reflectance (TIR) to generate an image. Under ideal conditions, a TIR fingerprint sensor can produce high-contrast fingerprint images with excellent feature definition. However, images produced by the same sensor under conditions that include dry skin, dirt on the skin, and marginal contact between the finger and the sensor, are likely to be severely degraded. This paper discusses the use of multispectral sensing as a means to collect additional images with new information about the fingerprint that can significantly augment the system performance under both normal and adverse sample conditions. In the context of this paper, "multispectral sensing" is used to broadly denote a collection of images taken under different illumination conditions: different polarizations, different illumination/detection configurations, as well as different wavelength illumination. Results from three small studies using an early-stage prototype of the multispectral-TIR (MTIR) sensor are presented along with results from the corresponding TIR data. The first experiment produced data from 9 people, 4 fingers from each person and 3 measurements per finger under "normal" conditions. The second experiment provided results from a study performed to test the relative performance of TIR and MTIR images when taken under extreme dry and dirty conditions. The third experiment examined the case where the area of contact between the finger and sensor is greatly reduced.

Recovery of latent fingerprints and DNA on human skin.

Science.gov (United States)

Färber, Doris; Seul, Andrea; Weisser, Hans-Joachim; Bohnert, Michael

2010-11-01

The project "Latent Fingerprints and DNA on Human Skin" was the first systematic research in Europe dealing with detection of fingerprints and DNA left by offenders on the skin of corpses. One thousand samples gave results that allow general statements on the materials and methods used. The tests were carried out according to a uniform trial structure. Fingerprints were deposited by natural donors on corpses. The latent fingerprints were treated with magnetic powder or black fingerprint powder. Afterward, they were lifted with silicone casting material (Isomark(®)) or gelatine foil. All lifts were swabbed to recover DNA. It was possible to visualize comparable and identifiable fingerprints on the skin of corpses (16%). In the same categories, magnetic powder (18.4%) yielded better results than black fingerprint powder (13.6%). The number of comparable and identifiable fingerprints decreased on the lifts (12.7%). Isomark(®) (14.9%) was the better lifting material in comparison with gelatine foil (10.1%). In one-third of the samples, DNA could be extracted from the powdered and lifted latents. Black fingerprint powder delivered the better result with a rate of 2.2% for full DNA profiles and profiles useful for exclusion in comparison with 1.8% for the magnetic powder traces. Isomark(®) (3.1%) yielded better results than gelatine foil (0.6%). © 2010 American Academy of Forensic Sciences.

Cell Identification based on Received Signal Strength Fingerprints: Concept and Application towards Energy Saving in Cellular Networks

Directory of Open Access Journals (Sweden)

Elke Roth-Mandutz

2014-09-01

Full Text Available The increasing deployment of small cells aimed at off-loading data traffic from macrocells in heterogeneous networks has resulted in a drastic increase in energy consumption in cellular networks. Energy consumption can be optimized in a selforganized way by adapting the number of active cells in response to the current traffic demand. In this paper we concentrate on the complex problem of how to identify small cells to be reactivated in situations where multiple cells are concurrently inactive. Solely based on the received signal strength, we present cell-specific patterns for the generation of unique cell fingerprints. The cell fingerprints of the deactivated cells are matched with measurements from a high data rate demanding mobile device to identify the most appropriate candidate. Our scheme results in a matching success rate of up to 100% to identify the best cell depending on the number of cells to be activated.

Towards reconstruction of overlapping fingerprints using plasma spectroscopy

Science.gov (United States)

Yang, Jun-Ho; Choi, Soo-Jin; Yoh, Jack J.

2017-08-01

Chemical analysis is commonly used in the field of forensic science where the precise discrimination of primary evidence is of significant importance. Laser-Induced Breakdown Spectroscopy (LIBS) exceeds other spectroscopic methods in terms of the time required for pre- and post-sample preparation, the insensitivity to sample phase state be it solid, liquid, or gas, and the detection of two-dimensional spectral mapping from real time point measurements. In this research, fingerprint samples on various surface materials are considered in the chemical detection and reconstruction of fingerprints using the two-dimensional LIBS technique. Strong and distinct intensities of specific wavelengths represent visible ink, natural secretion of sweat, and contaminants from the environment, all of which can be present in latent fingerprints. The particular aim of the work presented here is to enhance the precision of the two-dimensional recreation of the fingerprints present on metal, plastic, and artificially prepared soil surface using LIBS with principal component analysis. By applying a distinct wavelength discrimination for two overlapping fingerprint samples, separation into two non-identical chemical fingerprints was successfully performed.

Color Textons for Texture Recognition

NARCIS (Netherlands)

Burghouts, G.J.; Geusebroek, J.M.

2006-01-01

Texton models have proven to be very discriminative for the recognition of grayvalue images taken from rough textures. To further improve the discriminative power of the distinctive texton models of Varma and Zisserman (VZ model) (IJCV, vol. 62(1), pp. 61-81, 2005), we propose two schemes to exploit

Gender recognition from unconstrained and articulated human body.

Science.gov (United States)

Wu, Qin; Guo, Guodong

2014-01-01

Gender recognition has many useful applications, ranging from business intelligence to image search and social activity analysis. Traditional research on gender recognition focuses on face images in a constrained environment. This paper proposes a method for gender recognition in articulated human body images acquired from an unconstrained environment in the real world. A systematic study of some critical issues in body-based gender recognition, such as which body parts are informative, how many body parts are needed to combine together, and what representations are good for articulated body-based gender recognition, is also presented. This paper also pursues data fusion schemes and efficient feature dimensionality reduction based on the partial least squares estimation. Extensive experiments are performed on two unconstrained databases which have not been explored before for gender recognition.

Gender Recognition from Unconstrained and Articulated Human Body

Science.gov (United States)

Wu, Qin; Guo, Guodong

2014-01-01

Gender recognition has many useful applications, ranging from business intelligence to image search and social activity analysis. Traditional research on gender recognition focuses on face images in a constrained environment. This paper proposes a method for gender recognition in articulated human body images acquired from an unconstrained environment in the real world. A systematic study of some critical issues in body-based gender recognition, such as which body parts are informative, how many body parts are needed to combine together, and what representations are good for articulated body-based gender recognition, is also presented. This paper also pursues data fusion schemes and efficient feature dimensionality reduction based on the partial least squares estimation. Extensive experiments are performed on two unconstrained databases which have not been explored before for gender recognition. PMID:24977203

CNNs flag recognition preprocessing scheme based on gray scale stretching and local binary pattern

Science.gov (United States)

Gong, Qian; Qu, Zhiyi; Hao, Kun

2017-07-01

Flag is a rather special recognition target in image recognition because of its non-rigid features with the location, scale and rotation characteristics. The location change can be handled well by the depth learning algorithm Convolutional Neural Networks (CNNs), but the scale and rotation changes are quite a challenge for CNNs. Since it has good rotation and gray scale invariance, the local binary pattern (LBP) is combined with grayscale stretching and CNNs to make LBP and grayscale stretching as CNNs pretreatment, which can not only significantly improve the efficiency of flag recognition, but can also evaluate the recognition effect through ROC, accuracy, MSE and quality factor.

Face recognition in securing optical telecom network equipment

International Nuclear Information System (INIS)

Ali, N.M.

2015-01-01

In this paper, face recognition is used with a microcontroller based hardware module to secure the telecommunication equipments like ONU (optical network units) or any other telecommunication equipment. The face recognition classifier value optimization adaption is deployed and in this scheme by increasing or decreasing the number of images in the database will automatically generate and adopt the classifier value for recognition of known and unknown persons. On recognizing and unknown persons. On recognizing an unknown person, the hardware module will send an SMS to the concerned security personnel for security preventive measures. (author)

Gender Recognition from Unconstrained and Articulated Human Body

Directory of Open Access Journals (Sweden)

Qin Wu

2014-01-01

human body images acquired from an unconstrained environment in the real world. A systematic study of some critical issues in body-based gender recognition, such as which body parts are informative, how many body parts are needed to combine together, and what representations are good for articulated body-based gender recognition, is also presented. This paper also pursues data fusion schemes and efficient feature dimensionality reduction based on the partial least squares estimation. Extensive experiments are performed on two unconstrained databases which have not been explored before for gender recognition.

Distributed construction of quantum fingerprints

OpenAIRE

Ambainis, Andris; Shi, Yaoyun

2003-01-01

Quantum fingerprints are useful quantum encodings introduced by Buhrman, Cleve, Watrous, and de Wolf (Physical Review Letters, Volume 87, Number 16, Article 167902, 2001; quant-ph/0102001) in obtaining an efficient quantum communication protocol. We design a protocol for constructing the fingerprint in a distributed scenario. As an application, this protocol gives rise to a communication protocol more efficient than the best known classical protocol for a communication problem.

Secure fingerprint identification based on structural and microangiographic optical coherence tomography.

Science.gov (United States)

Liu, Xuan; Zaki, Farzana; Wang, Yahui; Huang, Qiongdan; Mei, Xin; Wang, Jiangjun

2017-03-10

Optical coherence tomography (OCT) allows noncontact acquisition of fingerprints and hence is a highly promising technology in the field of biometrics. OCT can be used to acquire both structural and microangiographic images of fingerprints. Microangiographic OCT derives its contrast from the blood flow in the vasculature of viable skin tissue, and microangiographic fingerprint imaging is inherently immune to fake fingerprint attack. Therefore, dual-modality (structural and microangiographic) OCT imaging of fingerprints will enable more secure acquisition of biometric data, which has not been investigated before. Our study on fingerprint identification based on structural and microangiographic OCT imaging is, we believe, highly innovative. In this study, we performed OCT imaging study for fingerprint acquisition, and demonstrated the capability of dual-modality OCT imaging for the identification of fake fingerprints.

Study of noninvasive detection of latent fingerprints using UV laser

Science.gov (United States)

Li, Hong-xia; Cao, Jing; Niu, Jie-qing; Huang, Yun-gang; Mao, Lin-jie; Chen, Jing-rong

2011-06-01

Latent fingerprints present a considerable challenge in forensics, and noninvasive procedure that captures a digital image of the latent fingerprints is significant in the field of criminal investigation. The capability of photography technologies using 266nm UV Nd:YAG solid state laser as excitation light source to provide detailed images of unprocessed latent fingerprints is demonstrated. Unprocessed latent fingerprints were developed on various non-absorbent and absorbing substrates. According to the special absorption, reflection, scattering and fluorescence characterization of the various residues in fingerprints (fatty acid ester, protein, and carbosylic acid salts etc) to the UV light to weaken or eliminate the background disturbance and increase the brightness contrast of fingerprints with the background, and using 266nm UV laser as excitation light source, fresh and old latent fingerprints on the surface of four types of non-absorbent objects as magazine cover, glass, back of cellphone, wood desktop paintwork and two types of absorbing objects as manila envelope, notebook paper were noninvasive detected and appeared through reflection photography and fluorescence photography technologies, and the results meet the fingerprint identification requirements in forensic science.

A multi-view face recognition system based on cascade face detector and improved Dlib

Science.gov (United States)

Zhou, Hongjun; Chen, Pei; Shen, Wei

2018-03-01

In this research, we present a framework for multi-view face detect and recognition system based on cascade face detector and improved Dlib. This method is aimed to solve the problems of low efficiency and low accuracy in multi-view face recognition, to build a multi-view face recognition system, and to discover a suitable monitoring scheme. For face detection, the cascade face detector is used to extracted the Haar-like feature from the training samples, and Haar-like feature is used to train a cascade classifier by combining Adaboost algorithm. Next, for face recognition, we proposed an improved distance model based on Dlib to improve the accuracy of multiview face recognition. Furthermore, we applied this proposed method into recognizing face images taken from different viewing directions, including horizontal view, overlooks view, and looking-up view, and researched a suitable monitoring scheme. This method works well for multi-view face recognition, and it is also simulated and tested, showing satisfactory experimental results.

Cognitive Fingerprints

Science.gov (United States)

2015-03-25

is another cognitive fingerprint that has been used extensively for authorship . This work has been ex- tended to authentication by relating keyboard...this work is the inference of high-level features such as personality, gender , and dominant hand but those features have not been integrated to date

Iris Recognition Using Feature Extraction of Box Counting Fractal Dimension

Science.gov (United States)

Khotimah, C.; Juniati, D.

2018-01-01

Biometrics is a science that is now growing rapidly. Iris recognition is a biometric modality which captures a photo of the eye pattern. The markings of the iris are distinctive that it has been proposed to use as a means of identification, instead of fingerprints. Iris recognition was chosen for identification in this research because every human has a special feature that each individual is different and the iris is protected by the cornea so that it will have a fixed shape. This iris recognition consists of three step: pre-processing of data, feature extraction, and feature matching. Hough transformation is used in the process of pre-processing to locate the iris area and Daugman’s rubber sheet model to normalize the iris data set into rectangular blocks. To find the characteristics of the iris, it was used box counting method to get the fractal dimension value of the iris. Tests carried out by used k-fold cross method with k = 5. In each test used 10 different grade K of K-Nearest Neighbor (KNN). The result of iris recognition was obtained with the best accuracy was 92,63 % for K = 3 value on K-Nearest Neighbor (KNN) method.

Joint Feature Extraction and Classifier Design for ECG-Based Biometric Recognition.

Science.gov (United States)

Gutta, Sandeep; Cheng, Qi

2016-03-01

Traditional biometric recognition systems often utilize physiological traits such as fingerprint, face, iris, etc. Recent years have seen a growing interest in electrocardiogram (ECG)-based biometric recognition techniques, especially in the field of clinical medicine. In existing ECG-based biometric recognition methods, feature extraction and classifier design are usually performed separately. In this paper, a multitask learning approach is proposed, in which feature extraction and classifier design are carried out simultaneously. Weights are assigned to the features within the kernel of each task. We decompose the matrix consisting of all the feature weights into sparse and low-rank components. The sparse component determines the features that are relevant to identify each individual, and the low-rank component determines the common feature subspace that is relevant to identify all the subjects. A fast optimization algorithm is developed, which requires only the first-order information. The performance of the proposed approach is demonstrated through experiments using the MIT-BIH Normal Sinus Rhythm database.

DNA fingerprinting in botany: past, present, future.

Science.gov (United States)

Nybom, Hilde; Weising, Kurt; Rotter, Björn

2014-01-03

Almost three decades ago Alec Jeffreys published his seminal Nature papers on the use of minisatellite probes for DNA fingerprinting of humans (Jeffreys and colleagues Nature 1985, 314:67-73 and Nature 1985, 316:76-79). The new technology was soon adopted for many other organisms including plants, and when Hilde Nybom, Kurt Weising and Alec Jeffreys first met at the very First International Conference on DNA Fingerprinting in Berne, Switzerland, in 1990, everybody was enthusiastic about the novel method that allowed us for the first time to discriminate between humans, animals, plants and fungi on the individual level using DNA markers. A newsletter coined "Fingerprint News" was launched, T-shirts were sold, and the proceedings of the Berne conference filled a first book on "DNA fingerprinting: approaches and applications". Four more conferences were about to follow, one on each continent, and Alec Jeffreys of course was invited to all of them. Since these early days, methodologies have undergone a rapid evolution and diversification. A multitude of techniques have been developed, optimized, and eventually abandoned when novel and more efficient and/or more reliable methods appeared. Despite some overlap between the lifetimes of the different technologies, three phases can be defined that coincide with major technological advances. Whereas the first phase of DNA fingerprinting ("the past") was dominated by restriction fragment analysis in conjunction with Southern blot hybridization, the advent of the PCR in the late 1980s gave way to the development of PCR-based single- or multi-locus profiling techniques in the second phase. Given that many routine applications of plant DNA fingerprinting still rely on PCR-based markers, we here refer to these methods as "DNA fingerprinting in the present", and include numerous examples in the present review. The beginning of the third phase actually dates back to 2005, when several novel, highly parallel DNA sequencing

An Introduction to Face Recognition Technology

Directory of Open Access Journals (Sweden)

Shang-Hung Lin

2000-01-01

Full Text Available Recently face recognition is attracting much attention in the society of network multimedia information access.  Areas such as network security, content indexing and retrieval, and video compression benefits from face recognition technology because "people" are the center of attention in a lot of video.  Network access control via face recognition not only makes hackers virtually impossible to steal one's "password", but also increases the user-friendliness in human-computer interaction.  Indexing and/or retrieving video data based on the appearances of particular persons will be useful for users such as news reporters, political scientists, and moviegoers.  For the applications of videophone and teleconferencing, the assistance of face recognition also provides a more efficient coding scheme.  In this paper, we give an introductory course of this new information processing technology.  The paper shows the readers the generic framework for the face recognition system, and the variants that are frequently encountered by the face recognizer.  Several famous face recognition algorithms, such as eigenfaces and neural networks, will also be explained.

Noisy Ocular Recognition Based on Three Convolutional Neural Networks

Directory of Open Access Journals (Sweden)

Min Beom Lee

2017-12-01

Full Text Available In recent years, the iris recognition system has been gaining increasing acceptance for applications such as access control and smartphone security. When the images of the iris are obtained under unconstrained conditions, an issue of undermined quality is caused by optical and motion blur, off-angle view (the user’s eyes looking somewhere else, not into the front of the camera, specular reflection (SR and other factors. Such noisy iris images increase intra-individual variations and, as a result, reduce the accuracy of iris recognition. A typical iris recognition system requires a near-infrared (NIR illuminator along with an NIR camera, which are larger and more expensive than fingerprint recognition equipment. Hence, many studies have proposed methods of using iris images captured by a visible light camera without the need for an additional illuminator. In this research, we propose a new recognition method for noisy iris and ocular images by using one iris and two periocular regions, based on three convolutional neural networks (CNNs. Experiments were conducted by using the noisy iris challenge evaluation-part II (NICE.II training dataset (selected from the university of Beira iris (UBIRIS.v2 database, mobile iris challenge evaluation (MICHE database, and institute of automation of Chinese academy of sciences (CASIA-Iris-Distance database. As a result, the method proposed by this study outperformed previous methods.

Noisy Ocular Recognition Based on Three Convolutional Neural Networks.

Science.gov (United States)

Lee, Min Beom; Hong, Hyung Gil; Park, Kang Ryoung

2017-12-17

In recent years, the iris recognition system has been gaining increasing acceptance for applications such as access control and smartphone security. When the images of the iris are obtained under unconstrained conditions, an issue of undermined quality is caused by optical and motion blur, off-angle view (the user's eyes looking somewhere else, not into the front of the camera), specular reflection (SR) and other factors. Such noisy iris images increase intra-individual variations and, as a result, reduce the accuracy of iris recognition. A typical iris recognition system requires a near-infrared (NIR) illuminator along with an NIR camera, which are larger and more expensive than fingerprint recognition equipment. Hence, many studies have proposed methods of using iris images captured by a visible light camera without the need for an additional illuminator. In this research, we propose a new recognition method for noisy iris and ocular images by using one iris and two periocular regions, based on three convolutional neural networks (CNNs). Experiments were conducted by using the noisy iris challenge evaluation-part II (NICE.II) training dataset (selected from the university of Beira iris (UBIRIS).v2 database), mobile iris challenge evaluation (MICHE) database, and institute of automation of Chinese academy of sciences (CASIA)-Iris-Distance database. As a result, the method proposed by this study outperformed previous methods.

Optimal experiment design for magnetic resonance fingerprinting.

Science.gov (United States)

Bo Zhao; Haldar, Justin P; Setsompop, Kawin; Wald, Lawrence L

2016-08-01

Magnetic resonance (MR) fingerprinting is an emerging quantitative MR imaging technique that simultaneously acquires multiple tissue parameters in an efficient experiment. In this work, we present an estimation-theoretic framework to evaluate and design MR fingerprinting experiments. More specifically, we derive the Cramér-Rao bound (CRB), a lower bound on the covariance of any unbiased estimator, to characterize parameter estimation for MR fingerprinting. We then formulate an optimal experiment design problem based on the CRB to choose a set of acquisition parameters (e.g., flip angles and/or repetition times) that maximizes the signal-to-noise ratio efficiency of the resulting experiment. The utility of the proposed approach is validated by numerical studies. Representative results demonstrate that the optimized experiments allow for substantial reduction in the length of an MR fingerprinting acquisition, and substantial improvement in parameter estimation performance.

Missing data reconstruction using Gaussian mixture models for fingerprint images

Science.gov (United States)

Agaian, Sos S.; Yeole, Rushikesh D.; Rao, Shishir P.; Mulawka, Marzena; Troy, Mike; Reinecke, Gary

2016-05-01

Publisher's Note: This paper, originally published on 25 May 2016, was replaced with a revised version on 16 June 2016. If you downloaded the original PDF, but are unable to access the revision, please contact SPIE Digital Library Customer Service for assistance. One of the most important areas in biometrics is matching partial fingerprints in fingerprint databases. Recently, significant progress has been made in designing fingerprint identification systems for missing fingerprint information. However, a dependable reconstruction of fingerprint images still remains challenging due to the complexity and the ill-posed nature of the problem. In this article, both binary and gray-level images are reconstructed. This paper also presents a new similarity score to evaluate the performance of the reconstructed binary image. The offered fingerprint image identification system can be automated and extended to numerous other security applications such as postmortem fingerprints, forensic science, investigations, artificial intelligence, robotics, all-access control, and financial security, as well as for the verification of firearm purchasers, driver license applicants, etc.

Uniqueness: skews bit occurrence frequencies in randomly generated fingerprint libraries.

Science.gov (United States)

Chen, Nelson G

2016-08-01

Requiring that randomly generated chemical fingerprint libraries have unique fingerprints such that no two fingerprints are identical causes a systematic skew in bit occurrence frequencies, the proportion at which specified bits are set. Observed frequencies (O) at which each bit is set within the resulting libraries systematically differ from frequencies at which bits are set at fingerprint generation (E). Observed frequencies systematically skew toward 0.5, with the effect being more pronounced as library size approaches the compound space, which is the total number of unique possible fingerprints given the number of bit positions each fingerprint contains. The effect is quantified for varying library sizes as a fraction of the overall compound space, and for changes in the specified frequency E. The cause and implications for this systematic skew are subsequently discussed. When generating random libraries of chemical fingerprints, the imposition of a uniqueness requirement should either be avoided or taken into account.

Utilizing AFIS searching tools to reduce errors in fingerprint casework.

Science.gov (United States)

Langenburg, Glenn; Hall, Carey; Rosemarie, Quincy

2015-12-01

Fifty-six (56) adjudicated, property crime cases involving fingerprint evidence were reviewed using a case-specific AFIS database tool. This tool allowed fingerprint experts to search latent prints in the cases against a database of friction ridge exemplars limited to only the individuals specific to that particular case. We utilized three different methods to encode and search the latent prints: automatic feature extraction, manual encoding performed by a student intern, and manual encoding performed by a fingerprint expert. Performance in the study was strongest when the encoding was conducted by the fingerprint expert. The results of the study showed that while the AFIS tools failed to locate all of the identifications originally reported by the initial fingerprint expert that worked the case, the AFIS tools helped to identify 7 additional latent prints that were not reported by the initial fingerprint expert. We conclude that this technology, when combined with fingerprint expertise, will reduce the number of instances where an erroneous exclusion could occur, increase the efficiency of a fingerprint unit, and be a useful tool for reviewing active or cold cases for missed opportunities to report identifications. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

On the introduction of secondary fingerprint classification

CSIR Research Space (South Africa)

Msiza, IS

2011-07-01

Full Text Available The concept of fingerprint classification is an important one because of the need to, before executing a database search procedure, virtually break the fingerprint template database into smaller, manageable partitions. This is done in order to avoid...

Snake Model Based on Improved Genetic Algorithm in Fingerprint Image Segmentation

Directory of Open Access Journals (Sweden)

Mingying Zhang

2016-12-01

Full Text Available Automatic fingerprint identification technology is a quite mature research field in biometric identification technology. As the preprocessing step in fingerprint identification, fingerprint segmentation can improve the accuracy of fingerprint feature extraction, and also reduce the time of fingerprint preprocessing, which has a great significance in improving the performance of the whole system. Based on the analysis of the commonly used methods of fingerprint segmentation, the existing segmentation algorithm is improved in this paper. The snake model is used to segment the fingerprint image. Additionally, it is improved by using the global optimization of the improved genetic algorithm. Experimental results show that the algorithm has obvious advantages both in the speed of image segmentation and in the segmentation effect.

Efficient Filtering of Noisy Fingerprint Images

Directory of Open Access Journals (Sweden)

Maria Liliana Costin

2016-01-01

Full Text Available Fingerprint identification is an important field in the wide domain of biometrics with many applications, in different areas such: judicial, mobile phones, access systems, airports. There are many elaborated algorithms for fingerprint identification, but none of them can guarantee that the results of identification are always 100 % accurate. A first step in a fingerprint image analysing process consists in the pre-processing or filtering. If the result after this step is not by a good quality the upcoming identification process can fail. A major difficulty can appear in case of fingerprint identification if the images that should be identified from a fingerprint image database are noisy with different type of noise. The objectives of the paper are: the successful completion of the noisy digital image filtering, a novel more robust algorithm of identifying the best filtering algorithm and the classification and ranking of the images. The choice about the best filtered images of a set of 9 algorithms is made with a dual method of fuzzy and aggregation model. We are proposing through this paper a set of 9 filters with different novelty designed for processing the digital images using the following methods: quartiles, medians, average, thresholds and histogram equalization, applied all over the image or locally on small areas. Finally the statistics reveal the classification and ranking of the best algorithms.

H.264/AVC digital fingerprinting based on spatio-temporal just noticeable distortion

Science.gov (United States)

Ait Saadi, Karima; Bouridane, Ahmed; Guessoum, Abderrezak

2014-01-01

This paper presents a robust adaptive embedding scheme using a modified Spatio-Temporal noticeable distortion (JND) model that is designed for tracing the distribution of the H.264/AVC video content and protecting them from unauthorized redistribution. The Embedding process is performed during coding process in selected macroblocks type Intra 4x4 within I-Frame. The method uses spread-spectrum technique in order to obtain robustness against collusion attacks and the JND model to dynamically adjust the embedding strength and control the energy of the embedded fingerprints so as to ensure their imperceptibility. Linear and non linear collusion attacks are performed to show the robustness of the proposed technique against collusion attacks while maintaining visual quality unchanged.

Study on Accuracy of Judgments by Chinese Fingerprint Examiners

Directory of Open Access Journals (Sweden)

Shiquan Liu

2015-01-01

Full Text Available The interpretation of fingerprint evidence depends on the judgments of fingerprint examiners. This study assessed the accuracy of different judgments made by fingerprint examiners following the Analysis, Comparison, and Evaluation (ACE process. Each examiner was given five marks for analysis, comparison, and evaluation. We compared the experts′ judgments against the ground truth and used an annotation platform to evaluate how Chinese fingerprint examiners document their comparisons during the identification process. The results showed that different examiners demonstrated different accuracy of judgments and different mechanisms to reach them.

Fingerprints as a Proxy for Readership of Sales Flyers

DEFF Research Database (Denmark)

Schmidt, Marcus J.; Krause, Niels; Solgaard, Hans Stubbe

2007-01-01

  Can readership of sales flyers and free newspapers be estimated by revealing fingerprints? In this paper we report the results of an empirical analysis based on 4604 flyer-pages conducted to assess the feasibility of the method. Results are encouraging, and indicate that the method presently may...... serve as a conservative estimate of readership. Advertising management may thus use the fingerprints-approach as an alternative audience measure and thereby assess the convergent validity of the traditional interview method and the fingerprint approach. While the fingerprint method appears valid...

Evaluation of fingerprint deformation using optical coherence tomography

Science.gov (United States)

Gutierrez da Costa, Henrique S.; Maxey, Jessica R.; Silva, Luciano; Ellerbee, Audrey K.

2014-02-01

Biometric identification systems have important applications to privacy and security. The most widely used of these, print identification, is based on imaging patterns present in the fingers, hands and feet that are formed by the ridges, valleys and pores of the skin. Most modern print sensors acquire images of the finger when pressed against a sensor surface. Unfortunately, this pressure may result in deformations, characterized by changes in the sizes and relative distances of the print patterns, and such changes have been shown to negatively affect the performance of fingerprint identification algorithms. Optical coherence tomography (OCT) is a novel imaging technique that is capable of imaging the subsurface of biological tissue. Hence, OCT may be used to obtain images of subdermal skin structures from which one can extract an internal fingerprint. The internal fingerprint is very similar in structure to the commonly used external fingerprint and is of increasing interest in investigations of identify fraud. We proposed and tested metrics based on measurements calculated from external and internal fingerprints to evaluate the amount of deformation of the skin. Such metrics were used to test hypotheses about the differences of deformation between the internal and external images, variations with the type of finger and location inside the fingerprint.

A network identity authentication system based on Fingerprint identification technology

Science.gov (United States)

Xia, Hong-Bin; Xu, Wen-Bo; Liu, Yuan

2005-10-01

Fingerprint verification is one of the most reliable personal identification methods. However, most of the automatic fingerprint identification system (AFIS) is not run via Internet/Intranet environment to meet today's increasing Electric commerce requirements. This paper describes the design and implementation of the archetype system of identity authentication based on fingerprint biometrics technology, and the system can run via Internet environment. And in our system the COM and ASP technology are used to integrate Fingerprint technology with Web database technology, The Fingerprint image preprocessing algorithms are programmed into COM, which deployed on the internet information server. The system's design and structure are proposed, and the key points are discussed. The prototype system of identity authentication based on Fingerprint have been successfully tested and evaluated on our university's distant education applications in an internet environment.

Capacity and optimal collusion attack channels for Gaussian fingerprinting games

Science.gov (United States)

Wang, Ying; Moulin, Pierre

2007-02-01

In content fingerprinting, the same media covertext - image, video, audio, or text - is distributed to many users. A fingerprint, a mark unique to each user, is embedded into each copy of the distributed covertext. In a collusion attack, two or more users may combine their copies in an attempt to "remove" their fingerprints and forge a pirated copy. To trace the forgery back to members of the coalition, we need fingerprinting codes that can reliably identify the fingerprints of those members. Researchers have been focusing on designing or testing fingerprints for Gaussian host signals and the mean square error (MSE) distortion under some classes of collusion attacks, in terms of the detector's error probability in detecting collusion members. For example, under the assumptions of Gaussian fingerprints and Gaussian attacks (the fingerprinted signals are averaged and then the result is passed through a Gaussian test channel), Moulin and Briassouli1 derived optimal strategies in a game-theoretic framework that uses the detector's error probability as the performance measure for a binary decision problem (whether a user participates in the collusion attack or not); Stone2 and Zhao et al. 3 studied average and other non-linear collusion attacks for Gaussian-like fingerprints; Wang et al. 4 stated that the average collusion attack is the most efficient one for orthogonal fingerprints; Kiyavash and Moulin 5 derived a mathematical proof of the optimality of the average collusion attack under some assumptions. In this paper, we also consider Gaussian cover signals, the MSE distortion, and memoryless collusion attacks. We do not make any assumption about the fingerprinting codes used other than an embedding distortion constraint. Also, our only assumptions about the attack channel are an expected distortion constraint, a memoryless constraint, and a fairness constraint. That is, the colluders are allowed to use any arbitrary nonlinear strategy subject to the above

Recognition of beer brand based on multivariate analysis of volatile fingerprint.

Science.gov (United States)

Cajka, Tomas; Riddellova, Katerina; Tomaniova, Monika; Hajslova, Jana

2010-06-18

Automated head-space solid-phase microextraction (HS-SPME)-based sampling procedure, coupled to gas chromatography-time-of-flight mass spectrometry (GC-TOFMS), was developed and employed for obtaining of fingerprints (GC profiles) of beer volatiles. In total, 265 speciality beer samples were collected over a 1-year period with the aim to distinguish, based on analytical (profiling) data, (i) the beers labelled as Rochefort 8; (ii) a group consisting of Rochefort 6, 8, 10 beers; and (iii) Trappist beers. For the chemometric evaluation of the data, partial least squares discriminant analysis (PLS-DA), linear discriminant analysis (LDA), and artificial neural networks with multilayer perceptrons (ANN-MLP) were tested. The best prediction ability was obtained for the model that distinguished a group of Rochefort 6, 8, 10 beers from the rest of beers. In this case, all chemometric tools employed provided 100% correct classification. Slightly worse prediction abilities were achieved for the models "Trappist vs. non-Trappist beers" with the values of 93.9% (PLS-DA), 91.9% (LDA) and 97.0% (ANN-MLP) and "Rochefort 8 vs. the rest" with the values of 87.9% (PLS-DA) and 84.8% (LDA) and 93.9% (ANN-MLP). In addition to chromatographic profiling, also the potential of direct coupling of SPME (extraction/pre-concentration device) with high-resolution TOFMS employing a direct analysis in real time (DART) ion source has been demonstrated as a challenging profiling approach. Copyright (c) 2010 Elsevier B.V. All rights reserved.

Analytical fingerprint for tantalum ores from African deposits

Science.gov (United States)

Melcher, F.; Graupner, T.; Sitnikova, M.; Oberthür, T.; Henjes-Kunst, F.; Gäbler, E.; Rantitsch, G.

2009-04-01

Kibaran age either show flat patterns for most tantalites, rising values from the LREE to the HREE, or trough-like patterns. Eu anomalies are strongly negative in columbite-tantalite from the Alto Ligonha Province in Mozambique, from the Namaqualand Province (Namibia, South Africa), and from Zimbabwe. Four main age populations of coltan deposits in Africa were revealed: (1) Archean (>2.5 Ga), (2) Paleoproterozoic (2.1-1.9 Ga), (3) early Neoproterozoic ("Kibaran", 1.0-0.9 Ga), and (4) late Neoproterozoic to early Paleozoic (Pan-African; ca. 0.6-0.4 Ga). Currently, we focus on the resolution of the fingerprinting system from region via ore province down to deposit scale, establishing a large and high-quality analytical data base, and developing fast-screening and low-cost methods. Analytical flow-charts and identification schemes for coltan ores will be presented at the Conference. The analytical results obtained so far indicate that a certification scheme including fingerprinting of sources of coltan ores is feasible. The methodology developed is capable to assist in the establishment of a control instrument in an envisaged certification of the production and trade chain of coltan.

Chemical Fingerprinting of Materials Developed Due To Environmental Issues

Science.gov (United States)

Smith, Doris A.; McCool, A. (Technical Monitor)

2000-01-01

This paper presents viewgraphs on chemical fingerprinting of materials developed due to environmental issues. Some of the topics include: 1) Aerospace Materials; 2) Building Blocks of Capabilities; 3) Spectroscopic Techniques; 4) Chromatographic Techniques; 5) Factors that Determine Fingerprinting Approach; and 6) Fingerprinting: Combination of instrumental analysis methods that diagnostically characterize a material.

[Studies on fingerprinting of Flos Buddleja by RP-HPLC].

Science.gov (United States)

Han, Peng; Cui, Ya-jun; Guo, Hong-zhu; Guo, De-an

2004-10-01

To establish fingerprinting of Flos Buddleja by using RP-HPLC for the quality control. The HPLC condition was as follows: Inertsil ODS-3 C18 analytical column (4.6 mm x 250 mm, 5 microm), gredient eluation with MeCN (0.1% TFA)-H2O (0.1%TFA), flow rate 1.0 mL x min(-1), detection wavelength 254 nm. 10 commercial samples were analyzed to establish a fingerprinting. Among the obtained fingerprinting, most of the detected peaks were separated effectively. The accuracy, repeatability and stability of this method were satisfied. The RSDs of relative retention time and area of aimed peaks which existed in all samples wereless than 5%. Theresults were in accordance with the request of fingerprinting. The established fingerprinting can be used for the quality control of Flos Buddleja.

Fingerprint matching on smart card: A review

CSIR Research Space (South Africa)

Baruni, Kedimotse P

2016-12-01

Full Text Available Fingerprint Match-on-Card (MoC) offers the highest degree of privacy and security to cardholders as the fingerprint never leaves the secure environment of a smart card. The level of security of a biometric system is evaluated by the location where...

Laser mass spectrometry for DNA fingerprinting for forensic applications

Energy Technology Data Exchange (ETDEWEB)

Chen, C.H.; Tang, K.; Taranenko, N.I.; Allman, S.L.; Chang, L.Y.

1994-12-31

The application of DNA fingerprinting has become very broad in forensic analysis, patient identification, diagnostic medicine, and wildlife poaching, since every individual`s DNA structure is identical within all tissues of their body. DNA fingerprinting was initiated by the use of restriction fragment length polymorphisms (RFLP). In 1987, Nakamura et al. found that a variable number of tandem repeats (VNTR) often occurred in the alleles. The probability of different individuals having the same number of tandem repeats in several different alleles is very low. Thus, the identification of VNTR from genomic DNA became a very reliable method for identification of individuals. DNA fingerprinting is a reliable tool for forensic analysis. In DNA fingerprinting, knowledge of the sequence of tandem repeats and restriction endonuclease sites can provide the basis for identification. The major steps for conventional DNA fingerprinting include (1) specimen processing (2) amplification of selected DNA segments by PCR, and (3) gel electrophoresis to do the final DNA analysis. In this work we propose to use laser desorption mass spectrometry for fast DNA fingerprinting. The process and advantages are discussed.

FPRandom: Randomizing core browser objects to break advanced device fingerprinting techniques

OpenAIRE

Laperdrix , Pierre; Baudry , Benoit; Mishra , Vikas

2017-01-01

International audience; The rich programming interfaces (APIs) provided by web browsers can be diverted to collect a browser fingerprint. A small number of queries on these interfaces are sufficient to build a fingerprint that is statistically unique and very stable over time. Consequently, the fingerprint can be used to track users. Our work aims at mitigating the risk of browser fingerprinting for users privacy by 'breaking' the stability of a fingerprint over time. We add randomness in the...

Straightforward fabrication of black nano silica dusting powder for latent fingerprint imaging

Science.gov (United States)

Komalasari, Isna; Krismastuti, Fransiska Sri Herwahyu; Elishian, Christine; Handayani, Eka Mardika; Nugraha, Willy Cahya; Ketrin, Rosi

2017-11-01

Imaging of latent fingerprint pattern (aka fingermark) is one of the most important and accurate detection methods in forensic investigation because of the characteristic of individual fingerprint. This detection technique relies on the mechanical adherence of fingerprint powder to the moisture and oily component of the skin left on the surface. The particle size of fingerprint powder is one of the critical parameter to obtain excellent fingerprint image. This study develops a simple, cheap and straightforward method to fabricate Nano size black dusting fingerprint powder based on Nano silica and applies the powder to visualize latent fingerprint. The nanostructured silica was prepared from tetraethoxysilane (TEOS) and then modified with Nano carbon, methylene blue and sodium acetate to color the powder. Finally, as a proof-of-principle, the ability of this black Nano silica dusting powder to image latent fingerprint is successfully demonstrated and the results show that this fingerprint powder provides clearer fingerprint pattern compared to the commercial one highlighting the potential application of the nanostructured silica in forensic science.

An Investigation on the Problem of Thinning in Fingerprint Processing

Directory of Open Access Journals (Sweden)

I. O. Omeiza

2012-06-01

Full Text Available A high-integrity thinning procedure for binarised fingerprints is proposed in this paper. Several authors and software developers have approached the thinning problems in fingerprint-processing differently. Their approach produced in most cases, fingerprint skeletons with low reliability and thus require additional minutiae-pruning stage to discard the erroneous minutiae in the obtained skeletons. The work involves a careful blending of some already existing algorithms to achieve optimal performance in thinning binarised fingerprint images. The algorithms considered are as follows. The "Zhang and Suen" parallel algorithm for thinning digital patterns, the improved parallel thinning algorithm by Holt and company and template-based thinning algorithm by Stentiford and Mortimer. The idea of combining these stand-alone algorithms to improve the quality of obtained objects skeleton in general image processing was first suggested in a text by Parker in 1998. However, his work does not specifically address the fingerprint problem. This work has examined and proves the plausibility of this thinning approach in the particular case of fingerprint application domain. The thinning procedure obtained satisfactory skeletons for fingerprint applications.

Making DNA Fingerprints.

Science.gov (United States)

Nunley, Kathie F.

1996-01-01

Presents an activity to simulate electrophoresis using everyday items. Uses adding machine paper to construct a set of DNA fingerprints that can be used to solve crime cases designed by students in any biology class. (JRH)

Vitality detection in personal authentication systems using fingerprints

OpenAIRE

Coli, Pietro

2008-01-01

Fingerprints are considered as the sign of each human being, and this has contributed the development of biometric applications based on such features. Since 2002, an important vulnerability has been shown: it is possible to deceive fingerprint scanners through artificial replicas of fingertips. In order to address this shortcoming it is need to recognize a spoofing attempt with artificial fingers looking for some “life signs” each time an user submit a fingerprint (vitality detection problem...

Generating cancelable fingerprint templates.

Science.gov (United States)

Ratha, Nalini K; Chikkerur, Sharat; Connell, Jonathan H; Bolle, Ruud M

2007-04-01

Biometrics-based authentication systems offer obvious usability advantages over traditional password and token-based authentication schemes. However, biometrics raises several privacy concerns. A biometric is permanently associated with a user and cannot be changed. Hence, if a biometric identifier is compromised, it is lost forever and possibly for every application where the biometric is used. Moreover, if the same biometric is used in multiple applications, a user can potentially be tracked from one application to the next by cross-matching biometric databases. In this paper, we demonstrate several methods to generate multiple cancelable identifiers from fingerprint images to overcome these problems. In essence, a user can be given as many biometric identifiers as needed by issuing a new transformation "key." The identifiers can be cancelled and replaced when compromised. We empirically compare the performance of several algorithms such as Cartesian, polar, and surface folding transformations of the minutiae positions. It is demonstrated through multiple experiments that we can achieve revocability and prevent cross-matching of biometric databases. It is also shown that the transforms are noninvertible by demonstrating that it is computationally as hard to recover the original biometric identifier from a transformed version as by randomly guessing. Based on these empirical results and a theoretical analysis we conclude that feature-level cancelable biometric construction is practicable in large biometric deployments.

The thermodynamics of latent fingerprint corrosion of metal elements and alloys.

Science.gov (United States)

Bond, John W

2008-11-01

Redox reactions taking place between the surface of a metal and fingerprint residue have been expressed thermodynamically in terms of both the Nernst equation for reduction potential and the complexation constant for the formation of complex metal halide ions in aqueous solution. These expressions are used to explain experimental results for the corrosion of 10 different metal elements by fingerprint residue in air at room temperature. Corrosion of noble metals, such as silver and gold, supports the proposition that the degree of metal corrosion is enhanced by the presence of chloride ions in eccrine sweat. Extending the experiments to include 10 metal alloys enabled the construction of a fingerprint corrosion series for 20 different metals. Fingerprint corrosion on metals alloyed with > approximately 40% copper was found to display third level fingerprint detail. A comparison of both conventional ink on paper and digital (Livescan) fingerprinting techniques with fingerprints deposited on 9 Karat gold alloy has shown that gold alloy depositions are least susceptible to third level detail obliteration by poor fingerprint capturing techniques.

Screen Fingerprints as a Novel Modality for Active Authentication

Science.gov (United States)

2014-03-01

Screen fingerprint is the new cyber biometric modality that we have proposed to measure and analyze active authentication. The screen finger ...as a new biometric modality for active authentication. Such a fingerprint is acquired by taking a screen recording of the computer being used and...extracting discriminative visual feature from the recording. 15. SUBJECT TERMS Active authentication, screen fingerprints, biometrics 16. SECURITY

Fingerprinting Mobile Devices Using Personalized Configurations

Directory of Open Access Journals (Sweden)

Kurtz Andreas

2016-01-01

Full Text Available Recently, Apple removed access to various device hardware identifiers that were frequently misused by iOS third-party apps to track users. We are, therefore, now studying the extent to which users of smartphones can still be uniquely identified simply through their personalized device configurations. Using Apple’s iOS as an example, we show how a device fingerprint can be computed using 29 different configuration features. These features can be queried from arbitrary thirdparty apps via the official SDK. Experimental evaluations based on almost 13,000 fingerprints from approximately 8,000 different real-world devices show that (1 all fingerprints are unique and distinguishable; and (2 utilizing a supervised learning approach allows returning users or their devices to be recognized with a total accuracy of 97% over time

An Analysis of the Privacy Threat in Vehicular Ad Hoc Networks due to Radio Frequency Fingerprinting

Directory of Open Access Journals (Sweden)

Gianmarco Baldini

2017-01-01

Full Text Available In Vehicular Ad Hoc Networks (VANETs used in the road transportation sector, privacy risks may arise because vehicles could be tracked on the basis of the information transmitted by the Vehicle to Vehicle (V2V and Vehicle to Infrastructure (V2I communications implemented with the Dedicated Short Range Communications (DSRC standards operating at 5.9 GHz. Various techniques have been proposed in the literature to mitigate these privacy risks including the use of pseudonym schemes, but they are mostly focused on data anonymization at the network and application layer. At the physical layer, the capability to accurately identify and fingerprint wireless devices through their radio frequency (RF emissions has been demonstrated in the literature. This capability may generate a privacy threat because vehicles can be tracked using the RF emissions of their DSRC devices. This paper investigates the privacy risks related to RF fingerprinting to determine if privacy breaches are feasible in practice. In particular, this paper analyzes the tracking accuracy in challenging RF environments with high attenuation and fading.

An investigation on the problem of thinning in fingerprint processing ...

African Journals Online (AJOL)

A high-integrity thinning procedure for binarised fingerprints is proposed in this paper. Several authors and software developers have approached the thinning problems in fingerprint-processing differently. Their approach produced in most cases, fingerprint skeletons with low reli abi lity and thus require additional ...

Towards a complete rule-based classification approach for flat fingerprints

CSIR Research Space (South Africa)

Webb, L

2014-12-01

Full Text Available fingerprints. This work implements an algorithm which includes new rules to account for more instances of flat fingerprints with missing singular points, specifically when the delta of a Right Loop or Left Loop fingerprint is not captured, when one of the loops...

Extracting subsurface fingerprints using optical coherence tomography

CSIR Research Space (South Africa)

Akhoury, SS

2015-02-01

Full Text Available Subsurface Fingerprints using Optical Coherence Tomography Sharat Saurabh Akhoury, Luke Nicholas Darlow Modelling and Digital Science, Council for Scientific and Industrial Research, Pretoria, South Africa Abstract Physiologists have found... approach to extract the subsurface fingerprint representation using a high-resolution imaging technology known as Optical Coherence Tomography (OCT). ...

Detection and analysis of diamond fingerprinting feature and its application

Energy Technology Data Exchange (ETDEWEB)

Li Xin; Huang Guoliang; Li Qiang; Chen Shengyi, E-mail: tshgl@tsinghua.edu.cn [Department of Biomedical Engineering, the School of Medicine, Tsinghua University, Beijing, 100084 (China)

2011-01-01

Before becoming a jewelry diamonds need to be carved artistically with some special geometric features as the structure of the polyhedron. There are subtle differences in the structure of this polyhedron in each diamond. With the spatial frequency spectrum analysis of diamond surface structure, we can obtain the diamond fingerprint information which represents the 'Diamond ID' and has good specificity. Based on the optical Fourier Transform spatial spectrum analysis, the fingerprinting identification of surface structure of diamond in spatial frequency domain was studied in this paper. We constructed both the completely coherent diamond fingerprinting detection system illuminated by laser and the partially coherent diamond fingerprinting detection system illuminated by led, and analyzed the effect of the coherence of light source to the diamond fingerprinting feature. We studied rotation invariance and translation invariance of the diamond fingerprinting and verified the feasibility of real-time and accurate identification of diamond fingerprint. With the profit of this work, we can provide customs, jewelers and consumers with a real-time and reliable diamonds identification instrument, which will curb diamond smuggling, theft and other crimes, and ensure the healthy development of the diamond industry.

Quality and matching performance analysis of three-dimensional unraveled fingerprints

Science.gov (United States)

Wang, Yongchang; Hao, Qi; Fatehpuria, Abhishika; Hassebrook, Laurence G.; Lau, Daniel L.

2010-07-01

The use of fingerprints as a biometric is both the oldest mode of computer-aided personal identification and the most-relied-on technology in use today. However, current acquisition methods have some challenging and peculiar difficulties. For higher performance fingerprint data acquisition and verification, a novel noncontact 3-D fingerprint scanner is investigated, where both the detailed 3-D and albedo information of the finger is obtained. The obtained high-resolution 3-D prints are further converted into 3-D unraveled prints, to be compatible with traditional 2-D automatic fingerprint identification systems. As a result, many limitations imposed on conventional fingerprint capture and processing can be reduced by the unobtrusiveness of this approach and the extra depth information acquired. To compare the quality and matching performances of 3-D unraveled with traditional 2-D plain fingerprints, we collect both 3-D prints and their 2-D plain counterparts. The print quality and matching performances are evaluated and analyzed by using National Institute of Standard Technology fingerprint software. Experimental results show that the 3-D unraveled print outperforms the 2-D print in both quality and matching performances.

Thinning Zhang-Suen dan Stentiford untuk Menentukan Ekstraksi Ciri (Minutiae Sebagai Identifikasi Pola Sidik Jari

Directory of Open Access Journals (Sweden)

Faiza Alif Fakhrina

2016-11-01

Full Text Available Fingerprint is the skin on the palms of the hands and feet that are covered with small ridge lines. Fingerprint pattern belonging to every human is being unique. There are fingerprint on the ridge pattern will not change during human life. Ridge pattern is characteristic of the fingrprint that can be used for biometric identification. Based on fingerprint ridge pattern into four, namely whorl, ulnar loop, radial loop, and arch. Minutiae Extraction (Crossing Number, Core and Delta, Center Point Location can be used for fingerprint pattern recognition. Some of the methods used in the fingerprint pattern recognition is Minutiae Extraction, and Thinning Zhang-Suen and Stentiford. Croosing Number is used for process Minutiae Extraction, example termination and bifurcation. The classification method used Linear Discriminant Analysis. The result fingerprint pattern recognition is system can recognize fingerprint patter as much as 20 images and system can not recognize fingerprint pattern as much as 10 images. Accuracy of fingerprint pattern recognition is 66%.

SIFT-based Ear Recognition by Fusion of Detected Keypoints from Color Similarity Slice Regions

OpenAIRE

Kisku, Dakshina Ranjan; Mehrotra, Hunny; Gupta, Phalguni; Sing, Jamuna Kanta

2010-01-01

Ear biometric is considered as one of the most reliable and invariant biometrics characteristics in line with iris and fingerprint characteristics. In many cases, ear biometrics can be compared with face biometrics regarding many physiological and texture characteristics. In this paper, a robust and efficient ear recognition system is presented, which uses Scale Invariant Feature Transform (SIFT) as feature descriptor for structural representation of ear images. In order to make it more robus...

Generation of DNA profiles from fingerprints developed with columnar thin film technique.

Science.gov (United States)

Plazibat, Stephanie L; Roy, Reena; Swiontek, Stephen E; Lakhtakia, Akhlesh

2015-12-01

Partial-bloody fingerprints and partial fingerprints with saliva are often encountered at crime scenes, potentially enabling the combination of fingerprint and DNA analyses for absolute identification, provided that the development technique for fingerprint analysis does not inhibit DNA analysis. 36 partial-bloody fingerprints and 30 fingerprints wetted with saliva, all deposited on brass, were first developed using the columnar-thin-film (CTF) technique and then subjected to short tandem repeat (STR) DNA analysis. Equal numbers of samples were subjected to the same DNA analysis without development. Tris (8-hydroxyquinolinato) aluminum, or Alq3, was evaporated to deposit CTFs for development of the prints. DNA was extracted from all 132 samples, quantified, and amplified with AmpFlSTR(®) Identifiler Plus Amplification Kit. Additionally, DNA analyses were conducted on four blood smears on un-fingerprinted brass that had been subjected to CTF deposition and four blood smears on un-fingerprinted brass that had not been subjected to CTF deposition. Complete and concordant autosomal STR profiles of the same quality were obtained from both undeveloped and CTF-developed fingerprints, indicating that CTF development of fingerprints preserves DNA and does not inhibit subsequent DNA analysis. Even when there were no fingerprints, CTF deposition did not lead to inhibition of DNA analysis. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

On Realistically Attacking Tor with Website Fingerprinting

Directory of Open Access Journals (Sweden)

Wang Tao

2016-10-01

Full Text Available Website fingerprinting allows a local, passive observer monitoring a web-browsing client’s encrypted channel to determine her web activity. Previous attacks have shown that website fingerprinting could be a threat to anonymity networks such as Tor under laboratory conditions. However, there are significant differences between laboratory conditions and realistic conditions. First, in laboratory tests we collect the training data set together with the testing data set, so the training data set is fresh, but an attacker may not be able to maintain a fresh data set. Second, laboratory packet sequences correspond to a single page each, but for realistic packet sequences the split between pages is not obvious. Third, packet sequences may include background noise from other types of web traffic. These differences adversely affect website fingerprinting under realistic conditions. In this paper, we tackle these three problems to bridge the gap between laboratory and realistic conditions for website fingerprinting. We show that we can maintain a fresh training set with minimal resources. We demonstrate several classification-based techniques that allow us to split full packet sequences effectively into sequences corresponding to a single page each. We describe several new algorithms for tackling background noise. With our techniques, we are able to build the first website fingerprinting system that can operate directly on packet sequences collected in the wild.

Preventing Wine Counterfeiting by Individual Cork Stopper Recognition Using Image Processing Technologies

Directory of Open Access Journals (Sweden)

Valter Costa

2018-03-01

Full Text Available Wine counterfeiting is a major problem worldwide. Within this context, an approach to the problem of discerning original wine bottles from forged ones is the use of natural features present in the product, object and/or material (using it “as is”. The proposed application uses the cork stopper as a unique fingerprint, combined with state of the art image processing techniques to achieve individual object recognition and smartphones as the authentication equipment. The anti-counterfeiting scheme is divided into two phases: an enrollment phase, where every bottle is registered in a database using a photo of its cork stopper inside the bottle; and a verification phase, where an end-user/retailer captures a photo of the cork stopper using a regular smartphone, compares the photo with the previously-stored one and retrieves it if the wine bottle was previously registered. To evaluate the performance of the proposed application, two datasets of natural/agglomerate cork stoppers were built, totaling 1000 photos. The worst case results show a 100% precision ratio, an accuracy of 99.94% and a recall of 94.00%, using different smartphones. The perfect score in precision is a promising result, proving that this system can be applied to the prevention of wine counterfeiting and consumer/retailer security when purchasing a wine bottle.

Two dimensional molecular electronics spectroscopy for molecular fingerprinting, DNA sequencing, and cancerous DNA recognition.

Science.gov (United States)

Rajan, Arunkumar Chitteth; Rezapour, Mohammad Reza; Yun, Jeonghun; Cho, Yeonchoo; Cho, Woo Jong; Min, Seung Kyu; Lee, Geunsik; Kim, Kwang S

2014-02-25

Laser-driven molecular spectroscopy of low spatial resolution is widely used, while electronic current-driven molecular spectroscopy of atomic scale resolution has been limited because currents provide only minimal information. However, electron transmission of a graphene nanoribbon on which a molecule is adsorbed shows molecular fingerprints of Fano resonances, i.e., characteristic features of frontier orbitals and conformations of physisorbed molecules. Utilizing these resonance profiles, here we demonstrate two-dimensional molecular electronics spectroscopy (2D MES). The differential conductance with respect to bias and gate voltages not only distinguishes different types of nucleobases for DNA sequencing but also recognizes methylated nucleobases which could be related to cancerous cell growth. This 2D MES could open an exciting field to recognize single molecule signatures at atomic resolution. The advantages of the 2D MES over the one-dimensional (1D) current analysis can be comparable to those of 2D NMR over 1D NMR analysis.

Efficient internal and surface fingerprint extraction and blending using optical coherence tomography.

Science.gov (United States)

Darlow, Luke Nicholas; Connan, James

2015-11-01

Optical coherence tomography provides a 3D representation of fingertip skin where surface and internal fingerprints are found. These fingerprints are topographically identical. However, the surface skin is prone to damage, distortion, and spoofing; and the internal fingerprint is difficult to access and extract. This research presents a novel scaling-resolution approach to fingerprint zone detection and extraction. Furthermore, a local-quality-based blending procedure is also proposed. The accuracy of the zone-detection algorithm is comparable to an earlier work, yielding a mean-squared error of 25.9 and structural similarity of 95.8% (compared to a ground-truth estimate). Blending the surface and internal fingerprints improved the National Institute of Science and Technology's Fingerprint Image Quality scores and the average maximum match scores (when matched against conventional surface counterparts). The fingerprint blending procedure was able to combine high-quality regions from both fingerprints, thus mitigating surface wrinkles and anomalous poor-quality regions. Furthermore, spoof detection via a surface-to-internal fingerprint comparison was proposed and tested.

DNA Fingerprinting in a Forensic Teaching Experiment

Science.gov (United States)

Wagoner, Stacy A.; Carlson, Kimberly A.

2008-01-01

This article presents an experiment designed to provide students, in a classroom laboratory setting, a hands-on demonstration of the steps used in DNA forensic analysis by performing DNA extraction, DNA fingerprinting, and statistical analysis of the data. This experiment demonstrates how DNA fingerprinting is performed and how long it takes. It…

8 CFR 236.5 - Fingerprints and photographs.

Science.gov (United States)

2010-01-01

... 8 Aliens and Nationality 1 2010-01-01 2010-01-01 false Fingerprints and photographs. 236.5 Section... to Order of Removal § 236.5 Fingerprints and photographs. Every alien 14 years of age or older... photographs shall be made available to Federal, State, and local law enforcement agencies upon request to the...

Application of DNA fingerprints for cell-line individualization.

Science.gov (United States)

Gilbert, D A; Reid, Y A; Gail, M H; Pee, D; White, C; Hay, R J; O'Brien, S J

1990-09-01

DNA fingerprints of 46 human cell lines were derived using minisatellite probes for hypervariable genetic loci. The incidence of 121 HaeIII DNA fragments among 33 cell lines derived from unrelated individuals was used to estimate allelic and genotypic frequencies for each fragment and for composite individual DNA fingerprints. We present a quantitative estimate of the extent of genetic difference between individuals, an estimate based on the percentage of restriction fragments at which they differ. The average percent difference (APD) among pairwise combinations from the population of 33 unrelated cell lines was 76.9%, compared with the APD in band sharing among cell lines derived from the same individual (less than or equal to 1.2%). Included in this survey were nine additional cell lines previously implicated as HeLa cell derivatives, and these lines were clearly confirmed as such by DNA fingerprints (APD less than or equal to 0.6%). On the basis of fragment frequencies in the tested cell line population, a simple genetic model was developed to estimate the frequencies of each DNA fingerprint in the population. The median incidence was 2.9 X 10(-17), and the range was 2.4 X 10(-21) to 6.6 X 10(-15). This value approximates the probability that a second cell line selected at random from unrelated individuals will match a given DNA fingerprint. Related calculations address the chance that any two DNA fingerprints would be identical among a large group of cell lines. This estimate is still very slight; for example, the chance of two or more common DNA fingerprints among 1 million distinct individuals is less than .001. The procedure provides a straightforward, easily interpreted, and statistically robust method for identification and individualization of human cells.

The Ins and Outs of DNA Fingerprinting the Infectious Fungi

Science.gov (United States)

Soll, David R.

2000-01-01

DNA fingerprinting methods have evolved as major tools in fungal epidemiology. However, no single method has emerged as the method of choice, and some methods perform better than others at different levels of resolution. In this review, requirements for an effective DNA fingerprinting method are proposed and procedures are described for testing the efficacy of a method. In light of the proposed requirements, the most common methods now being used to DNA fingerprint the infectious fungi are described and assessed. These methods include restriction fragment length polymorphisms (RFLP), RFLP with hybridization probes, randomly amplified polymorphic DNA and other PCR-based methods, electrophoretic karyotyping, and sequencing-based methods. Procedures for computing similarity coefficients, generating phylogenetic trees, and testing the stability of clusters are then described. To facilitate the analysis of DNA fingerprinting data, computer-assisted methods are described. Finally, the problems inherent in the collection of test and control isolates are considered, and DNA fingerprinting studies of strain maintenance during persistent or recurrent infections, microevolution in infecting strains, and the origin of nosocomial infections are assessed in light of the preceding discussion of the ins and outs of DNA fingerprinting. The intent of this review is to generate an awareness of the need to verify the efficacy of each DNA fingerprinting method for the level of genetic relatedness necessary to answer the epidemiological question posed, to use quantitative methods to analyze DNA fingerprint data, to use computer-assisted DNA fingerprint analysis systems to analyze data, and to file data in a form that can be used in the future for retrospective and comparative studies. PMID:10756003

Secure Biometric E-Voting Scheme

Science.gov (United States)

Ahmed, Taha Kh.; Aborizka, Mohamed

The implementation of the e-voting becomes more substantial with the rapid increase of e-government development. The recent growth in communications and cryptographic techniques facilitate the implementation of e-voting. Many countries introduced e-voting systems; unfortunately most of these systems are not fully functional. In this paper we will present an e-voting scheme that covers most of the e-voting requirements, smart card and biometric recognition technology were implemented to guarantee voter's privacy and authentication.

Partial Device Fingerprints

NARCIS (Netherlands)

Ciere, M.; Hernandez Ganan, C.; van Eeten, M.J.G.

2017-01-01

In computing, remote devices may be identified by means of device fingerprinting, which works by collecting a myriad of clientside attributes such as the device’s browser and operating system version, installed plugins, screen resolution, hardware artifacts, Wi-Fi settings, and anything else

Diversity of DNA fingerprints in Cryptococcus neoformans.

Science.gov (United States)

Varma, A; Swinne, D; Staib, F; Bennett, J E; Kwon-Chung, K J

1995-07-01

DNA fingerprint patterns of 156 Cryptococcus neoformans isolates (26 AIDS patients, 46 non-AIDS patients, and 40 environmental sources) from both varieties (126 C. neoformans var. neoformans and 30 C. neoformans var. gattii isolates) and from seven countries were analyzed by using the DNA probe UT-4p. Nine and twelve distinct DNA fingerprint patterns were observed for isolates of the C. neoformans var. neoformans and var. gattii, respectively. No pattern was unique to AIDS patients, non-AIDS patients, or the environment. Pattern II was observed more often in non-AIDS patients (8 of 23) than in AIDS patients (0 of 25). Pattern V was the most prevalent pattern (42 of 82) in clinical and environmental isolates. Isolates from three AIDS patients in Burundi and Zaire exhibited patterns identical to each other but different from those of isolates collected from their houses (i.e., dust of floors, walls, etc.) or a nearby pigeon coop. DNA fingerprint stability was determined for 53 isolates from nine non-AIDS patients at different time intervals during 5 to 128 weeks of antifungal therapy. For eight patients, the fingerprint pattern was stable while the ninth may have had a mixed infection. Pattern II was observed in 4 of 9 patients, which is similar to 4 of 14 in other non-AIDS patients as reported here. In spite of the extensive pattern heterogeneity among 15 C. neoformans var. gattii isolates in Australia, the patterns observed in seven California isolates were quite different from those in Australia. Among isolates of C. neoformans var. gattii, one fingerprint pattern (designated b) was observed in several countries of the Far East. The fingerprint patterns of two of three environmental isolates from Eucalyptus camaldulensis trees in Australia were identical to those of 2 of the 12 clinical isolates from the country.

[Identification of two varieties of Citri Fructus by fingerprint and chemometrics].

Science.gov (United States)

Su, Jing-hua; Zhang, Chao; Sun, Lei; Gu, Bing-ren; Ma, Shuang-cheng

2015-06-01

Citri Fructus identification by fingerprint and chemometrics was investigated in this paper. Twenty-three Citri Fructus samples were collected which referred to two varieties as Cirtus wilsonii and C. medica recorded in Chinese Pharmacopoeia. HPLC chromatograms were obtained. The components were partly identified by reference substances, and then common pattern was established for chemometrics analysis. Similarity analysis, principal component analysis (PCA) , partial least squares-discriminant analysis (PLS-DA) and hierarchical cluster analysis heatmap were applied. The results indicated that C. wilsonii and C. medica could be ideally classified with common pattern contained twenty-five characteristic peaks. Besides, preliminary pattern recognition had verified the chemometrics analytical results. Absolute peak area (APA) was used for relevant quantitative analysis, results showed the differences between two varieties and it was valuable for further quality control as selection of characteristic components.

Studies on Chromatographic Fingerprint and Fingerprinting Profile-Efficacy Relationship of Polygoni Perfoliati Herba

Directory of Open Access Journals (Sweden)

Li Tian

2013-01-01

Full Text Available Polygoni Perfoliati Herba is widely used in China with antibacterium, anti-inflammatory, expectorant, antitumor, and antivirus activities. To reveal the mechanisms of the activities of Polygoni Perfoliati Herba, the relationship between the fingerprinting profile and its bioactivities was investigated. In the present study, high-performance liquid chromatographic (HPLC fingerprinting method was developed. The established method was applied to analyze 51 batches of Polygoni Perfoliati Herba samples collected from different locations or in different harvesting times in China. Chemometrics, including similarity analysis, hierarchical clustering analysis, and principal component analysis, were used to express their similarities. It was found that similarity values of the samples were in the range of 0.432–0.998. The results of analgesic tests indicated that Polygoni Perfoliati Herba could significantly inhibit pain induced by hot plate and acetic acid in mice. The results of anti-inflammatory tests showed that Polygoni Perfoliati Herba had good anti-inflammatory effects (P < 0.01 in two models including dimethyl benzene-induced ear edema and acetic acid-induced peritoneal permeability in mice. Combining the results from chromatographic fingerprints with those from bioactivities, we found that seven peaks from Polygoni Perfoliati Herba were mainly responsible for analgesic and anti-inflammatory activities.

Teaching DNA Fingerprinting using a Hands-on Simulation.

Science.gov (United States)

Schug, Thatcher

1998-01-01

Presents an inexpensive hands-on lesson in DNA fingerprinting that can be completed in a single class period. Involves students in solving a murder in which a drop of blood is fingerprinted and matched with the blood of the murderer. (DDR)

DNA fingerprinting of the NCI-60 cell line panel.

Science.gov (United States)

Lorenzi, Philip L; Reinhold, William C; Varma, Sudhir; Hutchinson, Amy A; Pommier, Yves; Chanock, Stephen J; Weinstein, John N

2009-04-01

The National Cancer Institute's NCI-60 cell line panel, the most extensively characterized set of cells in existence and a public resource, is frequently used as a screening tool for drug discovery. Because many laboratories around the world rely on data from the NCI-60 cells, confirmation of their genetic identities represents an essential step in validating results from them. Given the consequences of cell line contamination or misidentification, quality control measures should routinely include DNA fingerprinting. We have, therefore, used standard DNA microsatellite short tandem repeats to profile the NCI-60, and the resulting DNA fingerprints are provided here as a reference. Consistent with previous reports, the fingerprints suggest that several NCI-60 lines have common origins: the melanoma lines MDA-MB-435, MDA-N, and M14; the central nervous system lines U251 and SNB-19; the ovarian lines OVCAR-8 and OVCAR-8/ADR (also called NCI/ADR); and the prostate lines DU-145, DU-145 (ATCC), and RC0.1. Those lines also show that the ability to connect two fingerprints to the same origin is not affected by stable transfection or by the development of multidrug resistance. As expected, DNA fingerprints were not able to distinguish different tissues-of-origin. The fingerprints serve principally as a barcodes.

Multi-task pose-invariant face recognition.

Science.gov (United States)

Ding, Changxing; Xu, Chang; Tao, Dacheng

2015-03-01

Face images captured in unconstrained environments usually contain significant pose variation, which dramatically degrades the performance of algorithms designed to recognize frontal faces. This paper proposes a novel face identification framework capable of handling the full range of pose variations within ±90° of yaw. The proposed framework first transforms the original pose-invariant face recognition problem into a partial frontal face recognition problem. A robust patch-based face representation scheme is then developed to represent the synthesized partial frontal faces. For each patch, a transformation dictionary is learnt under the proposed multi-task learning scheme. The transformation dictionary transforms the features of different poses into a discriminative subspace. Finally, face matching is performed at patch level rather than at the holistic level. Extensive and systematic experimentation on FERET, CMU-PIE, and Multi-PIE databases shows that the proposed method consistently outperforms single-task-based baselines as well as state-of-the-art methods for the pose problem. We further extend the proposed algorithm for the unconstrained face verification problem and achieve top-level performance on the challenging LFW data set.

Friction ridge skin - Automated Fingerprint Identification System (AFIS)

NARCIS (Netherlands)

Meuwly, Didier

2013-01-01

This contribution describes the development and the forensic use of automated fingerprint identification systems (AFISs). AFISs were initially developed in order to overcome the limitations of the paper-based fingerprint collections, by digitizing the ten-print cards in computerized databases and to

Rotation-invariant fingerprint matching using radon and DCT

Indian Academy of Sciences (India)

Sangita Bharkad

2017-11-20

Nov 20, 2017 ... [6] Bazen A and Gerez S 2003 Fingerprint matching by thin- plate spline modeling of elastic deformations. Pattern. Recogn. 36(8): 1859–1867. [7] Jain A, Hong L and Bolle R 1997 On-line fingerprint veri- fication. IEEE Trans.

Practical Fingerprinting Localization for Indoor Positioning System by Using Beacons

Directory of Open Access Journals (Sweden)

Santosh Subedi

2017-01-01

Full Text Available Recent developments in the fields of smartphones and wireless communication technologies such as beacons, Wi-Fi, and ultra-wideband have made it possible to realize indoor positioning system (IPS with a few meters of accuracy. In this paper, an improvement over traditional fingerprinting localization is proposed by combining it with weighted centroid localization (WCL. The proposed localization method reduces the total number of fingerprint reference points over the localization space, thus minimizing both the time required for reading radio frequency signals and the number of reference points needed during the fingerprinting learning process, which eventually makes the process less time-consuming. The proposed positioning has two major steps of operation. In the first step, we have realized fingerprinting that utilizes lightly populated reference points (RPs and WCL individually. Using the location estimated at the first step, WCL is run again for the final location estimation. The proposed localization technique reduces the number of required fingerprint RPs by more than 40% compared to normal fingerprinting localization method with a similar localization estimation error.

Performance characterization of structured light-based fingerprint scanner

Science.gov (United States)

Hassebrook, Laurence G.; Wang, Minghao; Daley, Raymond C.

2013-05-01

Our group believes that the evolution of fingerprint capture technology is in transition to include 3-D non-contact fingerprint capture. More specifically we believe that systems based on structured light illumination provide the highest level of depth measurement accuracy. However, for these new technologies to be fully accepted by the biometric community, they must be compliant with federal standards of performance. At present these standards do not exist for this new biometric technology. We propose and define a set of test procedures to be used to verify compliance with the Federal Bureau of Investigation's image quality specification for Personal Identity Verification single fingerprint capture devices. The proposed test procedures include: geometric accuracy, lateral resolution based on intensity or depth, gray level uniformity and flattened fingerprint image quality. Several 2-D contact analogies, performance tradeoffs and optimization dilemmas are evaluated and proposed solutions are presented.

Self-match based on polling scheme for passive optical network monitoring

Science.gov (United States)

Zhang, Xuan; Guo, Hao; Jia, Xinhong; Liao, Qinghua

2018-06-01

We propose a self-match based on polling scheme for passive optical network monitoring. Each end-user is equipped with an optical matcher that exploits only the specific length patchcord and two different fiber Bragg gratings with 100% reflectivity. The simple and low-cost scheme can greatly simplify the final recognition processing of the network link status and reduce the sensitivity of the photodetector. We analyze the time-domain relation between reflected pulses and establish the calculation model to evaluate the false alarm rate. The feasibility of the proposed scheme and the validity of the time-domain relation analysis are experimentally demonstrated.

Design and recognition of artificial landmarks for reliable indoor self-localization of mobile robots

Directory of Open Access Journals (Sweden)

Xu Zhong

2017-02-01

Full Text Available This article presents a self-localization scheme for indoor mobile robot navigation based on reliable design and recognition of artificial visual landmarks. Each landmark is patterned with a set of concentric circular rings in black and white, which reliably encodes the landmark’s identity under environmental illumination. A mobile robot in navigation uses an onboard camera to capture landmarks in the environment. The landmarks in an image are detected and identified using a bilayer recognition algorithm: A global recognition process initially extracts candidate landmark regions across the whole image and tries to identify enough landmarks; if necessary, a local recognition process locally enhances those unidentified regions of interest influenced by illumination and incompleteness and reidentifies them. The recognized landmarks are used to estimate the position and orientation of the onboard camera in the environment, based on the geometric relationship between the image and environmental frames. The experiments carried out in a real indoor environment show high robustness of the proposed landmark design and recognition scheme to the illumination condition, which leads to reliable and accurate mobile robot localization.

Development of quality control system for fingerprint comparison processes

Directory of Open Access Journals (Sweden)

Shiquan Liu

2017-01-01

Full Text Available Fingerprint evidence played an important role in investigation, prosecution, and trial process due to the belief of its uniqueness and unchanged characteristics. However, in recent years, the science behind the process of fingerprint comparisons has been questioned. Main research questions have been focusing on the opaqueness within the comparison processes, subjective judgments, lack of universal standards, no error rate expression on final conclusions, and poor scientific fundamental research data. Facing the above-mentioned questions, this paper aims to suggest a quality control system (QCS for fingerprint comparison processes. This QCS is based on the use of software (PiAnoS and its technological features, being able to provide a data management model to increase the transparency and quality of fingerprint comparison processes.

A uniqueness-and-anonymity-preserving remote user authentication scheme for connected health care.

Science.gov (United States)

Chang, Ya-Fen; Yu, Shih-Hui; Shiao, Ding-Rui

2013-04-01

Connected health care provides new opportunities for improving financial and clinical performance. Many connected health care applications such as telecare medicine information system, personally controlled health records system, and patient monitoring have been proposed. Correct and quality care is the goal of connected heath care, and user authentication can ensure the legality of patients. After reviewing authentication schemes for connected health care applications, we find that many of them cannot protect patient privacy such that others can trace users/patients by the transmitted data. And the verification tokens used by these authentication schemes to authenticate users or servers are only password, smart card and RFID tag. Actually, these verification tokens are not unique and easy to copy. On the other hand, biometric characteristics, such as iris, face, voiceprint, fingerprint and so on, are unique, easy to be verified, and hard to be copied. In this paper, a biometrics-based user authentication scheme will be proposed to ensure uniqueness and anonymity at the same time. With the proposed scheme, only the legal user/patient himself/herself can access the remote server, and no one can trace him/her according to transmitted data.

News Schemes for Activity Recognition Systems Using PCA-WSVM, ICA-WSVM, and LDA-WSVM

Directory of Open Access Journals (Sweden)

M’hamed Bilal Abidine

2015-08-01

Full Text Available Feature extraction and classification are two key steps for activity recognition in a smart home environment. In this work, we used three methods for feature extraction: Principal Component Analysis (PCA, Independent Component Analysis (ICA, and Linear Discriminant Analysis (LDA. The new features selected by each method are then used as the inputs for a Weighted Support Vector Machines (WSVM classifier. This classifier is used to handle the problem of imbalanced activity data from the sensor readings. The experiments were implemented on multiple real-world datasets with Conditional Random Fields (CRF, standard Support Vector Machines (SVM, Weighted SVM, and combined methods PCA+WSVM, ICA+WSVM, and LDA+WSVM showed that LDA+WSVM had a higher recognition rate than other methods for activity recognition.

Network-based Fingerprint Authentication System Using a Mobile Device

OpenAIRE

Zhang, Qihu

2016-01-01

Abstract—　Fingerprint-based user authentication is highly effective in networked services such as electronic payment, but conventional authentication solutions have problems in cost, usability and security. To resolve these problems, we propose a touch-less fingerprint authentication solution, in which a mobile device's built-in camera is used to capture fingerprint image, and then it is sent to the server to determine the identity of the user. We designed and implemented a prototype as an a...

Semantically transparent fingerprinting for right protection of digital cinema

Science.gov (United States)

Wu, Xiaolin

2003-06-01

Digital cinema, a new frontier and crown jewel of digital multimedia, has the potential of revolutionizing the science, engineering and business of movie production and distribution. The advantages of digital cinema technology over traditional analog technology are numerous and profound. But without effective and enforceable copyright protection measures, digital cinema can be more susceptible to widespread piracy, which can dampen or even prevent the commercial deployment of digital cinema. In this paper we propose a novel approach of fingerprinting each individual distribution copy of a digital movie for the purpose of tracing pirated copies back to their source. The proposed fingerprinting technique presents a fundamental departure from the traditional digital watermarking/fingerprinting techniques. Its novelty and uniqueness lie in a so-called semantic or subjective transparency property. The fingerprints are created by editing those visual and audio attributes that can be modified with semantic and subjective transparency to the audience. Semantically-transparent fingerprinting or watermarking is the most robust kind among all existing watermarking techniques, because it is content-based not sample-based, and semantically-recoverable not statistically-recoverable.

ULTRAVIOLET RAMAN SPECTRAL SIGNATURE ACQUISITION: UV RAMAN SPECTRAL FINGERPRINTS.

Energy Technology Data Exchange (ETDEWEB)

SEDLACEK,III, A.J.FINFROCK,C.

2002-09-01

As a member of the science-support part of the ITT-lead LISA development program, BNL is tasked with the acquisition of UV Raman spectral fingerprints and associated scattering cross-sections for those chemicals-of-interest to the program's sponsor. In support of this role, the present report contains the first installment of UV Raman spectral fingerprint data on the initial subset of chemicals. Because of the unique nature associated with the acquisition of spectral fingerprints for use in spectral pattern matching algorithms (i.e., CLS, PLS, ANN) great care has been undertaken to maximize the signal-to-noise and to minimize unnecessary spectral subtractions, in an effort to provide the highest quality spectral fingerprints. This report is divided into 4 sections. The first is an Experimental section that outlines how the Raman spectra are performed. This is then followed by a section on Sample Handling. Following this, the spectral fingerprints are presented in the Results section where the data reduction process is outlined. Finally, a Photographs section is included.

A Karnaugh-Map based fingerprint minutiae extraction method

Directory of Open Access Journals (Sweden)

Sunil Kumar Singla

2010-07-01

Full Text Available Fingerprint is one of the most promising method among all the biometric techniques and has been used for thepersonal authentication for a long time because of its wide acceptance and reliability. Features (Minutiae are extracted fromthe fingerprint in question and are compared with the features already stored in the database for authentication. Crossingnumber (CN is the most commonly used minutiae extraction method for fingerprints. In this paper, a new Karnaugh-Mapbased fingerprint minutiae extraction method has been proposed and discussed. In the proposed algorithm the 8 neighborsof a pixel in a 33 window are arranged as 8 bits of a byte and corresponding hexadecimal (hex value is calculated. Thesehex values are simplified using standard Karnaugh-Map (K-map technique to obtain the minimized logical expression.Experiments conducted on the FVC2002/Db1_a database reveals that the developed method is better than the crossingnumber (CN method.

Chemical characterization of fingerprints from adults and children

Energy Technology Data Exchange (ETDEWEB)

Buchanan, M.V.; Asano, K. [Oak Ridge National Lab., TN (United States); Bohanon, A. [Knoxville Police Dept., TN (United States)

1996-12-31

Observation that children`s fingerprints disappear from surfaces more quickly than adults`, initiated a study to characterize the chemical components in fingerprints. Samples were obtained from about 50 individuals ranging in age from 3 to 64 by extracting chemicals from the fingertips using rubbing alcohol. Using combined gas chromatography/mass spectrometry, a wide range of compounds were identified. Samples from children contained higher levels of relatively volatile free fatty acids, while those from adults had higher levels of less volatile long chain esters of fatty acids. These esters are thought to originate from sebaceous glands located on the face and levels of these compounds increase substantially after puberty. Also, other compounds were observed that could be used to develop improved methods for fingerprint detection at a crime scene. Further, observation of specific compounds raises the possibility of being able to identify personal traits (gender, habits, diseases, etc. ) via analysis of components in fingerprints and/or skin.

Defense of fake fingerprint attacks using a swept source laser optical coherence tomography setup

Science.gov (United States)

Meissner, Sven; Breithaupt, Ralph; Koch, Edmund

2013-03-01

The most established technique for the identification at biometric access control systems is the human fingerprint. While every human fingerprint is unique, fingerprints can be faked very easily by using thin layer fakes. Because commercial fingerprint scanners use only a two-dimensional image acquisition of the finger surface, they can only hardly differentiate between real fingerprints and fingerprint fakes applied on thin layer materials. A Swept Source OCT system with an A-line rate of 20 kHz and a lateral and axial resolution of approximately 13 μm, a centre wavelength of 1320 nm and a band width of 120 nm (FWHM) was used to acquire fingerprints and finger tips with overlying fakes. Three-dimensional volume stacks with dimensions of 4.5 mm x 4 mm x 2 mm were acquired. The layering arrangement of the imaged finger tips and faked finger tips was analyzed and subsequently classified into real and faked fingerprints. Additionally, sweat gland ducts were detected and consulted for the classification. The manual classification between real fingerprints and faked fingerprints results in almost 100 % correctness. The outer as well as the internal fingerprint can be recognized in all real human fingers, whereby this was not possible in the image stacks of the faked fingerprints. Furthermore, in all image stacks of real human fingers the sweat gland ducts were detected. The number of sweat gland ducts differs between the test persons. The typical helix shape of the ducts was observed. In contrast, in images of faked fingerprints we observe abnormal layer arrangements and no sweat gland ducts connecting the papillae of the outer fingerprint and the internal fingerprint. We demonstrated that OCT is a very useful tool to enhance the performance of biometric control systems concerning attacks by thin layer fingerprint fakes.

Non-destructive forensic latent fingerprint acquisition with chromatic white light sensors

Science.gov (United States)

Leich, Marcus; Kiltz, Stefan; Dittmann, Jana; Vielhauer, Claus

2011-02-01

Non-destructive latent fingerprint acquisition is an emerging field of research, which, unlike traditional methods, makes latent fingerprints available for additional verification or further analysis like tests for substance abuse or age estimation. In this paper a series of tests is performed to investigate the overall suitability of a high resolution off-the-shelf chromatic white light sensor for the contact-less and non-destructive latent fingerprint acquisition. Our paper focuses on scanning previously determined regions with exemplary acquisition parameter settings. 3D height field and reflection data of five different latent fingerprints on six different types of surfaces (HDD platter, brushed metal, painted car body (metallic and non-metallic finish), blued metal, veneered plywood) are experimentally studied. Pre-processing is performed by removing low-frequency gradients. The quality of the results is assessed subjectively; no automated feature extraction is performed. Additionally, the degradation of the fingerprint during the acquisition period is observed. While the quality of the acquired data is highly dependent on surface structure, the sensor is capable of detecting the fingerprint on all sample surfaces. On blued metal the residual material is detected; however, the ridge line structure dissolves within minutes after fingerprint placement.

Integrating Fingerprint Verification into the Smart Card-Based Healthcare Information System

Directory of Open Access Journals (Sweden)

Jin-Won Park

2009-01-01

Full Text Available As VLSI technology has been improved, a smart card employing 32-bit processors has been released, and more personal information such as medical, financial data can be stored in the card. Thus, it becomes important to protect personal information stored in the card. Verification of the card holder's identity using a fingerprint has advantages over the present practices of Personal Identification Numbers (PINs and passwords. However, the computational workload of fingerprint verification is much heavier than that of the typical PIN-based solution. In this paper, we consider three strategies to implement fingerprint verification in a smart card environment and how to distribute the modules of fingerprint verification between the smart card and the card reader. We first evaluate the number of instructions of each step of a typical fingerprint verification algorithm, and estimate the execution time of several cryptographic algorithms to guarantee the security/privacy of the fingerprint data transmitted in the smart card with the client-server environment. Based on the evaluation results, we analyze each scenario with respect to the security level and the real-time execution requirements in order to implement fingerprint verification in the smart card with the client-server environment.

Integrating Fingerprint Verification into the Smart Card-Based Healthcare Information System

Science.gov (United States)

Moon, Daesung; Chung, Yongwha; Pan, Sung Bum; Park, Jin-Won

2009-12-01

As VLSI technology has been improved, a smart card employing 32-bit processors has been released, and more personal information such as medical, financial data can be stored in the card. Thus, it becomes important to protect personal information stored in the card. Verification of the card holder's identity using a fingerprint has advantages over the present practices of Personal Identification Numbers (PINs) and passwords. However, the computational workload of fingerprint verification is much heavier than that of the typical PIN-based solution. In this paper, we consider three strategies to implement fingerprint verification in a smart card environment and how to distribute the modules of fingerprint verification between the smart card and the card reader. We first evaluate the number of instructions of each step of a typical fingerprint verification algorithm, and estimate the execution time of several cryptographic algorithms to guarantee the security/privacy of the fingerprint data transmitted in the smart card with the client-server environment. Based on the evaluation results, we analyze each scenario with respect to the security level and the real-time execution requirements in order to implement fingerprint verification in the smart card with the client-server environment.

Human matching performance of genuine crime scene latent fingerprints.

Science.gov (United States)

Thompson, Matthew B; Tangen, Jason M; McCarthy, Duncan J

2014-02-01

There has been very little research into the nature and development of fingerprint matching expertise. Here we present the results of an experiment testing the claimed matching expertise of fingerprint examiners. Expert (n = 37), intermediate trainee (n = 8), new trainee (n = 9), and novice (n = 37) participants performed a fingerprint discrimination task involving genuine crime scene latent fingerprints, their matches, and highly similar distractors, in a signal detection paradigm. Results show that qualified, court-practicing fingerprint experts were exceedingly accurate compared with novices. Experts showed a conservative response bias, tending to err on the side of caution by making more errors of the sort that could allow a guilty person to escape detection than errors of the sort that could falsely incriminate an innocent person. The superior performance of experts was not simply a function of their ability to match prints, per se, but a result of their ability to identify the highly similar, but nonmatching fingerprints as such. Comparing these results with previous experiments, experts were even more conservative in their decision making when dealing with these genuine crime scene prints than when dealing with simulated crime scene prints, and this conservatism made them relatively less accurate overall. Intermediate trainees-despite their lack of qualification and average 3.5 years experience-performed about as accurately as qualified experts who had an average 17.5 years experience. New trainees-despite their 5-week, full-time training course or their 6 months experience-were not any better than novices at discriminating matching and similar nonmatching prints, they were just more conservative. Further research is required to determine the precise nature of fingerprint matching expertise and the factors that influence performance. The findings of this representative, lab-based experiment may have implications for the way fingerprint examiners testify in

Comparing Categorical and Probabilistic Fingerprint Evidence.

Science.gov (United States)

Garrett, Brandon; Mitchell, Gregory; Scurich, Nicholas

2018-04-23

Fingerprint examiners traditionally express conclusions in categorical terms, opining that impressions do or do not originate from the same source. Recently, probabilistic conclusions have been proposed, with examiners estimating the probability of a match between recovered and known prints. This study presented a nationally representative sample of jury-eligible adults with a hypothetical robbery case in which an examiner opined on the likelihood that a defendant's fingerprints matched latent fingerprints in categorical or probabilistic terms. We studied model language developed by the U.S. Defense Forensic Science Center to summarize results of statistical analysis of the similarity between prints. Participant ratings of the likelihood the defendant left prints at the crime scene and committed the crime were similar when exposed to categorical and strong probabilistic match evidence. Participants reduced these likelihoods when exposed to the weaker probabilistic evidence, but did not otherwise discriminate among the prints assigned different match probabilities. © 2018 American Academy of Forensic Sciences.

Optical Methods in Fingerprint Imaging for Medical and Personality Applications.

Science.gov (United States)

Wang, Chia-Nan; Wang, Jing-Wein; Lin, Ming-Hsun; Chang, Yao-Lang; Kuo, Chia-Ming

2017-10-23

Over the years, analysis and induction of personality traits has been a topic for individual subjective conjecture or speculation, rather than a focus of inductive scientific analysis. This study proposes a novel framework for analysis and induction of personality traits. First, 14 personality constructs based on the "Big Five" personality factors were developed. Next, a new fingerprint image algorithm was used for classification, and the fingerprints were classified into eight types. The relationship between personality traits and fingerprint type was derived from the results of the questionnaire survey. After comparison of pre-test and post-test results, this study determined the induction ability of personality traits from fingerprint type. Experimental results showed that the left/right thumbprint type of a majority of subjects was left loop/right loop and that the personalities of individuals with this fingerprint type were moderate with no significant differences in the 14 personality constructs.

Enhancement of plant metabolite fingerprinting by machine learning.

Science.gov (United States)

Scott, Ian M; Vermeer, Cornelia P; Liakata, Maria; Corol, Delia I; Ward, Jane L; Lin, Wanchang; Johnson, Helen E; Whitehead, Lynne; Kular, Baldeep; Baker, John M; Walsh, Sean; Dave, Anuja; Larson, Tony R; Graham, Ian A; Wang, Trevor L; King, Ross D; Draper, John; Beale, Michael H

2010-08-01

Metabolite fingerprinting of Arabidopsis (Arabidopsis thaliana) mutants with known or predicted metabolic lesions was performed by (1)H-nuclear magnetic resonance, Fourier transform infrared, and flow injection electrospray-mass spectrometry. Fingerprinting enabled processing of five times more plants than conventional chromatographic profiling and was competitive for discriminating mutants, other than those affected in only low-abundance metabolites. Despite their rapidity and complexity, fingerprints yielded metabolomic insights (e.g. that effects of single lesions were usually not confined to individual pathways). Among fingerprint techniques, (1)H-nuclear magnetic resonance discriminated the most mutant phenotypes from the wild type and Fourier transform infrared discriminated the fewest. To maximize information from fingerprints, data analysis was crucial. One-third of distinctive phenotypes might have been overlooked had data models been confined to principal component analysis score plots. Among several methods tested, machine learning (ML) algorithms, namely support vector machine or random forest (RF) classifiers, were unsurpassed for phenotype discrimination. Support vector machines were often the best performing classifiers, but RFs yielded some particularly informative measures. First, RFs estimated margins between mutant phenotypes, whose relations could then be visualized by Sammon mapping or hierarchical clustering. Second, RFs provided importance scores for the features within fingerprints that discriminated mutants. These scores correlated with analysis of variance F values (as did Kruskal-Wallis tests, true- and false-positive measures, mutual information, and the Relief feature selection algorithm). ML classifiers, as models trained on one data set to predict another, were ideal for focused metabolomic queries, such as the distinctiveness and consistency of mutant phenotypes. Accessible software for use of ML in plant physiology is highlighted.

Fingerprint-Inspired Flexible Tactile Sensor for Accurately Discerning Surface Texture.

Science.gov (United States)

Cao, Yudong; Li, Tie; Gu, Yang; Luo, Hui; Wang, Shuqi; Zhang, Ting

2018-04-01

Inspired by the epidermal-dermal and outer microstructures of the human fingerprint, a novel flexible sensor device is designed to improve haptic perception and surface texture recognition, which is consisted of single-walled carbon nanotubes, polyethylene, and polydimethylsiloxane with interlocked and outer micropyramid arrays. The sensor shows high pressure sensitivity (-3.26 kPa -1 in the pressure range of 0-300 Pa), and it can detect the shear force changes induced by the dynamic interaction between the outer micropyramid structure on the sensor and the tested material surface, and the minimum dimension of the microstripe that can be discerned is as low as 15 µm × 15 µm (interval × width). To demonstrate the texture discrimination capability, the sensors are tested for accurately discerning various surface textures, such as the textures of different fabrics, Braille characters, the inverted pyramid patterns, which will have great potential in robot skins and haptic perception, etc. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Impedance spectral fingerprint of E. coli cells on interdigitated electrodes: A new approach for label free and selective detection

Directory of Open Access Journals (Sweden)

Maria Mallén-Alberdi

2016-03-01

Full Text Available Impedance-based biosensors for bacterial detection offer a rapid and cost-effective alternative to conventional techniques that are time-consuming and require specialized equipment and trained users. In this work, a new bacteria detection scheme is presented based on impedance measurements with antibody-modified polysilicon interdigitated electrodes (3 μm pitch, IDEs. The detection approach was carried out taking advantage of the E. coli structure which, in electrical terms, is constituted by two insulating cell membranes that separate a conductive cytoplasmatic medium and a more conductive periplasm. Impedance detection of bacteria is usually analyzed using electrical equivalent circuit models that show limitations for the interpretation of such complex cell structure. Here, a differential impedance spectrum representation is used to study the unique fingerprint that arises when bacteria attach to the surface of IDEs. That fingerprint shows the dual electrical behavior, insulating and conductive, at different frequency ranges. In parallel, finite-element simulations of this system using a three-shell bacteria model are performed to explain such phenomena. Overall, a new approach to detect bacteria is proposed that also enables to differentiate viable bacteria from other components non-specifically attached to the IDE surface by just detecting their spectral fingerprints. Keywords: Impedance spectroscopy, Bacterial detection, Interdigitated electrodes, Label-free detection, Immuno-detection, E. coli O157:H7

Multiple chromatographic fingerprinting and its application to the quality control of herbal medicines

International Nuclear Information System (INIS)

Fan Xiaohui; Cheng Yiyu; Ye Zhengliang; Lin Ruichao; Qian Zhongzhi

2006-01-01

Recently, chromatographic fingerprinting has become one of the most powerful approaches to quality control of herbal medicines. However, the performance of reported chromatographic fingerprinting constructed by single chromatogram sometimes turns out to be inadequate for complex herbal medicines, such as multi-herb botanical drug products. In this study, multiple chromatographic fingerprinting, which consists of more than one chromatographic fingerprint and represents the whole characteristics of chemical constitutions of the complex medicine, is proposed as a potential strategy in this complicated case. As a typical example, a binary chromatographic fingerprinting of 'Danshen Dropping Pill' (DSDP), the best-sold traditional Chinese medicine in China, was developed. First, two HPLC fingerprints that, respectively, represent chemical characteristics of depsides and saponins of DSDP were developed, which were used to construct binary chromatographic fingerprints of DSDP. Moreover, the authentication and validation of the binary fingerprints were performed. Then, a data-level information fusion method was employed to capture the chemical information encoded in two chromatographic fingerprints. Based on the fusion results, the lot-to-lot consistency and frauds can be determined either using similarity measure or by chemometrics approach. The application of binary chromatographic fingerprinting to consistency assessment and frauds detection of DSDP clearly demonstrated that the proposed method was a powerful approach to quality control of complex herbal medicines

Comprehensive Chemical Fingerprinting of High-Quality Cocoa at Early Stages of Processing: Effectiveness of Combined Untargeted and Targeted Approaches for Classification and Discrimination.

Science.gov (United States)

Magagna, Federico; Guglielmetti, Alessandro; Liberto, Erica; Reichenbach, Stephen E; Allegrucci, Elena; Gobino, Guido; Bicchi, Carlo; Cordero, Chiara

2017-08-02

This study investigates chemical information of volatile fractions of high-quality cocoa (Theobroma cacao L. Malvaceae) from different origins (Mexico, Ecuador, Venezuela, Columbia, Java, Trinidad, and Sao Tomè) produced for fine chocolate. This study explores the evolution of the entire pattern of volatiles in relation to cocoa processing (raw, roasted, steamed, and ground beans). Advanced chemical fingerprinting (e.g., combined untargeted and targeted fingerprinting) with comprehensive two-dimensional gas chromatography coupled with mass spectrometry allows advanced pattern recognition for classification, discrimination, and sensory-quality characterization. The entire data set is analyzed for 595 reliable two-dimensional peak regions, including 130 known analytes and 13 potent odorants. Multivariate analysis with unsupervised exploration (principal component analysis) and simple supervised discrimination methods (Fisher ratios and linear regression trees) reveal informative patterns of similarities and differences and identify characteristic compounds related to sample origin and manufacturing step.

Diversity of DNA fingerprints of Mycobacterium tuberculosis isolates in the United States.

Science.gov (United States)

Yang, Z; Barnes, P F; Chaves, F; Eisenach, K D; Weis, S E; Bates, J H; Cave, M D

1998-04-01

To investigate the diversity of IS6110 fingerprints of Mycobacterium tuberculosis isolates in the United States and to determine if matching IS6110 fingerprints represent recent interstate tuberculosis transmission, we performed restriction fragment length polymorphism analysis of M. tuberculosis isolates from 1,326 patients in three geographically separated states. Seven hundred ninety-five different IS6110 fingerprint patterns were generated, and pattern diversity was similar in each state. Ninety-six percent of the fingerprint patterns were observed in only one state, demonstrating that most IS6110 fingerprint patterns are confined to a single geographic location. Of the IS6110 fingerprint patterns that were shared by isolates from more than one state, most isolates with 1 to 5 IS6110 copies were separable by pTBN12 fingerprinting whereas those with > 15 copies were not. One high-copy-number M. tuberculosis strain had identical IS6110 and pTBN12 fingerprints and included 57 isolates from three states. Epidemiological data demonstrated significant recent transmission of tuberculosis within each city but not among the states. This suggests that identical fingerprints of isolates from geographically separate locations most likely reflect interstate tuberculosis transmission in the past, with subsequent intrastate spread of disease. Further evaluation of M. tuberculosis strains that cause outbreaks in different geographic locations will provide insight into the epidemiological and bacteriological factors that facilitate the spread of tuberculosis.

Improved Hip-Based Individual Recognition Using Wearable Motion Recording Sensor

Science.gov (United States)

Gafurov, Davrondzhon; Bours, Patrick

In todays society the demand for reliable verification of a user identity is increasing. Although biometric technologies based on fingerprint or iris can provide accurate and reliable recognition performance, they are inconvenient for periodic or frequent re-verification. In this paper we propose a hip-based user recognition method which can be suitable for implicit and periodic re-verification of the identity. In our approach we use a wearable accelerometer sensor attached to the hip of the person, and then the measured hip motion signal is analysed for identity verification purposes. The main analyses steps consists of detecting gait cycles in the signal and matching two sets of detected gait cycles. Evaluating the approach on a hip data set consisting of 400 gait sequences (samples) from 100 subjects, we obtained equal error rate (EER) of 7.5% and identification rate at rank 1 was 81.4%. These numbers are improvements by 37.5% and 11.2% respectively of the previous study using the same data set.

Fast Fingerprint Database Maintenance for Indoor Positioning Based on UGV SLAM

Directory of Open Access Journals (Sweden)

Jian Tang

2015-03-01

Full Text Available Indoor positioning technology has become more and more important in the last two decades. Utilizing Received Signal Strength Indicator (RSSI fingerprints of Signals of OPportunity (SOP is a promising alternative navigation solution. However, as the RSSIs vary during operation due to their physical nature and are easily affected by the environmental change, one challenge of the indoor fingerprinting method is maintaining the RSSI fingerprint database in a timely and effective manner. In this paper, a solution for rapidly updating the fingerprint database is presented, based on a self-developed Unmanned Ground Vehicles (UGV platform NAVIS. Several SOP sensors were installed on NAVIS for collecting indoor fingerprint information, including a digital compass collecting magnetic field intensity, a light sensor collecting light intensity, and a smartphone which collects the access point number and RSSIs of the pre-installed WiFi network. The NAVIS platform generates a map of the indoor environment and collects the SOPs during processing of the mapping, and then the SOP fingerprint database is interpolated and updated in real time. Field tests were carried out to evaluate the effectiveness and efficiency of the proposed method. The results showed that the fingerprint databases can be quickly created and updated with a higher sampling frequency (5Hz and denser reference points compared with traditional methods, and the indoor map can be generated without prior information. Moreover, environmental changes could also be detected quickly for fingerprint indoor positioning.

Optical Methods in Fingerprint Imaging for Medical and Personality Applications

Directory of Open Access Journals (Sweden)

Chia-Nan Wang

2017-10-01

Full Text Available Over the years, analysis and induction of personality traits has been a topic for individual subjective conjecture or speculation, rather than a focus of inductive scientific analysis. This study proposes a novel framework for analysis and induction of personality traits. First, 14 personality constructs based on the “Big Five” personality factors were developed. Next, a new fingerprint image algorithm was used for classification, and the fingerprints were classified into eight types. The relationship between personality traits and fingerprint type was derived from the results of the questionnaire survey. After comparison of pre-test and post-test results, this study determined the induction ability of personality traits from fingerprint type. Experimental results showed that the left/right thumbprint type of a majority of subjects was left loop/right loop and that the personalities of individuals with this fingerprint type were moderate with no significant differences in the 14 personality constructs.

[HPLC characteristic fingerprints of sedi linearis herba and sedi herba].

Science.gov (United States)

Lu, Lan-Qing; Mei, Qing; Wan, Ding-Rong; Yang, Xin-Zhou; Qiao, Shu; Zhao, Yu-Dan

2014-04-01

To study HPLC characteristic fingerprint of Sedum lineare from different harvest periods, and to compare with its related species Sedum sarmentosum. The HPLC fingerprints of Sedum lineare from different collecting periods were established and compared with Sedum sarmentosum by the same detection method. Hyperin, isoquercitrin and astragaloside were identified from the HPLC fingerprint of Sedum lineare. The fingerprint of Sedum lineare growing in the same area but different environment were basically identical; while there were remarkable differences of Sedum lineare growing in the same place but from different harvest periods, with the area of most common peaks changing from little to great, and slightly different peak number. The HPLC fingerprint of the two Sedum species had four common peaks, but could be distinguished from each other. The optimal harvest period of these two species should be full-bloom stage. The established method can provide reference for identification and quality analysis of Sedum lineare.

Identification and Quality Assessment of Chrysanthemum Buds by CE Fingerprinting

Directory of Open Access Journals (Sweden)

Xiaoping Xing

2015-01-01

Full Text Available A simple and efficient fingerprinting method for chrysanthemum buds was developed with the aim of establishing a quality control protocol based on biochemical makeup. Chrysanthemum bud samples were successively extracted by water and alcohol. The fingerprints of the chrysanthemum buds samples were obtained using capillary electrophoresis and electrochemical detection (CE-ED employing copper and carbon working electrodes to capture all of the chemical information. 10 batches of chrysanthemum buds were collected from different regions and various factories to establish the baseline fingerprint. The experimental data of 10 batches electropherogram buds by CE were analyzed by correlation coefficient and the included angle cosine methods. A standard chrysanthemum bud fingerprint including 24 common peaks was established, 12 from each electrode, which was successfully applied to identify and distinguish between chrysanthemum buds from 2 other chrysanthemum species. These results demonstrate that fingerprint analysis can be used as an important criterion for chrysanthemum buds quality control.

Optical Methods in Fingerprint Imaging for Medical and Personality Applications

Science.gov (United States)

Wang, Jing-Wein; Lin, Ming-Hsun; Chang, Yao-Lang; Kuo, Chia-Ming

2017-01-01

Over the years, analysis and induction of personality traits has been a topic for individual subjective conjecture or speculation, rather than a focus of inductive scientific analysis. This study proposes a novel framework for analysis and induction of personality traits. First, 14 personality constructs based on the “Big Five” personality factors were developed. Next, a new fingerprint image algorithm was used for classification, and the fingerprints were classified into eight types. The relationship between personality traits and fingerprint type was derived from the results of the questionnaire survey. After comparison of pre-test and post-test results, this study determined the induction ability of personality traits from fingerprint type. Experimental results showed that the left/right thumbprint type of a majority of subjects was left loop/right loop and that the personalities of individuals with this fingerprint type were moderate with no significant differences in the 14 personality constructs. PMID:29065556

Canonical, stable, general mapping using context schemes.

Science.gov (United States)

Novak, Adam M; Rosen, Yohei; Haussler, David; Paten, Benedict

2015-11-15

Sequence mapping is the cornerstone of modern genomics. However, most existing sequence mapping algorithms are insufficiently general. We introduce context schemes: a method that allows the unambiguous recognition of a reference base in a query sequence by testing the query for substrings from an algorithmically defined set. Context schemes only map when there is a unique best mapping, and define this criterion uniformly for all reference bases. Mappings under context schemes can also be made stable, so that extension of the query string (e.g. by increasing read length) will not alter the mapping of previously mapped positions. Context schemes are general in several senses. They natively support the detection of arbitrary complex, novel rearrangements relative to the reference. They can scale over orders of magnitude in query sequence length. Finally, they are trivially extensible to more complex reference structures, such as graphs, that incorporate additional variation. We demonstrate empirically the existence of high-performance context schemes, and present efficient context scheme mapping algorithms. The software test framework created for this study is available from https://registry.hub.docker.com/u/adamnovak/sequence-graphs/. anovak@soe.ucsc.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

A tree based method for the rapid screening of chemical fingerprints

DEFF Research Database (Denmark)

Kristensen, Thomas Greve; Nielsen, Jesper; Pedersen, Christian Nørgaard Storm

2009-01-01

The fingerprint of a molecule is a bitstring based on its structure, constructed such that structurally similar molecules will have similar fingerprints. Molecular fingerprints can be used in an initial phase for identifying novel drug candidates by screening large databases for molecules......: the kD grid and the Multibit tree. The kD grid is based on splitting the fingerprints into k shorter bitstrings and utilising these to compute bounds on the similarity of the complete bitstrings. The Multibit tree uses hierarchical clustering and similarity within each cluster to compute similar bounds...

Aspects of physicochemical methods for the detection of latent fingerprints

International Nuclear Information System (INIS)

Knowles, A.M.

1978-01-01

This paper reviews physicochemical methods of detecting latent finger-prints on a wide range of materials commonly found at the scene of a crime, with particular emphasis placed on the newer autoradiographic techniques. This is set against a description of studies on the fundamental nature of the latent fingerprint and its host substrate, with a brief review of the history of reagents used in latent fingerprint examination. (author)

Multiple chromatographic fingerprinting and its application to the quality control of herbal medicines

Energy Technology Data Exchange (ETDEWEB)

Fan Xiaohui [Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310027 (China); Cheng Yiyu [Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310027 (China)]. E-mail: chengyy@zju.edu.cn; Ye Zhengliang [Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310027 (China); Lin Ruichao [National Institute for the Control of Pharmaceutical and Biological Products, Beijing 100050 (China); Qian Zhongzhi [Committee of Chinese Pharmacopoeia, Beijing 100061 (China)

2006-01-12

Recently, chromatographic fingerprinting has become one of the most powerful approaches to quality control of herbal medicines. However, the performance of reported chromatographic fingerprinting constructed by single chromatogram sometimes turns out to be inadequate for complex herbal medicines, such as multi-herb botanical drug products. In this study, multiple chromatographic fingerprinting, which consists of more than one chromatographic fingerprint and represents the whole characteristics of chemical constitutions of the complex medicine, is proposed as a potential strategy in this complicated case. As a typical example, a binary chromatographic fingerprinting of 'Danshen Dropping Pill' (DSDP), the best-sold traditional Chinese medicine in China, was developed. First, two HPLC fingerprints that, respectively, represent chemical characteristics of depsides and saponins of DSDP were developed, which were used to construct binary chromatographic fingerprints of DSDP. Moreover, the authentication and validation of the binary fingerprints were performed. Then, a data-level information fusion method was employed to capture the chemical information encoded in two chromatographic fingerprints. Based on the fusion results, the lot-to-lot consistency and frauds can be determined either using similarity measure or by chemometrics approach. The application of binary chromatographic fingerprinting to consistency assessment and frauds detection of DSDP clearly demonstrated that the proposed method was a powerful approach to quality control of complex herbal medicines.

Improving Speaker Recognition by Biometric Voice Deconstruction

Science.gov (United States)

Mazaira-Fernandez, Luis Miguel; Álvarez-Marquina, Agustín; Gómez-Vilda, Pedro

2015-01-01

Person identification, especially in critical environments, has always been a subject of great interest. However, it has gained a new dimension in a world threatened by a new kind of terrorism that uses social networks (e.g., YouTube) to broadcast its message. In this new scenario, classical identification methods (such as fingerprints or face recognition) have been forcedly replaced by alternative biometric characteristics such as voice, as sometimes this is the only feature available. The present study benefits from the advances achieved during last years in understanding and modeling voice production. The paper hypothesizes that a gender-dependent characterization of speakers combined with the use of a set of features derived from the components, resulting from the deconstruction of the voice into its glottal source and vocal tract estimates, will enhance recognition rates when compared to classical approaches. A general description about the main hypothesis and the methodology followed to extract the gender-dependent extended biometric parameters is given. Experimental validation is carried out both on a highly controlled acoustic condition database, and on a mobile phone network recorded under non-controlled acoustic conditions. PMID:26442245

Analysis of cellular and extracellular DNA in fingerprints

Energy Technology Data Exchange (ETDEWEB)

Button, Julie M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2014-09-09

It has been previously shown that DNA can be recovered from latent fingerprints left on various surfaces [R. A. H. van Oorschot and M. K. Jones, Nature 387, 767 (1997)]. However, the source of the DNA, extracellular versus cellular origin, is difficult to determine. If the DNA is cellular, it is believed to belong to skin cells while extracellular DNA is believed to originate from body fluids such as sweat [D. J. Daly et. al, Forensic Sci. Int. Genet. 6, 41-46 (2012); V. V. Vlassov et. al, BioEssays 29, 654-667 (2007)]. The origin of the DNA in fingerprints has implications for processing and interpretation of forensic evidence. The determination of the origin of DNA in fingerprints is further complicated by the fact that the DNA in fingerprints tends to be at a very low quantity [R. A. H. van Oorschot and M. K. Jones, Nature 387, 767 (1997)]. This study examined fingerprints from five volunteers left on sterilized glass slides and plastic pens. Three fingerprints were left on each glass slide (thumb, index, and middle fingers) while the pens were held as if one was writing with them. The DNA was collected from the objects using the wet swabbing technique (TE buffer). Following collection, the cellular and extracellular components of each sample were separated using centrifugation and an acoustofluidics system. Centrifugation is still the primary separation technique utilized in forensics laboratories, while acoustic focusing uses sound waves to focus large particles (cells) into low pressure nodes, separating them from the rest of the sample matrix. After separation, all samples were quantified using real-time quantitative PCR (qPCR). The overall trend is that there is more DNA in the extracellular fractions than cellular fractions for both centrifugation and acoustofluidic processing. Additionally, more DNA was generally collected from the pen samples than the samples left on glass slides.

Fast probabilistic file fingerprinting for big data.

Science.gov (United States)

Tretyakov, Konstantin; Laur, Sven; Smant, Geert; Vilo, Jaak; Prins, Pjotr

2013-01-01

Biological data acquisition is raising new challenges, both in data analysis and handling. Not only is it proving hard to analyze the data at the rate it is generated today, but simply reading and transferring data files can be prohibitively slow due to their size. This primarily concerns logistics within and between data centers, but is also important for workstation users in the analysis phase. Common usage patterns, such as comparing and transferring files, are proving computationally expensive and are tying down shared resources. We present an efficient method for calculating file uniqueness for large scientific data files, that takes less computational effort than existing techniques. This method, called Probabilistic Fast File Fingerprinting (PFFF), exploits the variation present in biological data and computes file fingerprints by sampling randomly from the file instead of reading it in full. Consequently, it has a flat performance characteristic, correlated with data variation rather than file size. We demonstrate that probabilistic fingerprinting can be as reliable as existing hashing techniques, with provably negligible risk of collisions. We measure the performance of the algorithm on a number of data storage and access technologies, identifying its strengths as well as limitations. Probabilistic fingerprinting may significantly reduce the use of computational resources when comparing very large files. Utilisation of probabilistic fingerprinting techniques can increase the speed of common file-related workflows, both in the data center and for workbench analysis. The implementation of the algorithm is available as an open-source tool named pfff, as a command-line tool as well as a C library. The tool can be downloaded from http://biit.cs.ut.ee/pfff.

[HPTLC fingerprint analysis of andrographolides from Andrographis paniculata].

Science.gov (United States)

Shao, Yan-Hua; Wang, Jian-Gang; Lai, Xiao-Ping; Wu, Xiang-Wei; Ding, Ping

2014-02-01

To establish the high-performance thin layer chromatography (HPTLC) fingerprint of andrographolides from Andrographis paniculata, and to valuate the fingerprint similarity of samples from different habitats, markets, used parts and so on. Chromatographic conditions were as follows: stationary phase: precoated HPTLC GF254 silica-gel plate (20 cm x 10 cm); developing solvent system: chloroform-toluene-methanol (80:10:15); Relative humidity: 42%; Color development reagent: 5% H2SO4 ethanolic solution, heating at 105 degrees C and observing the fluorescent chromatogram in a UV cabinet at 366 nm. The common patterns of HPTLC fingerprint were obtained through CHROMAP 1.5 solution software. The HPTLC fingerprint of andrographolides was consisted of 9 characteristic peaks (fluorescent bands) including andrographolide, neoandrographolide and dehydroandrographolide which were chemical reference substances. The investigation and analysis of 51 batches of Andrographis paniculata showed that there were remarkable differences among different samples, so was the content of andrographolide and total lactones. This method is simple and rapid, which can serve as an effective identification and quality assessment method for Andrographis paniculata.

Partial Fingerprint Image Enhancement using Region Division Technique and Morphological Transform

International Nuclear Information System (INIS)

Ahmad, A.; Arshad, I.; Raja, G.

2015-01-01

Fingerprints are the most renowned biometric trait for identification and verification. The quality of fingerprint image plays a vital role in feature extraction and matching. Existing algorithms work well for good quality fingerprint images and fail for partial fingerprint images as they are obtained from excessively dry fingers or affected by disease resulting in broken ridges. We propose an algorithm to enhance partial fingerprint images using morphological operatins with region division technique. The proposed method divides low quality image into six regions from top to bottom. Morphological operations choose an appropriate Structuring Element (SE) that joins broken ridges and thus enhance the image for further processing. The proposed method uses SE line with suitable angle theta and radius r in each region based on the orientation of the ridges. The algorithm is applied to 14 low quality fingerprint images from FVC-2002 database. Experimental results show that percentage accuracy has been improved using the proposed algorithm. The manual markup has been reduced and accuracy of 76.16% with Equal Error Rate (EER) of 3.16% is achieved. (author)

Novel fingerprint re-alignment solution that uses the TFCP as a reference

CSIR Research Space (South Africa)

Msiza, IS

2011-08-01

Full Text Available , independent, and efficient for all types of fingerprints. It, in particular, is useful when dealing with the type of fingerprints that belong to the Plain Arch (PA) fingerprint class. The credibility of this proposed solution is interrogated through its...

Uniform design based SVM model selection for face recognition

Science.gov (United States)

Li, Weihong; Liu, Lijuan; Gong, Weiguo

2010-02-01

Support vector machine (SVM) has been proved to be a powerful tool for face recognition. The generalization capacity of SVM depends on the model with optimal hyperparameters. The computational cost of SVM model selection results in application difficulty in face recognition. In order to overcome the shortcoming, we utilize the advantage of uniform design--space filling designs and uniformly scattering theory to seek for optimal SVM hyperparameters. Then we propose a face recognition scheme based on SVM with optimal model which obtained by replacing the grid and gradient-based method with uniform design. The experimental results on Yale and PIE face databases show that the proposed method significantly improves the efficiency of SVM model selection.

Piezoelectric micromachined ultrasonic transducers for fingerprint sensing

Science.gov (United States)

Lu, Yipeng

Fingerprint identification is the most prevalent biometric technology due to its uniqueness, universality and convenience. Over the past two decades, a variety of physical mechanisms have been exploited to capture an electronic image of a human fingerprint. Among these, capacitive fingerprint sensors are the ones most widely used in consumer electronics because they are fabricated using conventional complementary metal oxide semiconductor (CMOS) integrated circuit technology. However, capacitive fingerprint sensors are extremely sensitive to finger contamination and moisture. This thesis will introduce an ultrasonic fingerprint sensor using a PMUT array, which offers a potential solution to this problem. In addition, it has the potential to increase security, as it allows images to be collected at various depths beneath the epidermis, providing images of the sub-surface dermis layer and blood vessels. Firstly, PMUT sensitivity is maximized by optimizing the layer stack and electrode design, and the coupling coefficient is doubled via series transduction. Moreover, a broadband PMUT with 97% fractional bandwidth is achieved by utilizing a thinner structure excited at two adjacent mechanical vibration modes with overlapping bandwidth. In addition, we proposed waveguide PMUTs, which function to direct acoustic waves, confine acoustic energy, and provide mechanical protection for the PMUT array. Furthermore, PMUT arrays were fabricated with different processes to form the membrane, including front-side etching with a patterned sacrificial layer, front-side etching with additional anchor, cavity SOI wafers and eutectic bonding. Additionally, eutectic bonding allows the PMUT to be integrated with CMOS circuits. PMUTs were characterized in the mechanical, electrical and acoustic domains. Using transmit beamforming, a narrow acoustic beam was achieved, and high-resolution (sub-100 microm) and short-range (~1 mm) pulse-echo ultrasonic imaging was demonstrated using a steel

Real time biometric surveillance with gait recognition

Science.gov (United States)

Mohapatra, Subasish; Swain, Anisha; Das, Manaswini; Mohanty, Subhadarshini

2018-04-01

Bio metric surveillance has become indispensable for every system in the recent years. The contribution of bio metric authentication, identification, and screening purposes are widely used in various domains for preventing unauthorized access. A large amount of data needs to be updated, segregated and safeguarded from malicious software and misuse. Bio metrics is the intrinsic characteristics of each individual. Recently fingerprints, iris, passwords, unique keys, and cards are commonly used for authentication purposes. These methods have various issues related to security and confidentiality. These systems are not yet automated to provide the safety and security. The gait recognition system is the alternative for overcoming the drawbacks of the recent bio metric based authentication systems. Gait recognition is newer as it hasn't been implemented in the real-world scenario so far. This is an un-intrusive system that requires no knowledge or co-operation of the subject. Gait is a unique behavioral characteristic of every human being which is hard to imitate. The walking style of an individual teamed with the orientation of joints in the skeletal structure and inclinations between them imparts the unique characteristic. A person can alter one's own external appearance but not skeletal structure. These are real-time, automatic systems that can even process low-resolution images and video frames. In this paper, we have proposed a gait recognition system and compared the performance with conventional bio metric identification systems.

A General Polygon-based Deformable Model for Object Recognition

DEFF Research Database (Denmark)

Jensen, Rune Fisker; Carstensen, Jens Michael

1999-01-01

We propose a general scheme for object localization and recognition based on a deformable model. The model combines shape and image properties by warping a arbitrary prototype intensity template according to the deformation in shape. The shape deformations are constrained by a probabilistic distr...

Authentications of Myanmar National Registration Card

Directory of Open Access Journals (Sweden)

Myint Myint Sein

2013-04-01

Full Text Available The automatic identification system of Myanmar national registration card (NRC holder is presented in this paper. The proposed system can be handled the identification by the extracted low quality face image and fingerprint image from Myanmar NRC. Both of the facial recognition and fingerprint recognition system are developed for Myanmar citizenship confirmation. Age invariant face recognition algorithm is performed based on combination of DiaPCA (Diagonal principal Component Analysis and KNN (Kth nearest neighbor classifier approaches. An algorithm of the fingerprint recognition is proposed for recognition of the poor quality fingerprint image with fabric background.  Several experiments have been done for confirming the effectiveness of the proposed approach.

Ridge Width Correlations between Inked Prints and Powdered Latent Fingerprints.

Science.gov (United States)

De Alcaraz-Fossoul, Josep; Barrot-Feixat, Carme; Zapico, Sara C; Mancenido, Michelle; Broatch, Jennifer; Roberts, Katherine A; Carreras-Marin, Clara; Tasker, Jack

2017-10-03

A methodology to estimate the time of latent fingerprint deposition would be of great value to law enforcement and courts. It has been observed that ridge topography changes as latent prints age, including the widths of ridges that could be measured as a function of time. Crime suspects are commonly identified using fingerprint databases that contain reference inked tenprints (flat and rolled impressions). These can be of interest in aging studies as they provide baseline information relating to the original (nonaged) ridges' widths. In practice, the age of latent fingerprints could be estimated following a comparison process between the evidentiary aged print and the corresponding reference inked print. The present article explores possible correlations between inked and fresh latent fingerprints deposited on different substrates and visualized with TiO 2 . The results indicate that the ridge width of flat inked prints is most similar to fresh latent fingerprints , and these should be used as the comparison standard for future aging studies. © 2017 American Academy of Forensic Sciences.

Indoor Trajectory Tracking Scheme Based on Delaunay Triangulation and Heuristic Information in Wireless Sensor Networks.

Science.gov (United States)

Qin, Junping; Sun, Shiwen; Deng, Qingxu; Liu, Limin; Tian, Yonghong

2017-06-02

Object tracking and detection is one of the most significant research areas for wireless sensor networks. Existing indoor trajectory tracking schemes in wireless sensor networks are based on continuous localization and moving object data mining. Indoor trajectory tracking based on the received signal strength indicator ( RSSI ) has received increased attention because it has low cost and requires no special infrastructure. However, RSSI tracking introduces uncertainty because of the inaccuracies of measurement instruments and the irregularities (unstable, multipath, diffraction) of wireless signal transmissions in indoor environments. Heuristic information includes some key factors for trajectory tracking procedures. This paper proposes a novel trajectory tracking scheme based on Delaunay triangulation and heuristic information (TTDH). In this scheme, the entire field is divided into a series of triangular regions. The common side of adjacent triangular regions is regarded as a regional boundary. Our scheme detects heuristic information related to a moving object's trajectory, including boundaries and triangular regions. Then, the trajectory is formed by means of a dynamic time-warping position-fingerprint-matching algorithm with heuristic information constraints. Field experiments show that the average error distance of our scheme is less than 1.5 m, and that error does not accumulate among the regions.

Multifragment alleles in DNA fingerprints of the parrot, Amazona ventralis

Science.gov (United States)

Brock, M.K.; White, B.N.

1991-01-01

Human DNA probes that identify variable numbers of tandem repeat loci are being used to generate DNA fingerprints in many animal and plant species. In most species the majority of the sc rable autoradiographic bands of the DNA fingerprint represent alleles from numerous unlinked loci. This study was initiated to use DNA fingerprints to determine the amount of band-sharing among captive Hispaniolan parrots (Amazona ventralis) with known genetic relationships. This would form the data base to examine DNA fingerprints of the closely related and endangered Puerto Rican parrot (A. vittata) and to estimate the degree of inbreeding in the relic population. We found by segregation analysis of the bands scored in the DNA fingerprints of the Hispaniolan parrots that there may be as few as two to five loci identified by the human 33.15 probe. Furthermore, at one locus we identified seven alleles, one of which is represented by as many as 19 cosegregating bands. It is unknown how common multiband alleles might be in natural populations, and their existence will cause problems in the assessment of relatedness by band-sharing analysis. We believe, therefore, that a pedigree analysis should be included in all DNA fingerprinting studies, where possible, in order to estimate the number of loci identified by a minisatellite DNA probe and to examine the nature of their alleles.

Intelligent Facial Recognition Systems: Technology advancements for security applications

Energy Technology Data Exchange (ETDEWEB)

Beer, C.L.

1993-07-01

Insider problems such as theft and sabotage can occur within the security and surveillance realm of operations when unauthorized people obtain access to sensitive areas. A possible solution to these problems is a means to identify individuals (not just credentials or badges) in a given sensitive area and provide full time personnel accountability. One approach desirable at Department of Energy facilities for access control and/or personnel identification is an Intelligent Facial Recognition System (IFRS) that is non-invasive to personnel. Automatic facial recognition does not require the active participation of the enrolled subjects, unlike most other biological measurement (biometric) systems (e.g., fingerprint, hand geometry, or eye retinal scan systems). It is this feature that makes an IFRS attractive for applications other than access control such as emergency evacuation verification, screening, and personnel tracking. This paper discusses current technology that shows promising results for DOE and other security applications. A survey of research and development in facial recognition identified several companies and universities that were interested and/or involved in the area. A few advanced prototype systems were also identified. Sandia National Laboratories is currently evaluating facial recognition systems that are in the advanced prototype stage. The initial application for the evaluation is access control in a controlled environment with a constant background and with cooperative subjects. Further evaluations will be conducted in a less controlled environment, which may include a cluttered background and subjects that are not looking towards the camera. The outcome of the evaluations will help identify areas of facial recognition systems that need further development and will help to determine the effectiveness of the current systems for security applications.

Comparison of Powder Dusting and Cyanoacrylate Fuming Techniques in Retrieving Latent Fingerprint Exposed to Environment Conditions

International Nuclear Information System (INIS)

Mayalvanan, Y.; Sri Pawita Albakri Amir Hamzah; Chuan, L.L.; Muhamad Hilmi Baba; Amidon Anan

2014-01-01

Latent fingerprints are one of the best evidence to prove the presence of an individuals presence at the crime scene. There are many techniques available for a successful fingerprint lifting. Two of the most common ones are fingerprint powder dusting and cyanoacrylate fuming. This research aims to compare both techniques and determine which has a higher success rate in retrieving fingerprints exposed to local environmental conditions for three days. Fingerprint samples were collected from 18 subjects on glass, perspex and aluminium slides. These samples were then exposed to local environmental conditions for three days. The fingerprints were then developed using the aforementioned techniques. Based on the results, it can be safely said that, fuming results in clearer fingerprints and more minutiae can be found from the retrieved fingerprints even with exposure to less than optimum local conditions. This proves that fuming is a better fingerprint lifting method to resolve latent fingerprint compared to powder dusting. Surface on which the fingerprint is retrieved from influences the quality of clarity of a latent fingerprint. (author)

Quality improvement of fingerprints of decayed corpses by local thanatopractical processing (Thanatoprint

Directory of Open Access Journals (Sweden)

Gahr, Britta

2013-11-01

Full Text Available Thanatopractical processing allows morphological reconstruction of even advanced decayed bodies. By extracting fluids from the body’s tissue antemortem tenseness and volume can be restored. If bodies are partly subject to thanatopractical processing in the hand region (“Thanatoprint”, fingerprints of high quality can be gathered even in cases of advanced decay. Without this treatment fingerprinting can be extremely difficult, if not impossible. Thanatopractical processing could be applied successfully in cases of partial to subtotal detachment of the epidermis as well. In an interdisciplinary study 400 fingerprints of bodies in various states of decay were examined after application of Thanatoprint. In 76.75% fingerprints were applicable for data entry into AFIS (Automated Fingerprint Identification System; another 11.00% of the fingerprints could be used for the process of non-elimination. Further advantages of the method are low invasivity while maintaining the integrity of the corpse, less time- and material requirement as well as its long-lasting effect.

Distortion Estimation in Compressed Music Using Only Audio Fingerprints

NARCIS (Netherlands)

Doets, P.J.O.; Lagendijk, R.L.

2008-01-01

An audio fingerprint is a compact yet very robust representation of the perceptually relevant parts of an audio signal. It can be used for content-based audio identification, even when the audio is severely distorted. Audio compression changes the fingerprint slightly. We show that these small

A preliminary study of DTI Fingerprinting on stroke analysis.

Science.gov (United States)

Ma, Heather T; Ye, Chenfei; Wu, Jun; Yang, Pengfei; Chen, Xuhui; Yang, Zhengyi; Ma, Jingbo

2014-01-01

DTI (Diffusion Tensor Imaging) is a well-known MRI (Magnetic Resonance Imaging) technique which provides useful structural information about human brain. However, the quantitative measurement to physiological variation of subtypes of ischemic stroke is not available. An automatically quantitative method for DTI analysis will enhance the DTI application in clinics. In this study, we proposed a DTI Fingerprinting technology to quantitatively analyze white matter tissue, which was applied in stroke classification. The TBSS (Tract Based Spatial Statistics) method was employed to generate mask automatically. To evaluate the clustering performance of the automatic method, lesion ROI (Region of Interest) is manually drawn on the DWI images as a reference. The results from the DTI Fingerprinting were compared with those obtained from the reference ROIs. It indicates that the DTI Fingerprinting could identify different states of ischemic stroke and has promising potential to provide a more comprehensive measure of the DTI data. Further development should be carried out to improve DTI Fingerprinting technology in clinics.

Examination of Zinc Oxide Nanoparticles as a Fluorescent Fingerprint Detection Powder

International Nuclear Information System (INIS)

Tun Tun Lin

2010-12-01

Detection of latent fingerprint was performed using zinc oxide nanoparticles which were produced by simple and efficient method in aqueous media from zinc nitrate. Synthesized ZnO nanoparticles were characterized by XRD, SEM and AFM for ZnO purification and particle size examination. In this paper an effort has been made to compare the results of using ZnO nanoparticles and conventional fingerprint powders such as ZnO bulk powder, CaO, TiO2, printer toner powder and graphite. Fingerprints on different materials were also examined by the use of ZnO and Graphite powder, which is currently used in the Central Intelligence Department of Myanmar Police Force.From this research, it was observed that zinc oxide nanoparticles powder produced a much clearer picture of the fingerprints, compared to conventional powders and it has very good quality at sticking to the fingerprint residue but not to the background surface.

dna and seed proteins fingerprinting of egyptian crop plants

African Journals Online (AJOL)

Dr. Haddad

2012-11-01

Nov 1, 2012 ... combinations were used for fingerprinting six cultivars which belongs to barley, rice and wheat cultivars leading to the production of numerous AFLP bands, 300 of them were polymorphic. Thirty SSR markers were obtained from fingerprinting eight cultivars belonging to the five studied species using 11.

A GPU-paralleled implementation of an enhanced face recognition algorithm

Science.gov (United States)

Chen, Hao; Liu, Xiyang; Shao, Shuai; Zan, Jiguo

2013-03-01

Face recognition algorithm based on compressed sensing and sparse representation is hotly argued in these years. The scheme of this algorithm increases recognition rate as well as anti-noise capability. However, the computational cost is expensive and has become a main restricting factor for real world applications. In this paper, we introduce a GPU-accelerated hybrid variant of face recognition algorithm named parallel face recognition algorithm (pFRA). We describe here how to carry out parallel optimization design to take full advantage of many-core structure of a GPU. The pFRA is tested and compared with several other implementations under different data sample size. Finally, Our pFRA, implemented with NVIDIA GPU and Computer Unified Device Architecture (CUDA) programming model, achieves a significant speedup over the traditional CPU implementations.

Fingerprinting of complex mixtures with the use of high performance liquid chromatography, inductively coupled plasma atomic emission spectroscopy and chemometrics

International Nuclear Information System (INIS)

Ni Yongnian; Peng Yunyan; Kokot, Serge

2008-01-01

The molecular and metal profile fingerprints were obtained from a complex substance, Atractylis chinensis DC-a traditional Chinese medicine (TCM), with the use of the high performance liquid chromatography (HPLC) and inductively coupled plasma atomic emission spectroscopy (ICP-AES) techniques. This substance was used in this work as an example of a complex biological material, which has found application as a TCM. Such TCM samples are traditionally processed by the Bran, Cut, Fried and Swill methods, and were collected from five provinces in China. The data matrices obtained from the two types of analysis produced two principal component biplots, which showed that the HPLC fingerprint data were discriminated on the basis of the methods for processing the raw TCM, while the metal analysis grouped according to the geographical origin. When the two data matrices were combined into a one two-way matrix, the resulting biplot showed a clear separation on the basis of the HPLC fingerprints. Importantly, within each different grouping the objects separated according to their geographical origin, and they ranked approximately in the same order in each group. This result suggested that by using such an approach, it is possible to derive improved characterisation of the complex TCM materials on the basis of the two kinds of analytical data. In addition, two supervised pattern recognition methods, K-nearest neighbors (KNNs) method, and linear discriminant analysis (LDA), were successfully applied to the individual data matrices-thus, supporting the PCA approach

DNA fingerprinting in botany: past, present, future

OpenAIRE

Nybom, Hilde; Weising, Kurt; Rotter, Björn

2014-01-01

Almost three decades ago Alec Jeffreys published his seminal Nature papers on the use of minisatellite probes for DNA fingerprinting of humans (Jeffreys and colleagues Nature 1985, 314:67–73 and Nature 1985, 316:76–79). The new technology was soon adopted for many other organisms including plants, and when Hilde Nybom, Kurt Weising and Alec Jeffreys first met at the very First International Conference on DNA Fingerprinting in Berne, Switzerland, in 1990, everybody was enthusiastic about the n...

Accessible biometrics: A frustrated total internal reflection approach to imaging fingerprints.

Science.gov (United States)

Smith, Nathan D; Sharp, James S

2017-05-01

Fingerprints are widely used as a means of identifying persons of interest because of the highly individual nature of the spatial distribution and types of features (or minuta) found on the surface of a finger. This individuality has led to their wide application in the comparison of fingerprints found at crime scenes with those taken from known offenders and suspects in custody. However, despite recent advances in machine vision technology and image processing techniques, fingerprint evidence is still widely being collected using outdated practices involving ink and paper - a process that can be both time consuming and expensive. Reduction of forensic service budgets increasingly requires that evidence be gathered and processed more rapidly and efficiently. However, many of the existing digital fingerprint acquisition devices have proven too expensive to roll out on a large scale. As a result new, low-cost imaging technologies are required to increase the quality and throughput of the processing of fingerprint evidence. Here we describe an inexpensive approach to digital fingerprint acquisition that is based upon frustrated total internal reflection imaging. The quality and resolution of the images produced are shown to be as good as those currently acquired using ink and paper based methods. The same imaging technique is also shown to be capable of imaging powdered fingerprints that have been lifted from a crime scene using adhesive tape or gel lifters. Copyright © 2017 The Chartered Society of Forensic Sciences. Published by Elsevier B.V. All rights reserved.

Solving the Mystery of Fading Fingerprints with London Dispersion Forces.

Science.gov (United States)

Kimbrough, Doris R.; DeLorenzo, Ronald

1998-01-01

Focuses on the kidnapping of a child whose fingerprints were not found inside the crime vehicle. Discusses the investigation that followed and led to knowledge of the differences between the fingerprints of children and adults. (DDR)

Protein Stable Isotope Fingerprinting (P-SIF): Multidimensional Protein Chromatography Coupled to Stable Isotope-Ratio Mass Spectrometry

Science.gov (United States)

Pearson, A.; Bovee, R. J.; Mohr, W.; Tang, T.

2012-12-01

As metagenomics increases our insight into microbial community diversity and metabolic potential, new approaches are required to determine the biogeochemical expression of this potential within ecosystems. Because stable isotopic analysis of the major bioactive elements (C, N) has been used historically to map flows of substrates and energy among macroscopic food webs, similar principles may apply to microbes. To address this challenge, we have developed a new analytical approach called Protein Stable Isotope Fingerprinting (P-SIF). P-SIF generates natural stable isotopic fingerprints of microbial individual or community proteomes. The main advantage of P-SIF is the potential to bridge the gap between diversity and function, thereby providing a window into the "black box" of environmental microbiology and helping to decipher the roles of uncultivated species. Our method implements a three-way, orthogonal scheme to separate mixtures of whole proteins into subfractions dominated by single or closely-related proteins. Protein extracts first are isoelectrically focused in a gel-free technique that yields 12 fractions separated over a gradient of pH 3-10. Each fraction then is separated by size-exclusion chromatography into 20 pools, ranging from >100kD to ~10kD. Finally, each of these pools is subjected to HPLC and collected in 40 time-slices based on protein hydrophobicity. Theoretical calculation reveals that the true chromatographic resolution of the total scheme is 5000, somewhat less than the 9600 resulting fractions. High-yielding fractions are subjected to δ13C analysis by spooling-wire microcombustion irMS (SWiM-irMS) optimized for samples containing 1-5 nmol carbon. Here we will present the method, results for a variety of pure cultures, and preliminary data for a sample of mixed environmental proteins. The data show the promise of this method for unraveling the metabolic complexity hidden within microbial communities.

Road Sign Recognition with Fuzzy Adaptive Pre-Processing Models

Science.gov (United States)

Lin, Chien-Chuan; Wang, Ming-Shi

2012-01-01

A road sign recognition system based on adaptive image pre-processing models using two fuzzy inference schemes has been proposed. The first fuzzy inference scheme is to check the changes of the light illumination and rich red color of a frame image by the checking areas. The other is to check the variance of vehicle's speed and angle of steering wheel to select an adaptive size and position of the detection area. The Adaboost classifier was employed to detect the road sign candidates from an image and the support vector machine technique was employed to recognize the content of the road sign candidates. The prohibitory and warning road traffic signs are the processing targets in this research. The detection rate in the detection phase is 97.42%. In the recognition phase, the recognition rate is 93.04%. The total accuracy rate of the system is 92.47%. For video sequences, the best accuracy rate is 90.54%, and the average accuracy rate is 80.17%. The average computing time is 51.86 milliseconds per frame. The proposed system can not only overcome low illumination and rich red color around the road sign problems but also offer high detection rates and high computing performance. PMID:22778650

Spectrum-effect relationship between HPLC fingerprints and hypolipidemic effect of Curcuma aromatica.

Science.gov (United States)

Liu, Meiqiong; Wu, Youjiao; Huang, Shushi; Liu, Huagang; Feng, Jie

2018-02-23

Curcuma aromatica is used as a traditional Chinese medicine, and it is mainly distributed in Guangxi, China. In this study, 10 batches of C. aromatica were collected from different origins in Guangxi. The fingerprints were established by HPLC technique to investigate the quality stability of C. aromatica. The spectrum-effect relationship between HPLC fingerprints and hypolipidemic effect of C. aromatica was assessed by similarity analysis, gray relational analysis and multiple linear regression analysis. From the results, the similarity values between each batch of C. aromatica and reference fingerprint were >0.880, indicating the good quality stability of the 10 batches of C. aromatica. Twenty common peaks were selected as the fingerprints to evaluate the quality and hypolipidemic effect of C. aromatica. The results of spectrum-effect relationship showed that peaks 10, 18, 13, 15 and 17 in the fingerprints were closely related to hypolipidemic effect. This study successfully established the spectrum-effect relationship between HPLC fingerprints and hypolipidemic effect of C. aromatica, which provided methods for quality control and more effectively studies on bioactive compounds of C. aromatica. It could also provide a new simple and effective method for utilizing the fingerprints to optimize the Chinese prescription and develop traditional Chinese medicine. Copyright © 2018 John Wiley & Sons, Ltd.

A Modified Electrostatic Adsorption Apparatus for Latent Fingerprint Development on Unfired Cartridge Cases.

Science.gov (United States)

Xu, Jingyang; Zhang, Ziyuan; Zheng, Xiaochun; Bond, John W

2017-05-01

Visualization of latent fingerprints on metallic surfaces by the method of applying electrostatic charging and adsorption is considered as a promising chemical-free method, which has the merit of nondestruction, and is considered to be effective for some difficult situations such as aged fingerprint deposits or those exposed to environmental extremes. In fact, a portable electrostatic generator can be easily accessible in a local forensic technology laboratory, which is already widely used in the visualization of footwear impressions. In this study, a modified version of this electrostatic apparatus is proposed for latent fingerprint development and has shown great potential in visualizing fingerprints on metallic surfaces such as cartridge cases. Results indicate that this experimental arrangement can successfully develop aged latent fingerprints on metal surfaces, and we demonstrate its effectiveness compared with existing conventional fingerprint recovery methods. © 2016 American Academy of Forensic Sciences.

Detecting anthropogenic climate change with an optimal fingerprint method

International Nuclear Information System (INIS)

Hegerl, G.C.; Storch, H. von; Hasselmann, K.; Santer, B.D.; Jones, P.D.

1994-01-01

We propose a general fingerprint strategy to detect anthropogenic climate change and present application to near surface temperature trends. An expected time-space-variable pattern of anthropogenic climate change (the 'signal') is identified through application of an appropriate optimally matched space-time filter (the 'fingerprint') to the observations. The signal and the fingerprint are represented in a space with sufficient observed and simulated data. The signal pattern is derived from a model-generated prediction of anthropogenic climate change. Application of the fingerprint filter to the data yields a scalar detection variable. The statistically optimal fingerprint is obtained by weighting the model-predicted pattern towards low-noise directions. A combination of model output and observations is used to estimate the noise characteristics of the detection variable, arising from the natural variability of climate in the absence of external forcing. We test then the null hypothesis that the observed climate change is part of natural climate variability. We conclude that a statistically significant externally induced warming has been observed, with the caveat of a possibly inadequate estimate of the internal climate variability. In order to attribute this warming uniquely to anthropogenic greenhouse gas forcing, more information on the climate's response to other forcing mechanisms (e.g. changes in solar radiation, volcanic or anthropogenic aerosols) and their interaction is needed. (orig./KW)

Establishment and application of milk fingerprint by gel filtration chromatography.

Science.gov (United States)

Gao, P; Li, J; Li, Z; Hao, J; Zan, L

2016-12-01

Raw milk adulteration frequently occurs in undeveloped countries. It not only reduces the nutritional value of milk, but it is also harmful to consumers. In this paper, we focused on investigating an efficient method for the quality control of raw milk protein. A gel filtration chromatography (GFC) fingerprint method combined with chemometrics was developed for fingerprint analysis of raw milk. To optimize the GFC conditions, milk fat was removed by centrifugation, and GFC analysis was performed on a Superdex 75 10/300GL column (Just Scientific, Shanghai, China) with 0.2 M NaH 2 PO 4 -Na 2 HPO 4 buffer (pH 7.0) as the mobile phase. The flow rate was 0.5mL/min, and the detection wavelength was set at 280 nm. Ten batches of 120 raw milk samples were analyzed to establish the GFC fingerprint under optimal conditions. Six major peaks common to the chromatogram of each raw milk sample were selected for fingerprint analysis, and the characteristic peaks were used to establish a standard chromatographic fingerprint. Principal component analysis was then applied to classify GFC information of adulterated milk and raw milk, allowing adulterated samples to be effectively screened out from the raw milk in principal component analysis scores plot. The fingerprint method demonstrates promising features in detecting milk protein adulteration. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Polarization-based and specular-reflection-based noncontact latent fingerprint imaging and lifting

Science.gov (United States)

Lin, Shih-Schön; Yemelyanov, Konstantin M.; Pugh, Edward N., Jr.; Engheta, Nader

2006-09-01

In forensic science the finger marks left unintentionally by people at a crime scene are referred to as latent fingerprints. Most existing techniques to detect and lift latent fingerprints require application of a certain material directly onto the exhibit. The chemical and physical processing applied to the fingerprint potentially degrades or prevents further forensic testing on the same evidence sample. Many existing methods also have deleterious side effects. We introduce a method to detect and extract latent fingerprint images without applying any powder or chemicals on the object. Our method is based on the optical phenomena of polarization and specular reflection together with the physiology of fingerprint formation. The recovered image quality is comparable to existing methods. In some cases, such as the sticky side of tape, our method shows unique advantages.

Ubiquity of Wi-Fi: Crowdsensing Properties for Urban Fingerprint Positioning

Directory of Open Access Journals (Sweden)

LECA, C. L.

2017-11-01

Full Text Available Positioning systems based on location fingerprinting have become an area of intense research, mainly with the aim of providing indoor localization. Many challenges arise when trying to deploy location fingerprinting to an outdoor environment. The main problem is achieving coverage of large outdoor spaces, which needs an intensive data gathering effort. This paper proposes the use of mobile crowdsensing in order to build a fingerprint database consisting of Wi-Fi networks received signal strength measurements. Mobile crowdsensing is represented by the usage of smart-phones equipped with GPS and Wi-Fi sensors for the collection of fingerprints. The primary objective of this work is to prove the feasibility of urban positioning using Wi-Fi crowdsensed data by showing that Wi-Fi networks are ubiquitous in urban areas. We then examine the gathered data and report our findings on challenges in building and maintaining a large-scale fingerprint database, the influence of the data collection method on the Wi-Fi data and the influence of fading on measurements. As Wi-Fi access-points are shown to exhibit mobility, we also propose and analyze methods for detecting and classification of mobile and static access-points.

Accommodating error analysis in comparison and clustering of molecular fingerprints.

Science.gov (United States)

Salamon, H; Segal, M R; Ponce de Leon, A; Small, P M

1998-01-01

Molecular epidemiologic studies of infectious diseases rely on pathogen genotype comparisons, which usually yield patterns comprising sets of DNA fragments (DNA fingerprints). We use a highly developed genotyping system, IS6110-based restriction fragment length polymorphism analysis of Mycobacterium tuberculosis, to develop a computational method that automates comparison of large numbers of fingerprints. Because error in fragment length measurements is proportional to fragment length and is positively correlated for fragments within a lane, an align-and-count method that compensates for relative scaling of lanes reliably counts matching fragments between lanes. Results of a two-step method we developed to cluster identical fingerprints agree closely with 5 years of computer-assisted visual matching among 1,335 M. tuberculosis fingerprints. Fully documented and validated methods of automated comparison and clustering will greatly expand the scope of molecular epidemiology.

Hyperbolic Location Fingerprinting: A Calibration-Free Solution for Handling Differences in Signal Strength

DEFF Research Database (Denmark)

Kjærgaard, Mikkel Baun; Munk, Carsten Valdemar

2008-01-01

records fingerprints as signal-strength ratios between pairs of base stations instead of absolute signal-strength values. The proposed solution has been evaluated by extending two well-known location fingerprinting techniques to hyperbolic location fingerprinting. The extended techniques have been tested...

Multimodal Biometric System Based on the Recognition of Face and Both Irises

Directory of Open Access Journals (Sweden)

Yeong Gon Kim

2012-09-01

Full Text Available The performance of unimodal biometric systems (based on a single modality such as face or fingerprint has to contend with various problems, such as illumination variation, skin condition and environmental conditions, and device variations. Therefore, multimodal biometric systems have been used to overcome the limitations of unimodal biometrics and provide high accuracy recognition. In this paper, we propose a new multimodal biometric system based on score level fusion of face and both irises' recognition. Our study has the following novel features. First, the device proposed acquires images of the face and both irises simultaneously. The proposed device consists of a face camera, two iris cameras, near-infrared illuminators and cold mirrors. Second, fast and accurate iris detection is based on two circular edge detections, which are accomplished in the iris image on the basis of the size of the iris detected in the face image. Third, the combined accuracy is enhanced by combining each score for the face and both irises using a support vector machine. The experimental results show that the equal error rate for the proposed method is 0.131%, which is lower than that of face or iris recognition and other fusion methods.

Zone-based RSS Reporting for Location Fingerprinting

DEFF Research Database (Denmark)

Kjærgaard, Mikkel Baun; Treu, Georg; Linnhoff–Popien, Claudia

2007-01-01

In typical location fingerprinting systems a tracked terminal reports sampled Received Signal Strength (RSS) values to a location server, which estimates its position based on a database of pre-recorded RSS fingerprints. So far, poll-based and periodic RSS reporting has been proposed. However......, for supporting proactive Location-based Services (LBSs), triggered by pre-defined spatial events, the periodic protocol is inefficient. Hence, this paper introduces zone-based RSS reporting: the location server translates geographical zones defined by the LBS into RSS-based representations, which are dynamically...

Extracting valley-ridge lines from point-cloud-based 3D fingerprint models.

Science.gov (United States)

Pang, Xufang; Song, Zhan; Xie, Wuyuan

2013-01-01

3D fingerprinting is an emerging technology with the distinct advantage of touchless operation. More important, 3D fingerprint models contain more biometric information than traditional 2D fingerprint images. However, current approaches to fingerprint feature detection usually must transform the 3D models to a 2D space through unwrapping or other methods, which might introduce distortions. A new approach directly extracts valley-ridge features from point-cloud-based 3D fingerprint models. It first applies the moving least-squares method to fit a local paraboloid surface and represent the local point cloud area. It then computes the local surface's curvatures and curvature tensors to facilitate detection of the potential valley and ridge points. The approach projects those points to the most likely valley-ridge lines, using statistical means such as covariance analysis and cross correlation. To finally extract the valley-ridge lines, it grows the polylines that approximate the projected feature points and removes the perturbations between the sampled points. Experiments with different 3D fingerprint models demonstrate this approach's feasibility and performance.

An atomistic fingerprint algorithm for learning ab initio molecular force fields

Science.gov (United States)

Tang, Yu-Hang; Zhang, Dongkun; Karniadakis, George Em

2018-01-01

Molecular fingerprints, i.e., feature vectors describing atomistic neighborhood configurations, is an important abstraction and a key ingredient for data-driven modeling of potential energy surface and interatomic force. In this paper, we present the density-encoded canonically aligned fingerprint algorithm, which is robust and efficient, for fitting per-atom scalar and vector quantities. The fingerprint is essentially a continuous density field formed through the superimposition of smoothing kernels centered on the atoms. Rotational invariance of the fingerprint is achieved by aligning, for each fingerprint instance, the neighboring atoms onto a local canonical coordinate frame computed from a kernel minisum optimization procedure. We show that this approach is superior over principal components analysis-based methods especially when the atomistic neighborhood is sparse and/or contains symmetry. We propose that the "distance" between the density fields be measured using a volume integral of their pointwise difference. This can be efficiently computed using optimal quadrature rules, which only require discrete sampling at a small number of grid points. We also experiment on the choice of weight functions for constructing the density fields and characterize their performance for fitting interatomic potentials. The applicability of the fingerprint is demonstrated through a set of benchmark problems.

Mid-infrared supercontinuum generation in the fingerprint region

DEFF Research Database (Denmark)

Møller, Uffe Visbech; Petersen, Christian Rosenberg; Kubat, Irnis

The mid-infrared spectral region is of great technical and scientific interest because most molecules display fundamental vibrational absorptions in this region, leaving distinctive spectral fingerprints. Here, we demonstrate experimentally that launching intense ultra-short pulses with a central...... the potential of fibres to emit across the mid-infrared molecular fingerprint region, which is of key importance for applications such as early cancer diagnostics, gas sensing and food quality control....

Graphene Nanopres for DNA Fingerprinting

Science.gov (United States)

Ahmed, Towfiq; Balatsky, Alexander V.; Haraldsen, J. T.; Schuller, Ivan K.; di Ventra, M.; Wikfeldt, K. T.

2013-03-01

The recent progress in nanopore experiments with transverse current is important for the development of fast, accurate and cheap finger-printing techniques for single nucleotide. Despite its enormous potential for the next generation DNA sequencing technology, the presence of large noise in the temporal spectrum of transverse current remains a big challenge for getting highly accurate interpretation of data. In this paper we present our abinitio calculations, and propose graphene based device for DNA fingerprinting. We calculate transmission current through graphene for each DNA base (A,C,G,T). As shown in our work, a proper time-series analysis of a signal provides a higher quality information in identifying single bio-molecule is translocating through the nanopores. This work is supported by LANL, Nordita, US DOE, AFOSR, and NIH.

Impact of SNR, masker type and noise reduction processing on sentence recognition performance and listening effort as indicated by the pupil dilation response

DEFF Research Database (Denmark)

Ohlenforst, Barbara; Wendt, Dorothea; Kramer, Sophia E

2018-01-01

Recent studies have shown that activating the noise reduction scheme in hearing aids results in a smaller peak pupil dilation (PPD), indicating reduced listening effort, at 50% and 95% correct sentence recognition with a 4-talker masker. The objective of this study was to measure the effect...... of the noise reduction scheme (on or off) on PPD and sentence recognition across a wide range of signal-to-noise ratios (SNRs) from +16 dB to -12 dB and two masker types (4-talker and stationary noise). Relatively low PPDs were observed at very low (-12 dB) and very high (+16 dB to +8 dB) SNRs presumably due...... to 'giving up' and 'easy listening', respectively. The maximum PPD was observed with SNRs at approximately 50% correct sentence recognition. Sentence recognition with both masker types was significantly improved by the noise reduction scheme, which corresponds to the shift in performance from SNR function...

Fissile fingerprints

International Nuclear Information System (INIS)

Edwards, R.

1995-01-01

This article looks at recent research which may allow police and customs officers to detect smuggled weapons-grade plutonium and uranium. Contrary to popular opinion, nuclear materials do not have a nuclear ''fingerprint'' but enough information can be gleaned from sources to confirm what has been learnt from other data. Indeed, two leading nuclear laboratories can look at the same analytical results and draw different conclusions. The case of a lead cylinder seized from a German garage is examined to illustrate the confusion. (UK)

Performance analysis of a hybrid fingerprint extracted from optical coherence tomography fingertip scans

CSIR Research Space (South Africa)

Darlow, Luke N

2016-06-01

Full Text Available The Hybrid fingerprint is a local-quality-specific blend of the surface and internal fingerprints, extracted from optical coherence tomography scans. Owing to its origin, and the manner in which it is obtained, the Hybrid fingerprint is a high...

Investigation of gamma-ray fingerprint identifying mechanism for the types of radiation sources

CERN Document Server

Liu Su Ping; Gu Dang Chang; Gong-Jian; Hao Fan Hua; Hu Guang Chun

2002-01-01

Radiation fingerprints sometimes can be used to label and identify the radiation resources. For instance, in a future nuclear reduction treaty that requires verification of irreversible dismantling of reduced nuclear warheads, the radiation fingerprints of nuclear warheads are expected to play a key role in labelling and identifying the reduced warheads. It would promote the development of nuclear warheads deep-cuts verification technologies if authors start right now some investigations on the issues related to the radiation fingerprints. The author dedicated to the investigation of gamma-ray fingerprint identifying mechanism for the types of radiation resources. The purpose of the identifying mechanism investigation is to find a credible way to tell whether any two gamma-ray spectral fingerprints that are under comparison are radiated from the same resource. The authors created the spectrum pattern comparison (SPC) to study the comparability of the two radiation fingerprints. Guided by the principle of SPC,...

The FBI wavelet/scalar quantization standard for gray-scale fingerprint image compression

Energy Technology Data Exchange (ETDEWEB)

Bradley, J.N.; Brislawn, C.M. [Los Alamos National Lab., NM (United States); Hopper, T. [Federal Bureau of Investigation, Washington, DC (United States)

1993-05-01

The FBI has recently adopted a standard for the compression of digitized 8-bit gray-scale fingerprint images. The standard is based on scalar quantization of a 64-subband discrete wavelet transform decomposition of the images, followed by Huffman coding. Novel features of the algorithm include the use of symmetric boundary conditions for transforming finite-length signals and a subband decomposition tailored for fingerprint images scanned at 500 dpi. The standard is intended for use in conjunction with ANSI/NBS-CLS 1-1993, American National Standard Data Format for the Interchange of Fingerprint Information, and the FBI`s Integrated Automated Fingerprint Identification System.

Multispectral Palmprint Recognition Using a Quaternion Matrix

Directory of Open Access Journals (Sweden)

Yafeng Li

2012-04-01

Full Text Available Palmprints have been widely studied for biometric recognition for many years. Traditionally, a white light source is used for illumination. Recently, multispectral imaging has drawn attention because of its high recognition accuracy. Multispectral palmprint systems can provide more discriminant information under different illuminations in a short time, thus they can achieve better recognition accuracy. Previously, multispectral palmprint images were taken as a kind of multi-modal biometrics, and the fusion scheme on the image level or matching score level was used. However, some spectral information will be lost during image level or matching score level fusion. In this study, we propose a new method for multispectral images based on a quaternion model which could fully utilize the multispectral information. Firstly, multispectral palmprint images captured under red, green, blue and near-infrared (NIR illuminations were represented by a quaternion matrix, then principal component analysis (PCA and discrete wavelet transform (DWT were applied respectively on the matrix to extract palmprint features. After that, Euclidean distance was used to measure the dissimilarity between different features. Finally, the sum of two distances and the nearest neighborhood classifier were employed for recognition decision. Experimental results showed that using the quaternion matrix can achieve a higher recognition rate. Given 3000 test samples from 500 palms, the recognition rate can be as high as 98.83%.

A novel hand-type detection technique with fingerprint sensor

Science.gov (United States)

Abe, Narishige; Shinzaki, Takashi

2013-05-01

In large-scale biometric authentication systems such as the US-Visit (USA), a 10-fingerprints scanner which simultaneously captures four fingerprints is used. In traditional systems, specific hand-types (left or right) are indicated, but it is difficult to detect hand-type due to the hand rotation and the opening and closing of fingers. In this paper, we evaluated features that were extracted from hand images (which were captured by a general optical scanner) that are considered to be effective for detecting hand-type. Furthermore, we extended the knowledge to real fingerprint images, and evaluated the accuracy with which it detects hand-type. We obtained an accuracy of about 80% with only three fingers (index, middle, ring finger).

Visualization of latent fingerprints beneath opaque electrical tapes by optical coherence tomography

Science.gov (United States)

Liu, Kangkang; Zhang, Ning; Meng, Li; Li, Zhigang; Xu, Xiaojing

2018-03-01

Electrical tape is found as one type of important trace evidence in crime scene. For example, it is very frequently used to insulate wires in explosive devices in many criminal cases. The fingerprints of the suspects were often left on the adhesive side of the tapes, which can provide very useful clues for the investigation and make it possible for individual identification. The most commonly used method to detect and visualize those latent fingerprints is to peel off each layer of the tapes first and then adopt the chemical methods to develop the fingerprints on the tapes. However, the peeling-off and chemical development process would degrade and contaminate the fingerprints and thus adversely affect the accuracy of identification. Optical coherence tomography (OCT) is a novel forensic imaging modality based on lowcoherence interferometry, which has the advantages of non-destruction, micrometer-level high resolution and crosssectional imaging. In this study, a fiber-based spectral-domain OCT (SD-OCT) system with {6μm resolution was employed to obtain the image of fingerprint sandwiched between two opaque electrical tapes without any pre-processing procedure like peeling-off. Three-dimensional (3D) OCT reconstruction was performed and the subsurface image was produced to visualize the latent fingerprints. The results demonstrate that OCT is a promising tool for recovering the latent fingerprints hidden beneath opaque electrical tape non-destructively and rapidly.

DNA fingerprinting in forensics: past, present, future.

Science.gov (United States)

Roewer, Lutz

2013-11-18

DNA fingerprinting, one of the great discoveries of the late 20th century, has revolutionized forensic investigations. This review briefly recapitulates 30 years of progress in forensic DNA analysis which helps to convict criminals, exonerate the wrongly accused, and identify victims of crime, disasters, and war. Current standard methods based on short tandem repeats (STRs) as well as lineage markers (Y chromosome, mitochondrial DNA) are covered and applications are illustrated by casework examples. Benefits and risks of expanding forensic DNA databases are discussed and we ask what the future holds for forensic DNA fingerprinting.

Quantitative analysis and demonstration of modified triple-branch signal detection scheme for SAC-OCDMA systems

Science.gov (United States)

Chen, Fujun; Feng, Gang; Zhang, Siwei

2016-10-01

The triple-branch signal detection (TBSD) scheme can eliminate multiple-user interference (MUI) without fixed in-phase cross-correlation (IPCC) stipulation in the spectral-amplitude-coding optical code division multiple access (SACOCDMA) systems. In this paper, we modify the traditional TBSD scheme and theoretically analyze the principle of the MUI elimination. Then, the bit-error-rate (BER) performance of the modified TBSD scheme is investigated under multiple transmission rates. The results show that the modified TBSD employing the codes with unfixed IPCC can achieve simultaneous optical code recognition and MUI elimination in the SAC-OCDMA.

DNA fingerprinting, DNA barcoding, and next generation sequencing technology in plants.

Science.gov (United States)

Sucher, Nikolaus J; Hennell, James R; Carles, Maria C

2012-01-01

DNA fingerprinting of plants has become an invaluable tool in forensic, scientific, and industrial laboratories all over the world. PCR has become part of virtually every variation of the plethora of approaches used for DNA fingerprinting today. DNA sequencing is increasingly used either in combination with or as a replacement for traditional DNA fingerprinting techniques. A prime example is the use of short, standardized regions of the genome as taxon barcodes for biological identification of plants. Rapid advances in "next generation sequencing" (NGS) technology are driving down the cost of sequencing and bringing large-scale sequencing projects into the reach of individual investigators. We present an overview of recent publications that demonstrate the use of "NGS" technology for DNA fingerprinting and DNA barcoding applications.

RF-Based Location Using Interpolation Functions to Reduce Fingerprint Mapping

Science.gov (United States)

Ezpeleta, Santiago; Claver, José M.; Pérez-Solano, Juan J.; Martí, José V.

2015-01-01

Indoor RF-based localization using fingerprint mapping requires an initial training step, which represents a time consuming process. This location methodology needs a database conformed with RSSI (Radio Signal Strength Indicator) measures from the communication transceivers taken at specific locations within the localization area. But, the real world localization environment is dynamic and it is necessary to rebuild the fingerprint database when some environmental changes are made. This paper explores the use of different interpolation functions to complete the fingerprint mapping needed to achieve the sought accuracy, thereby reducing the effort in the training step. Also, different distributions of test maps and reference points have been evaluated, showing the validity of this proposal and necessary trade-offs. Results reported show that the same or similar localization accuracy can be achieved even when only 50% of the initial fingerprint reference points are taken. PMID:26516862

DNA Fingerprinting Using PCR: A Practical Forensic Science Activity

Science.gov (United States)

Choi, Hyun-Jung; Ahn, Jung Hoon; Ko, Minsu

2008-01-01

This paper describes a forensic science simulation programme applicable for use in colleges. Students were asked to find a putative suspect by DNA fingerprinting using a simple protocol developed in this study. DNA samples were obtained from a hair root and a drop of blood, common sources of DNA in forensic science. The DNA fingerprinting protocol…

Kernel Learning of Histogram of Local Gabor Phase Patterns for Face Recognition

Directory of Open Access Journals (Sweden)

Bineng Zhong

2008-06-01

Full Text Available This paper proposes a new face recognition method, named kernel learning of histogram of local Gabor phase pattern (K-HLGPP, which is based on Daugman’s method for iris recognition and the local XOR pattern (LXP operator. Unlike traditional Gabor usage exploiting the magnitude part in face recognition, we encode the Gabor phase information for face classification by the quadrant bit coding (QBC method. Two schemes are proposed for face recognition. One is based on the nearest-neighbor classifier with chi-square as the similarity measurement, and the other makes kernel discriminant analysis for HLGPP (K-HLGPP using histogram intersection and Gaussian-weighted chi-square kernels. The comparative experiments show that K-HLGPP achieves a higher recognition rate than other well-known face recognition systems on the large-scale standard FERET, FERET200, and CAS-PEAL-R1 databases.

THE INVESTIGATION OF THE RELATIONSHIP BETWEEN FINGERPRINT PATTERNS AND CRIME TYPES

OpenAIRE

DELİCE, Murat; DUMAN, Ali; ÖZEL, Şaban Ali

2014-01-01

The exclusivity of prints at the tip of each individuals fingers is known for thousands of years and these prints are used for security purposes for a long time. Recent developments have pointed out that fingerprint patterns are related to gender, heredity, diseases, blood types and even character. However, the relationship between fingerprint patterns and crime types has not been explored. In order to meet this need, this research study examines the fingerprint patterns of suspects who are i...

Improving Speaker Recognition by Biometric Voice Deconstruction

Directory of Open Access Journals (Sweden)

Luis Miguel eMazaira-Fernández

2015-09-01

Full Text Available Person identification, especially in critical environments, has always been a subject of great interest. However, it has gained a new dimension in a world threatened by a new kind of terrorism that uses social networks (e.g. YouTube to broadcast its message. In this new scenario, classical identification methods (such fingerprints or face recognition have been forcedly replaced by alternative biometric characteristics such as voice, as sometimes this is the only feature available. Through the present paper, a new methodology to characterize speakers will be shown. This methodology is benefiting from the advances achieved during the last years in understanding and modelling voice production. The paper hypothesizes that a gender dependent characterization of speakers combined with the use of a new set of biometric parameters extracted from the components resulting from the deconstruction of the voice into its glottal source and vocal tract estimates, will enhance recognition rates when compared to classical approaches. A general description about the main hypothesis and the methodology followed to extract gender-dependent extended biometric parameters are given. Experimental validation is carried out both on a highly controlled acoustic condition database, and on a mobile phone network recorded under non-controlled acoustic conditions.

Application of DNA fingerprints for cell-line individualization.

OpenAIRE

Gilbert, D A; Reid, Y A; Gail, M H; Pee, D; White, C; Hay, R J; O'Brien, S J

1990-01-01

DNA fingerprints of 46 human cell lines were derived using minisatellite probes for hypervariable genetic loci. The incidence of 121 HaeIII DNA fragments among 33 cell lines derived from unrelated individuals was used to estimate allelic and genotypic frequencies for each fragment and for composite individual DNA fingerprints. We present a quantitative estimate of the extent of genetic difference between individuals, an estimate based on the percentage of restriction fragments at which they d...

A new method of artificial latent fingerprint creation using artificial sweat and inkjet printer.

Science.gov (United States)

Hong, Sungwook; Hong, Ingi; Han, Aleum; Seo, Jin Yi; Namgung, Juyoung

2015-12-01

In order to study fingerprinting in the field of forensic science, it is very important to have two or more latent fingerprints with identical chemical composition and intensity. However, it is impossible to obtain identical fingerprints, in reality, because fingerprinting comes out slightly differently every time. A previous research study had proposed an artificial fingerprint creation method in which inkjet ink was replaced with amino acids and sodium chloride solution: the components of human sweat. But, this method had some drawbacks: divalent cations were not added while formulating the artificial sweat solution, and diluted solutions were used for creating weakly deposited latent fingerprint. In this study, a method was developed for overcoming the drawbacks of the methods used in the previous study. Several divalent cations were added in this study because the amino acid-ninhydrin (or some of its analogues) complex is known to react with divalent cations to produce a photoluminescent product; and, similarly, the amino acid-1,2-indanedione complex is known to be catalyzed by a small amount of zinc ions to produce a highly photoluminescent product. Also, in this study, a new technique was developed which enables to adjust the intensity when printing the latent fingerprint patterns. In this method, image processing software is used to control the intensity of the master fingerprint patterns, which adjusts the printing intensity of the latent fingerprints. This new method opened the way to produce a more realistic artificial fingerprint in various strengths with one artificial sweat working solution. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Multi-font printed Mongolian document recognition system

Science.gov (United States)

Peng, Liangrui; Liu, Changsong; Ding, Xiaoqing; Wang, Hua; Jin, Jianming

2009-01-01

Mongolian is one of the major ethnic languages in China. Large amount of Mongolian printed documents need to be digitized in digital library and various applications. Traditional Mongolian script has unique writing style and multi-font-type variations, which bring challenges to Mongolian OCR research. As traditional Mongolian script has some characteristics, for example, one character may be part of another character, we define the character set for recognition according to the segmented components, and the components are combined into characters by rule-based post-processing module. For character recognition, a method based on visual directional feature and multi-level classifiers is presented. For character segmentation, a scheme is used to find the segmentation point by analyzing the properties of projection and connected components. As Mongolian has different font-types which are categorized into two major groups, the parameter of segmentation is adjusted for each group. A font-type classification method for the two font-type group is introduced. For recognition of Mongolian text mixed with Chinese and English, language identification and relevant character recognition kernels are integrated. Experiments show that the presented methods are effective. The text recognition rate is 96.9% on the test samples from practical documents with multi-font-types and mixed scripts.

Noise-robust speech recognition through auditory feature detection and spike sequence decoding.

Science.gov (United States)

Schafer, Phillip B; Jin, Dezhe Z

2014-03-01

Speech recognition in noisy conditions is a major challenge for computer systems, but the human brain performs it routinely and accurately. Automatic speech recognition (ASR) systems that are inspired by neuroscience can potentially bridge the performance gap between humans and machines. We present a system for noise-robust isolated word recognition that works by decoding sequences of spikes from a population of simulated auditory feature-detecting neurons. Each neuron is trained to respond selectively to a brief spectrotemporal pattern, or feature, drawn from the simulated auditory nerve response to speech. The neural population conveys the time-dependent structure of a sound by its sequence of spikes. We compare two methods for decoding the spike sequences--one using a hidden Markov model-based recognizer, the other using a novel template-based recognition scheme. In the latter case, words are recognized by comparing their spike sequences to template sequences obtained from clean training data, using a similarity measure based on the length of the longest common sub-sequence. Using isolated spoken digits from the AURORA-2 database, we show that our combined system outperforms a state-of-the-art robust speech recognizer at low signal-to-noise ratios. Both the spike-based encoding scheme and the template-based decoding offer gains in noise robustness over traditional speech recognition methods. Our system highlights potential advantages of spike-based acoustic coding and provides a biologically motivated framework for robust ASR development.

Nucleus fingerprinting for the unique identification of Feulgen-stained nuclei

Science.gov (United States)

Friedrich, David; Brozio, Matthias; Bell, André; Biesterfeld, Stefan; Böcking, Alfred; Aach, Til

2012-03-01

DNA Image Cytometry is a method for non-invasive cancer diagnosis which measures the DNA content of Feulgen-stained nuclei. DNA content is measured using a microscope system equipped with a digital camera as a densitometer and estimating the DNA content from the absorption of light when passing through the nuclei. However, a DNA Image Cytometry measurement is only valid if each nucleus is only measured once. To assist the user in preventing multiple measurements of the same nucleus, we have developed a unique digital identifier for the characterization of Feulgen-stained nuclei, the so called Nucleus Fingerprint. Only nuclei with a new fingerprint can be added to the measurement. This fingerprint is based on basic nucleus features, the contour of the nucleus and the spatial relationship to nuclei in the vicinity. Based on this characterization, a classifier for testing two nuclei for identity is presented. In a pairwise comparison of ~40000 pairs of mutually different nuclei, 99.5% were classified as different. In another 450 tests, the fingerprints of the same nucleus recorded a second time were in all cases judged identical. We therefore conclude that our Nucleus Fingerprint approach robustly prevents the repeated measurement of nuclei in DNA Image Cytometry.

Fingerprint Image Enhancement Based on Second Directional Derivative of the Digital Image

Directory of Open Access Journals (Sweden)

Onnia Vesa

2002-01-01

Full Text Available This paper presents a novel approach of fingerprint image enhancement that relies on detecting the fingerprint ridges as image regions where the second directional derivative of the digital image is positive. A facet model is used in order to approximate the derivatives at each image pixel based on the intensity values of pixels located in a certain neighborhood. We note that the size of this neighborhood has a critical role in achieving accurate enhancement results. Using neighborhoods of various sizes, the proposed algorithm determines several candidate binary representations of the input fingerprint pattern. Subsequently, an output binary ridge-map image is created by selecting image zones, from the available binary image candidates, according to a MAP selection rule. Two public domain collections of fingerprint images are used in order to objectively assess the performance of the proposed fingerprint image enhancement approach.

The FBI wavelet/scalar quantization standard for gray-scale fingerprint image compression

Energy Technology Data Exchange (ETDEWEB)

Bradley, J.N.; Brislawn, C.M. (Los Alamos National Lab., NM (United States)); Hopper, T. (Federal Bureau of Investigation, Washington, DC (United States))

1993-01-01

The FBI has recently adopted a standard for the compression of digitized 8-bit gray-scale fingerprint images. The standard is based on scalar quantization of a 64-subband discrete wavelet transform decomposition of the images, followed by Huffman coding. Novel features of the algorithm include the use of symmetric boundary conditions for transforming finite-length signals and a subband decomposition tailored for fingerprint images scanned at 500 dpi. The standard is intended for use in conjunction with ANSI/NBS-CLS 1-1993, American National Standard Data Format for the Interchange of Fingerprint Information, and the FBI's Integrated Automated Fingerprint Identification System.

[Baking method of Platycladi Cacumen Carbonisatum based on similarity of UPLC fingerprints].

Science.gov (United States)

Shan, Mingqiu; Chen, Chao; Yao, Xiaodong; Ding, Anwei

2010-09-01

To establish a baking method of Platycladi Cacumen Carbonisatum for providing a new idea to Carbonic Herbs' research. Samples were prepared in an oven for different time at different temperatures separately. Then the fingerprints of the samples were determined by UPLC. According to the standard fingerprint, the similarities of the samples' fingerprints were compared. The similarities of 3 samples, which were baked at 230 degrees C for 20 min, 30 min and at 240 degrees C for 20 min, were above 0.96. According to the similarities of the fingerprints and in view of the appearances, Platycladi Cacumen Carbonizing should be baked at 230 degrees C for 20 min.

Fingerprint matching algorithm for poor quality images

Directory of Open Access Journals (Sweden)

Vedpal Singh

2015-04-01

Full Text Available The main aim of this study is to establish an efficient platform for fingerprint matching for low-quality images. Generally, fingerprint matching approaches use the minutiae points for authentication. However, it is not such a reliable authentication method for low-quality images. To overcome this problem, the current study proposes a fingerprint matching methodology based on normalised cross-correlation, which would improve the performance and reduce the miscalculations during authentication. It would decrease the computational complexities. The error rate of the proposed method is 5.4%, which is less than the two-dimensional (2D dynamic programming (DP error rate of 5.6%, while Lee's method produces 5.9% and the combined method has 6.1% error rate. Genuine accept rate at 1% false accept rate is 89.3% but at 0.1% value it is 96.7%, which is higher. The outcome of this study suggests that the proposed methodology has a low error rate with minimum computational effort as compared with existing methods such as Lee's method and 2D DP and the combined method.

Fingerprint Matching by Thin-plate Spline Modelling of Elastic Deformations

NARCIS (Netherlands)

Bazen, A.M.; Gerez, Sabih H.

2003-01-01

This paper presents a novel minutiae matching method that describes elastic distortions in fingerprints by means of a thin-plate spline model, which is estimated using a local and a global matching stage. After registration of the fingerprints according to the estimated model, the number of matching

AIR-MRF: Accelerated iterative reconstruction for magnetic resonance fingerprinting.

Science.gov (United States)

Cline, Christopher C; Chen, Xiao; Mailhe, Boris; Wang, Qiu; Pfeuffer, Josef; Nittka, Mathias; Griswold, Mark A; Speier, Peter; Nadar, Mariappan S

2017-09-01

Existing approaches for reconstruction of multiparametric maps with magnetic resonance fingerprinting (MRF) are currently limited by their estimation accuracy and reconstruction time. We aimed to address these issues with a novel combination of iterative reconstruction, fingerprint compression, additional regularization, and accelerated dictionary search methods. The pipeline described here, accelerated iterative reconstruction for magnetic resonance fingerprinting (AIR-MRF), was evaluated with simulations as well as phantom and in vivo scans. We found that the AIR-MRF pipeline provided reduced parameter estimation errors compared to non-iterative and other iterative methods, particularly at shorter sequence lengths. Accelerated dictionary search methods incorporated into the iterative pipeline reduced the reconstruction time at little cost of quality. Copyright © 2017 Elsevier Inc. All rights reserved.

Real-Time Multiview Recognition of Human Gestures by Distributed Image Processing

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Sato Kosuke

2010-01-01

Full Text Available Since a gesture involves a dynamic and complex motion, multiview observation and recognition are desirable. For the better representation of gestures, one needs to know, in the first place, from which views a gesture should be observed. Furthermore, it becomes increasingly important how the recognition results are integrated when larger numbers of camera views are considered. To investigate these problems, we propose a framework under which multiview recognition is carried out, and an integration scheme by which the recognition results are integrated online and in realtime. For performance evaluation, we use the ViHASi (Virtual Human Action Silhouette public image database as a benchmark and our Japanese sign language (JSL image database that contains 18 kinds of hand signs. By examining the recognition rates of each gesture for each view, we found gestures that exhibit view dependency and the gestures that do not. Also, we found that the view dependency itself could vary depending on the target gesture sets. By integrating the recognition results of different views, our swarm-based integration provides more robust and better recognition performance than individual fixed-view recognition agents.

Stereoselective virtual screening of the ZINC database using atom pair 3D-fingerprints.

Science.gov (United States)

Awale, Mahendra; Jin, Xian; Reymond, Jean-Louis

2015-01-01

Tools to explore large compound databases in search for analogs of query molecules provide a strategically important support in drug discovery to help identify available analogs of any given reference or hit compound by ligand based virtual screening (LBVS). We recently showed that large databases can be formatted for very fast searching with various 2D-fingerprints using the city-block distance as similarity measure, in particular a 2D-atom pair fingerprint (APfp) and the related category extended atom pair fingerprint (Xfp) which efficiently encode molecular shape and pharmacophores, but do not perceive stereochemistry. Here we investigated related 3D-atom pair fingerprints to enable rapid stereoselective searches in the ZINC database (23.2 million 3D structures). Molecular fingerprints counting atom pairs at increasing through-space distance intervals were designed using either all atoms (16-bit 3DAPfp) or different atom categories (80-bit 3DXfp). These 3D-fingerprints retrieved molecular shape and pharmacophore analogs (defined by OpenEye ROCS scoring functions) of 110,000 compounds from the Cambridge Structural Database with equal or better accuracy than the 2D-fingerprints APfp and Xfp, and showed comparable performance in recovering actives from decoys in the DUD database. LBVS by 3DXfp or 3DAPfp similarity was stereoselective and gave very different analogs when starting from different diastereomers of the same chiral drug. Results were also different from LBVS with the parent 2D-fingerprints Xfp or APfp. 3D- and 2D-fingerprints also gave very different results in LBVS of folded molecules where through-space distances between atom pairs are much shorter than topological distances. 3DAPfp and 3DXfp are suitable for stereoselective searches for shape and pharmacophore analogs of query molecules in large databases. Web-browsers for searching ZINC by 3DAPfp and 3DXfp similarity are accessible at www.gdb.unibe.ch and should provide useful assistance to drug

Binary similarity measures for fingerprint analysis of qualitative metabolomic profiles.

Science.gov (United States)

Rácz, Anita; Andrić, Filip; Bajusz, Dávid; Héberger, Károly

2018-01-01

Contemporary metabolomic fingerprinting is based on multiple spectrometric and chromatographic signals, used either alone or combined with structural and chemical information of metabolic markers at the qualitative and semiquantitative level. However, signal shifting, convolution, and matrix effects may compromise metabolomic patterns. Recent increase in the use of qualitative metabolomic data, described by the presence (1) or absence (0) of particular metabolites, demonstrates great potential in the field of metabolomic profiling and fingerprint analysis. The aim of this study is a comprehensive evaluation of binary similarity measures for the elucidation of patterns among samples of different botanical origin and various metabolomic profiles. Nine qualitative metabolomic data sets covering a wide range of natural products and metabolomic profiles were applied to assess 44 binary similarity measures for the fingerprinting of plant extracts and natural products. The measures were analyzed by the novel sum of ranking differences method (SRD), searching for the most promising candidates. Baroni-Urbani-Buser (BUB) and Hawkins-Dotson (HD) similarity coefficients were selected as the best measures by SRD and analysis of variance (ANOVA), while Dice (Di1), Yule, Russel-Rao, and Consonni-Todeschini 3 ranked the worst. ANOVA revealed that concordantly and intermediately symmetric similarity coefficients are better candidates for metabolomic fingerprinting than the asymmetric and correlation based ones. The fingerprint analysis based on the BUB and HD coefficients and qualitative metabolomic data performed equally well as the quantitative metabolomic profile analysis. Fingerprint analysis based on the qualitative metabolomic profiles and binary similarity measures proved to be a reliable way in finding the same/similar patterns in metabolomic data as that extracted from quantitative data.

Fingerprint-based structure retrieval using electron density.

Science.gov (United States)

Yin, Shuangye; Dokholyan, Nikolay V

2011-03-01

We present a computational approach that can quickly search a large protein structural database to identify structures that fit a given electron density, such as determined by cryo-electron microscopy. We use geometric invariants (fingerprints) constructed using 3D Zernike moments to describe the electron density, and reduce the problem of fitting of the structure to the electron density to simple fingerprint comparison. Using this approach, we are able to screen the entire Protein Data Bank and identify structures that fit two experimental electron densities determined by cryo-electron microscopy. Copyright © 2010 Wiley-Liss, Inc.

Fingerprint extraction from interference destruction terahertz spectrum.

Science.gov (United States)

Xiong, Wei; Shen, Jingling

2010-10-11

In this paper, periodic peaks in a terahertz absorption spectrum are confirmed to be induced from interference effects. Theoretically, we explained the periodic peaks and calculated the locations of them. Accordingly, a technique was suggested, with which the interference peaks in a terahertz spectrum can be eliminated and therefore a real terahertz absorption spectrum can be obtained. Experimentally, a sample, Methamphetamine, was investigated and its terahertz fingerprint was successfully extracted from its interference destruction spectrum. This technique is useful in getting samples' terahertz fingerprint spectra, and furthermore provides a fast nondestructive testing method using a large size terahertz beam to identify materials.

Algorithm comparison for schedule optimization in MR fingerprinting.

Science.gov (United States)

Cohen, Ouri; Rosen, Matthew S

2017-09-01

In MR Fingerprinting, the flip angles and repetition times are chosen according to a pseudorandom schedule. In previous work, we have shown that maximizing the discrimination between different tissue types by optimizing the acquisition schedule allows reductions in the number of measurements required. The ideal optimization algorithm for this application remains unknown, however. In this work we examine several different optimization algorithms to determine the one best suited for optimizing MR Fingerprinting acquisition schedules. Copyright © 2017 Elsevier Inc. All rights reserved.

Chemical Fingerprint Analysis and Quantitative Analysis of Rosa rugosa by UPLC-DAD

Directory of Open Access Journals (Sweden)

Sanawar Mansur

2016-12-01

Full Text Available A method based on ultra performance liquid chromatography with a diode array detector (UPLC-DAD was developed for quantitative analysis of five active compounds and chemical fingerprint analysis of Rosa rugosa. Ten batches of R. rugosa collected from different plantations in the Xinjiang region of China were used to establish the fingerprint. The feasibility and advantages of the used UPLC fingerprint were verified for its similarity evaluation by systematically comparing chromatograms with professional analytical software recommended by State Food and Drug Administration (SFDA of China. In quantitative analysis, the five compounds showed good regression (R2 = 0.9995 within the test ranges, and the recovery of the method was in the range of 94.2%–103.8%. The similarities of liquid chromatography fingerprints of 10 batches of R. rugosa were more than 0.981. The developed UPLC fingerprint method is simple, reliable, and validated for the quality control and identification of R. rugosa. Additionally, simultaneous quantification of five major bioactive ingredients in the R. rugosa samples was conducted to interpret the consistency of the quality test. The results indicated that the UPLC fingerprint, as a characteristic distinguishing method combining similarity evaluation and quantification analysis, can be successfully used to assess the quality and to identify the authenticity of R. rugosa.

Security enhanced multi-factor biometric authentication scheme using bio-hash function.

Directory of Open Access Journals (Sweden)

Younsung Choi

Full Text Available With the rapid development of personal information and wireless communication technology, user authentication schemes have been crucial to ensure that wireless communications are secure. As such, various authentication schemes with multi-factor authentication have been proposed to improve the security of electronic communications. Multi-factor authentication involves the use of passwords, smart cards, and various biometrics to provide users with the utmost privacy and data protection. Cao and Ge analyzed various authentication schemes and found that Younghwa An's scheme was susceptible to a replay attack where an adversary masquerades as a legal server and a user masquerading attack where user anonymity is not provided, allowing an adversary to execute a password change process by intercepting the user's ID during login. Cao and Ge improved upon Younghwa An's scheme, but various security problems remained. This study demonstrates that Cao and Ge's scheme is susceptible to a biometric recognition error, slow wrong password detection, off-line password attack, user impersonation attack, ID guessing attack, a DoS attack, and that their scheme cannot provide session key agreement. Then, to address all weaknesses identified in Cao and Ge's scheme, this study proposes a security enhanced multi-factor biometric authentication scheme and provides a security analysis and formal analysis using Burrows-Abadi-Needham logic. Finally, the efficiency analysis reveals that the proposed scheme can protect against several possible types of attacks with only a slightly high computational cost.

Security enhanced multi-factor biometric authentication scheme using bio-hash function.

Science.gov (United States)

Choi, Younsung; Lee, Youngsook; Moon, Jongho; Won, Dongho

2017-01-01

With the rapid development of personal information and wireless communication technology, user authentication schemes have been crucial to ensure that wireless communications are secure. As such, various authentication schemes with multi-factor authentication have been proposed to improve the security of electronic communications. Multi-factor authentication involves the use of passwords, smart cards, and various biometrics to provide users with the utmost privacy and data protection. Cao and Ge analyzed various authentication schemes and found that Younghwa An's scheme was susceptible to a replay attack where an adversary masquerades as a legal server and a user masquerading attack where user anonymity is not provided, allowing an adversary to execute a password change process by intercepting the user's ID during login. Cao and Ge improved upon Younghwa An's scheme, but various security problems remained. This study demonstrates that Cao and Ge's scheme is susceptible to a biometric recognition error, slow wrong password detection, off-line password attack, user impersonation attack, ID guessing attack, a DoS attack, and that their scheme cannot provide session key agreement. Then, to address all weaknesses identified in Cao and Ge's scheme, this study proposes a security enhanced multi-factor biometric authentication scheme and provides a security analysis and formal analysis using Burrows-Abadi-Needham logic. Finally, the efficiency analysis reveals that the proposed scheme can protect against several possible types of attacks with only a slightly high computational cost.

Security enhanced multi-factor biometric authentication scheme using bio-hash function

Science.gov (United States)

Lee, Youngsook; Moon, Jongho

2017-01-01

With the rapid development of personal information and wireless communication technology, user authentication schemes have been crucial to ensure that wireless communications are secure. As such, various authentication schemes with multi-factor authentication have been proposed to improve the security of electronic communications. Multi-factor authentication involves the use of passwords, smart cards, and various biometrics to provide users with the utmost privacy and data protection. Cao and Ge analyzed various authentication schemes and found that Younghwa An’s scheme was susceptible to a replay attack where an adversary masquerades as a legal server and a user masquerading attack where user anonymity is not provided, allowing an adversary to execute a password change process by intercepting the user’s ID during login. Cao and Ge improved upon Younghwa An’s scheme, but various security problems remained. This study demonstrates that Cao and Ge’s scheme is susceptible to a biometric recognition error, slow wrong password detection, off-line password attack, user impersonation attack, ID guessing attack, a DoS attack, and that their scheme cannot provide session key agreement. Then, to address all weaknesses identified in Cao and Ge’s scheme, this study proposes a security enhanced multi-factor biometric authentication scheme and provides a security analysis and formal analysis using Burrows-Abadi-Needham logic. Finally, the efficiency analysis reveals that the proposed scheme can protect against several possible types of attacks with only a slightly high computational cost. PMID:28459867

Beware of the possibility of fingerprinting techniques transferring DNA.

Science.gov (United States)

van Oorschot, Roland A H; Treadwell, Sally; Beaurepaire, James; Holding, Nicole L; Mitchell, Robert J

2005-11-01

Fingerprinting brushes have the potential to collect and transfer DNA during powdering. Squirrel-hair fingerprint brushes exposed to specific sets of saliva stains and brushes used in routine casework were tested for their ability to collect and transfer DNA containing material using standard DNA extraction procedures and AmpFlSTR Profiler Plus amplification and typing procedures. The tests found that the risk of transferring DNA during powdering and having a detrimental impact on the analysis increases if the examiner powders over either biological stains (such as blood or saliva) or very fresh prints and uses more sensitive PCR amplification and typing procedures. We advocate caution when powdering prints from which DNA may also be collected and provide options for consideration to limit the risk of transferred DNA contamination while fingerprinting.

A STRONG SECURITY PROTOCOL AGAINST FINGERPRINT DATABASE ATTACKS

Directory of Open Access Journals (Sweden)

U. Latha

2013-08-01

Full Text Available The Biometric data is subject to on-going changes and create a crucial problem in fingerprint database. To deal with this, a security protocol is proposed to protect the finger prints information from the prohibited users. Here, a security protocol is proposed to protect the finger prints information. The proposed system comprised of three phases namely, fingerprint reconstruction, feature extraction and development of trigon based security protocol. In fingerprint reconstruction, the different crack variance level finger prints images are reconstructed by the M-band Dual Tree Complex Wavelet Transform (DTCWT. After that features are extracted by binarization. A set of finger print images are utilized to evaluate the performance of security protocol and the result from this process guarantees the healthiness of the proposed trigon based security protocol. The implementation results show the effectiveness of proposed trigon based security protocol in protecting the finger print information and the achieved improvement in image reconstruction and the security process.

Wavelet/scalar quantization compression standard for fingerprint images

Energy Technology Data Exchange (ETDEWEB)

Brislawn, C.M.

1996-06-12

US Federal Bureau of Investigation (FBI) has recently formulated a national standard for digitization and compression of gray-scale fingerprint images. Fingerprints are scanned at a spatial resolution of 500 dots per inch, with 8 bits of gray-scale resolution. The compression algorithm for the resulting digital images is based on adaptive uniform scalar quantization of a discrete wavelet transform subband decomposition (wavelet/scalar quantization method). The FBI standard produces archival-quality images at compression ratios of around 15 to 1 and will allow the current database of paper fingerprint cards to be replaced by digital imagery. The compression standard specifies a class of potential encoders and a universal decoder with sufficient generality to reconstruct compressed images produced by any compliant encoder, allowing flexibility for future improvements in encoder technology. A compliance testing program is also being implemented to ensure high standards of image quality and interchangeability of data between different implementations.

Complexity and distortion analysis on methods for unrolling 3D to 2D fingerprints

CSIR Research Space (South Africa)

Mlambo, CS

2015-11-01

Full Text Available and studies involve the application of three-dimensional (3D) fingerprint systems, where the details of the finger are captured using 3D technologies and the captured 3D fingerprints are converted into two-dimensional (2D) fingerprints. This paper presents a...

Deep Learning-Based Iris Segmentation for Iris Recognition in Visible Light Environment

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Muhammad Arsalan

2017-11-01

Full Text Available Existing iris recognition systems are heavily dependent on specific conditions, such as the distance of image acquisition and the stop-and-stare environment, which require significant user cooperation. In environments where user cooperation is not guaranteed, prevailing segmentation schemes of the iris region are confronted with many problems, such as heavy occlusion of eyelashes, invalid off-axis rotations, motion blurs, and non-regular reflections in the eye area. In addition, iris recognition based on visible light environment has been investigated to avoid the use of additional near-infrared (NIR light camera and NIR illuminator, which increased the difficulty of segmenting the iris region accurately owing to the environmental noise of visible light. To address these issues; this study proposes a two-stage iris segmentation scheme based on convolutional neural network (CNN; which is capable of accurate iris segmentation in severely noisy environments of iris recognition by visible light camera sensor. In the experiment; the noisy iris challenge evaluation part-II (NICE-II training database (selected from the UBIRIS.v2 database and mobile iris challenge evaluation (MICHE dataset were used. Experimental results showed that our method outperformed the existing segmentation methods.

High-speed biometrics ultrasonic system for 3D fingerprint imaging

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Maev, Roman G.; Severin, Fedar

2012-10-01

The objective of this research is to develop a new robust fingerprint identification technology based upon forming surface-subsurface (under skin) ultrasonic 3D images of the finger pads. The presented work aims to create specialized ultrasonic scanning methods for biometric purposes. Preliminary research has demonstrated the applicability of acoustic microscopy for fingerprint reading. The additional information from internal skin layers and dermis structures contained in the scan can essentially improve confidence in the identification. Advantages of this system include high resolution and quick scanning time. Operating in pulse-echo mode provides spatial resolution up to 0.05 mm. Technology advantages of the proposed technology are the following: • Full-range scanning of the fingerprint area "nail to nail" (2.5 x 2.5 cm) can be done in less than 5 sec with a resolution of up to 1000 dpi. • Collection of information about the in-depth structure of the fingerprint realized by the set of spherically focused 50 MHz acoustic lens provide the resolution ~ 0.05 mm or better • In addition to fingerprints, this technology can identify sweat porous at the surface and under the skin • No sensitivity to the contamination of the finger's surface • Detection of blood velocity using Doppler effect can be implemented to distinguish living specimens • Utilization as polygraph device • Simple connectivity to fingerprint databases obtained with other techniques • The digitally interpolated images can then be enhanced allowing for greater resolution • Method can be applied to fingernails and underlying tissues, providing more information • A laboratory prototype of the biometrics system based on these described principles was designed, built and tested. It is the first step toward a practical implementation of this technique.

Forensic Discrimination of Latent Fingerprints Using Laser-Induced Breakdown Spectroscopy (LIBS) and Chemometric Approaches.

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Yang, Jun-Ho; Yoh, Jack J

2018-01-01

A novel technique is reported for separating overlapping latent fingerprints using chemometric approaches that combine laser-induced breakdown spectroscopy (LIBS) and multivariate analysis. The LIBS technique provides the capability of real time analysis and high frequency scanning as well as the data regarding the chemical composition of overlapping latent fingerprints. These spectra offer valuable information for the classification and reconstruction of overlapping latent fingerprints by implementing appropriate statistical multivariate analysis. The current study employs principal component analysis and partial least square methods for the classification of latent fingerprints from the LIBS spectra. This technique was successfully demonstrated through a classification study of four distinct latent fingerprints using classification methods such as soft independent modeling of class analogy (SIMCA) and partial least squares discriminant analysis (PLS-DA). The novel method yielded an accuracy of more than 85% and was proven to be sufficiently robust. Furthermore, through laser scanning analysis at a spatial interval of 125 µm, the overlapping fingerprints were reconstructed as separate two-dimensional forms.

Analysis of fingerprint samples, testing various conditions, for forensic DNA identification.

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Ostojic, Lana; Wurmbach, Elisa

2017-01-01

Fingerprints can be of tremendous value for forensic biology, since they can be collected from a wide variety of evident types, such as handles of weapons, tools collected in criminal cases, and objects with no apparent staining. DNA obtained from fingerprints varies greatly in quality and quantity, which ultimately affects the quality of the resulting STR profiles. Additional difficulties can arise when fingerprint samples show mixed STR profiles due to the handling of multiple persons. After applying a tested protocol for sample collection (swabbing with 5% Triton X-100), DNA extraction (using an enzyme that works at elevated temperatures), and PCR amplification (AmpFlSTR® Identifiler® using 31cycles) extensive analysis was performed to better understand the challenges inherent to fingerprint samples, with the ultimate goal of developing valuable profiles (≥50% complete). The impact of time on deposited fingerprints was investigated, revealing that while the quality of profiles deteriorated, full STR profiles could still be obtained from samples after 40days of storage at room temperature. By comparing the STR profiles from fingerprints of the dominant versus the non-dominant hand, we found a slightly better quality from the non-dominant hand, which was not always significant. Substrates seem to have greater effects on fingerprints. Tests on glass, plastic, paper and metal (US Quarter dollar, made of Cu and Ni), common substrates in offices and homes, showed best results for glass, followed by plastic and paper, while almost no profiles were obtained from a Quarter dollar. Important for forensic casework, we also assessed three-person mixtures of touched fingerprint samples. Unlike routinely used approaches for sampling evidence, the surface of an object (bottle) was sectioned into six equal parts and separate samples were taken from each section. The samples were processed separately for DNA extraction and STR amplification. The results included a few single

Quality based approach for adaptive face recognition

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Abboud, Ali J.; Sellahewa, Harin; Jassim, Sabah A.

2009-05-01

Recent advances in biometric technology have pushed towards more robust and reliable systems. We aim to build systems that have low recognition errors and are less affected by variation in recording conditions. Recognition errors are often attributed to the usage of low quality biometric samples. Hence, there is a need to develop new intelligent techniques and strategies to automatically measure/quantify the quality of biometric image samples and if necessary restore image quality according to the need of the intended application. In this paper, we present no-reference image quality measures in the spatial domain that have impact on face recognition. The first is called symmetrical adaptive local quality index (SALQI) and the second is called middle halve (MH). Also, an adaptive strategy has been developed to select the best way to restore the image quality, called symmetrical adaptive histogram equalization (SAHE). The main benefits of using quality measures for adaptive strategy are: (1) avoidance of excessive unnecessary enhancement procedures that may cause undesired artifacts, and (2) reduced computational complexity which is essential for real time applications. We test the success of the proposed measures and adaptive approach for a wavelet-based face recognition system that uses the nearest neighborhood classifier. We shall demonstrate noticeable improvements in the performance of adaptive face recognition system over the corresponding non-adaptive scheme.

A BAC clone fingerprinting approach to the detection of human genome rearrangements

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Krzywinski, Martin; Bosdet, Ian; Mathewson, Carrie; Wye, Natasja; Brebner, Jay; Chiu, Readman; Corbett, Richard; Field, Matthew; Lee, Darlene; Pugh, Trevor; Volik, Stas; Siddiqui, Asim; Jones, Steven; Schein, Jacquie; Collins, Collin; Marra, Marco

2007-01-01

We present a method, called fingerprint profiling (FPP), that uses restriction digest fingerprints of bacterial artificial chromosome clones to detect and classify rearrangements in the human genome. The approach uses alignment of experimental fingerprint patterns to in silico digests of the sequence assembly and is capable of detecting micro-deletions (1-5 kb) and balanced rearrangements. Our method has compelling potential for use as a whole-genome method for the identification and characterization of human genome rearrangements. PMID:17953769

[Identification of a repetitive sequence element for DNA fingerprinting in Phytophthora sojae].

Science.gov (United States)

Yin, Lihua; Wang, Qinhu; Ning, Feng; Zhu, Xiaoying; Zuo, Yuhu; Shan, Weixing

2010-04-01

Establishment of DNA fingerprinting in Phytophthora sojae and an analysis of genetic relationship of Heilongjiang and Xinjiang populations. Bioinformatics tools were used to search repetitive sequences in P. sojae and Southern blot analysis was employed for DNA fingerprinting analysis of P. sojae populations from Heilongjiang and Xinjiang using the identified repetitive sequence. A moderately repetitive sequence was identified and designated as PS1227. Southern blot analysis indicated 34 distinct bands ranging in size from 1.5 kb-23 kb, of which 21 were polymorphic among 49 isolates examined. Analysis of single-zoospore progenies showed that the PS1227 fingerprint pattern was mitotically stable. DNA fingerprinting showed that the P. sojae isolates HP4002, SY6 and GJ0105 of Heilongjiang are genetically identical to DW303, 71228 and 71222 of Xinjiang, respectively. A moderately repetitive sequence designated PS1227 which will be useful for epidemiology and population biology studies of P. sojae was obtained, and a PS1227-based DNA fingerprinting analysis provided molecular evidence that P. sojae in Xinjiang was likely introduced from Heilongjiang.

Cloning and Characterization of a Complex DNA Fingerprinting Probe for Candida parapsilosis

Science.gov (United States)

Enger, Lee; Joly, Sophie; Pujol, Claude; Simonson, Patricia; Pfaller, Michael; Soll, David R.

2001-01-01

Candida parapsilosis accounts for a significant number of nosocomial fungemias, but in fact, no effective and verified genetic fingerprinting method has emerged for assessing the relatedness of independent isolates for epidemiological studies. A complex 15-kb DNA fingerprinting probe, Cp3-13, was therefore isolated from a library of C. parapsilosis genomic DNA fragments. The efficacy of Cp3-13 for DNA fingerprinting was verified by a comparison of its clustering capacity with those of randomly amplified polymorphic DNA analysis and internally transcribed spacer region sequencing, by testing species specificity, and by assessing its capacity to identify microevolutionary changes both in vitro and in vivo. Southern blot hybridization of EcoRI/SalI-digested DNA with Cp3-13 provides a fingerprinting system that (i) identifies the same strain in independent isolates, (ii) discriminates between unrelated isolates, (iii) separates independent isolates into valid groups in a dendrogram, (iv) identifies microevolution in infecting populations, and (v) is amenable to automatic computer-assisted DNA fingerprint analysis. This probe is now available for epidemiological studies. PMID:11158125

Examination of Speed Contribution of Parallelization for Several Fingerprint Pre-Processing Algorithms

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GORGUNOGLU, S.

2014-05-01

Full Text Available In analysis of minutiae based fingerprint systems, fingerprints needs to be pre-processed. The pre-processing is carried out to enhance the quality of the fingerprint and to obtain more accurate minutiae points. Reducing the pre-processing time is important for identification and verification in real time systems and especially for databases holding large fingerprints information. Parallel processing and parallel CPU computing can be considered as distribution of processes over multi core processor. This is done by using parallel programming techniques. Reducing the execution time is the main objective in parallel processing. In this study, pre-processing of minutiae based fingerprint system is implemented by parallel processing on multi core computers using OpenMP and on graphics processor using CUDA to improve execution time. The execution times and speedup ratios are compared with the one that of single core processor. The results show that by using parallel processing, execution time is substantially improved. The improvement ratios obtained for different pre-processing algorithms allowed us to make suggestions on the more suitable approaches for parallelization.

Fingerprint image enhancement by differential hysteresis processing.

Science.gov (United States)

Blotta, Eduardo; Moler, Emilce

2004-05-10

A new method to enhance defective fingerprints images through image digital processing tools is presented in this work. When the fingerprints have been taken without any care, blurred and in some cases mostly illegible, as in the case presented here, their classification and comparison becomes nearly impossible. A combination of spatial domain filters, including a technique called differential hysteresis processing (DHP), is applied to improve these kind of images. This set of filtering methods proved to be satisfactory in a wide range of cases by uncovering hidden details that helped to identify persons. Dactyloscopy experts from Policia Federal Argentina and the EAAF have validated these results.

Improvement Schemes for Indoor Mobile Location Estimation: A Survey

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Jianga Shang

2015-01-01

Full Text Available Location estimation is significant in mobile and ubiquitous computing systems. The complexity and smaller scale of the indoor environment impose a great impact on location estimation. The key of location estimation lies in the representation and fusion of uncertain information from multiple sources. The improvement of location estimation is a complicated and comprehensive issue. A lot of research has been done to address this issue. However, existing research typically focuses on certain aspects of the problem and specific methods. This paper reviews mainstream schemes on improving indoor location estimation from multiple levels and perspectives by combining existing works and our own working experiences. Initially, we analyze the error sources of common indoor localization techniques and provide a multilayered conceptual framework of improvement schemes for location estimation. This is followed by a discussion of probabilistic methods for location estimation, including Bayes filters, Kalman filters, extended Kalman filters, sigma-point Kalman filters, particle filters, and hidden Markov models. Then, we investigate the hybrid localization methods, including multimodal fingerprinting, triangulation fusing multiple measurements, combination of wireless positioning with pedestrian dead reckoning (PDR, and cooperative localization. Next, we focus on the location determination approaches that fuse spatial contexts, namely, map matching, landmark fusion, and spatial model-aided methods. Finally, we present the directions for future research.

Visual Recognition and Its Application to Robot Arm Control

Directory of Open Access Journals (Sweden)

Jih-Gau Juang

2015-10-01

Full Text Available This paper presents an application of optical word recognition and fuzzy control to a smartphone automatic test system. The system consists of a robot arm and two webcams. After the words from the control panel that represent commands are recognized by the robot system, the robot arm performs the corresponding actions to test the smartphone. One of the webcams is utilized to capture commands on the screen of the control panel, the other to recognize the words on the screen of the tested smartphone. The method of image processing is based on the Red-Green-Blue (RGB and Hue-Saturation-Luminance (HSL color spaces to reduce the influence of light. Fuzzy theory is used in the robot arm’s position control. The Optical Character Recognition (OCR technique is applied to the word recognition, and the recognition results are then checked by a dictionary process to increase the recognition accuracy. The camera which is used to recognize the tested smartphone also provides object coordinates to the fuzzy controller, then the robot arm moves to the desired positions and presses the desired buttons. The proposed control scheme allows the robot arm to perform different assigned test functions successfully.

Development and assessment of microarray-based DNA fingerprinting in Eucalyptus grandis.

Science.gov (United States)

Lezar, Sabine; Myburg, A A; Berger, D K; Wingfield, M J; Wingfield, B D

2004-11-01

Development of improved Eucalyptus genotypes involves the routine identification of breeding stock and superior clones. Currently, microsatellites and random amplified polymorphic DNA markers are the most widely used DNA-based techniques for fingerprinting of these trees. While these techniques have provided rapid and powerful fingerprinting assays, they are constrained by their reliance on gel or capillary electrophoresis, and therefore, relatively low throughput of fragment analysis. In contrast, recently developed microarray technology holds the promise of parallel analysis of thousands of markers in plant genomes. The aim of this study was to develop a DNA fingerprinting chip for Eucalyptus grandis and to investigate its usefulness for fingerprinting of eucalypt trees. A prototype chip was prepared using a partial genomic library from total genomic DNA of 23 E. grandis trees, of which 22 were full siblings. A total of 384 cloned genomic fragments were individually amplified and arrayed onto glass slides. DNA fingerprints were obtained for 17 individuals by hybridizing labeled genome representations of the individual trees to the 384-element chip. Polymorphic DNA fragments were identified by evaluating the binary distribution of their background-corrected signal intensities across full-sib individuals. Among 384 DNA fragments on the chip, 104 (27%) were found to be polymorphic. Hybridization of these polymorphic fragments was highly repeatable (R2>0.91) within the E. grandis individuals, and they allowed us to identify all 17 full-sib individuals. Our results suggest that DNA microarrays can be used to effectively fingerprint large numbers of closely related Eucalyptus trees.

Fringe patterns generated by micro-optical sensors for pattern recognition.

Science.gov (United States)

Tamee, Kreangsak; Chaiwong, Khomyuth; Yothapakdee, Kriengsak; Yupapin, Preecha P

2015-01-01

We present a new result of pattern recognition generation scheme using a small-scale optical muscle sensing system, which consisted of an optical add-drop filter incorporating two nonlinear optical side ring resonators. When light from laser source enters into the system, the device is stimulated by an external physical parameter that introduces a change in the phase of light propagation within the sensing device, which can be formed by the interference fringe patterns. Results obtained have shown that the fringe patterns can be used to form the relationship between signal patterns and fringe pattern recognitions.

Carotenoids Database: structures, chemical fingerprints and distribution among organisms.

Science.gov (United States)

Yabuzaki, Junko

2017-01-01

To promote understanding of how organisms are related via carotenoids, either evolutionarily or symbiotically, or in food chains through natural histories, we built the Carotenoids Database. This provides chemical information on 1117 natural carotenoids with 683 source organisms. For extracting organisms closely related through the biosynthesis of carotenoids, we offer a new similarity search system 'Search similar carotenoids' using our original chemical fingerprint 'Carotenoid DB Chemical Fingerprints'. These Carotenoid DB Chemical Fingerprints describe the chemical substructure and the modification details based upon International Union of Pure and Applied Chemistry (IUPAC) semi-systematic names of the carotenoids. The fingerprints also allow (i) easier prediction of six biological functions of carotenoids: provitamin A, membrane stabilizers, odorous substances, allelochemicals, antiproliferative activity and reverse MDR activity against cancer cells, (ii) easier classification of carotenoid structures, (iii) partial and exact structure searching and (iv) easier extraction of structural isomers and stereoisomers. We believe this to be the first attempt to establish fingerprints using the IUPAC semi-systematic names. For extracting close profiled organisms, we provide a new tool 'Search similar profiled organisms'. Our current statistics show some insights into natural history: carotenoids seem to have been spread largely by bacteria, as they produce C30, C40, C45 and C50 carotenoids, with the widest range of end groups, and they share a small portion of C40 carotenoids with eukaryotes. Archaea share an even smaller portion with eukaryotes. Eukaryotes then have evolved a considerable variety of C40 carotenoids. Considering carotenoids, eukaryotes seem more closely related to bacteria than to archaea aside from 16S rRNA lineage analysis. : http://carotenoiddb.jp. © The Author(s) 2017. Published by Oxford University Press.

A simple low cost latent fingerprint sensor based on deflectometry and WFT analysis

Science.gov (United States)

Dhanotia, Jitendra; Chatterjee, Amit; Bhatia, Vimal; Prakash, Shashi

2018-02-01

In criminal investigations, latent fingerprints are one of the most significant forms of evidence and most commonly used forensic investigation tool worldwide. The existing non-contact latent fingerprint detection systems are bulky, expensive and require environment which is shock and vibration resistant, thereby limiting their usability outside the laboratory. In this article, a compact, full field, low cost technique for profiling of fingerprints using deflectometry is proposed. Using inexpensive mobile phone screen based structured illumination, and windowed Fourier transform (WFT) based phase retrieval mechanism, the 2D and 3D phase plots reconstruct the profile information of the fingerprint. The phase information is also used to confirm a match between two fingerprints in real time. Since the proposed technique is non-interferometric, the measurements are least affected by environmental perturbations. Using the proposed technique, a portable sensor capable of field deployment has been realized.

Image-based fingerprint verification system using LabVIEW

Directory of Open Access Journals (Sweden)

Sunil K. Singla

2008-09-01

Full Text Available Biometric-based identification/verification systems provide a solution to the security concerns in the modern world where machine is replacing human in every aspect of life. Fingerprints, because of their uniqueness, are the most widely used and highly accepted biometrics. Fingerprint biometric systems are either minutiae-based or pattern learning (image based. The minutiae-based algorithm depends upon the local discontinuities in the ridge flow pattern and are used when template size is important while image-based matching algorithm uses both the micro and macro feature of a fingerprint and is used if fast response is required. In the present paper an image-based fingerprint verification system is discussed. The proposed method uses a learning phase, which is not present in conventional image-based systems. The learning phase uses pseudo random sub-sampling, which reduces the number of comparisons needed in the matching stage. This system has been developed using LabVIEW (Laboratory Virtual Instrument Engineering Workbench toolbox version 6i. The availability of datalog files in LabVIEW makes it one of the most promising candidates for its usage as a database. Datalog files can access and manipulate data and complex data structures quickly and easily. It makes writing and reading much faster. After extensive experimentation involving a large number of samples and different learning sizes, high accuracy with learning image size of 100 100 and a threshold value of 700 (1000 being the perfect match has been achieved.

Generating One Biometric Feature from Another: Faces from Fingerprints

Directory of Open Access Journals (Sweden)

Seref Sagiroglu

2010-04-01

Full Text Available This study presents a new approach based on artificial neural networks for generating one biometric feature (faces from another (only fingerprints. An automatic and intelligent system was designed and developed to analyze the relationships among fingerprints and faces and also to model and to improve the existence of the relationships. The new proposed system is the first study that generates all parts of the face including eyebrows, eyes, nose, mouth, ears and face border from only fingerprints. It is also unique and different from similar studies recently presented in the literature with some superior features. The parameter settings of the system were achieved with the help of Taguchi experimental design technique. The performance and accuracy of the system have been evaluated with 10-fold cross validation technique using qualitative evaluation metrics in addition to the expanded quantitative evaluation metrics. Consequently, the results were presented on the basis of the combination of these objective and subjective metrics for illustrating the qualitative properties of the proposed methods as well as a quantitative evaluation of their performances. Experimental results have shown that one biometric feature can be determined from another. These results have once more indicated that there is a strong relationship between fingerprints and faces.

Laser mass spectrometry for DNA fingerprinting for forensic applications

Science.gov (United States)

Chen, C. H. Winston; Tang, Kai; Taranenko, N. I.; Allman, S. L.; Ch'ang, L. Y.

1994-10-01

The application of DNA fingerprinting has become very broad in forensic analysis, patient identification, diagnostic medicine, and wildlife poaching, since every individual's DNA structure is identical within all tissues oftheir body. DNA fingerprinting was initiated by the use of restriction fragment length polymorphisms (RFLP). In 1987, Nakamura et aL2 found that a variable number of tandem repeats (VNTR) often occurred in the alleles. The probability of different individuals having the same number of tandem repeats in several different alleles is very low. Thus, the identification of VNTR from genomic DNA became a very reliable method for identification of individuals. Take the Huntington gene as an example, there are CAG trinucleotide repeats. For normal people, the number of CAG repeats is usually between 10 and 40. Since people have chromosomes in pairs, the possibility oftwo individuals having the same VNTR in the Huntington gene is less than one percent, ifwe assume equal distribution for various repeats. When several allels containing VNTR are analyzed for the number of repeats, the possibility of two individuals being exactly identical becomes very unlikely. Thus, DNA fingerprinting is a reliable tool for forensic analysis. In DNA fingerprinting, knowledge of the sequence of tandem repeats and restriction endornuclease sites can provide the basis for identification.

Generating One Biometric Feature from Another: Faces from Fingerprints

Science.gov (United States)

Ozkaya, Necla; Sagiroglu, Seref

2010-01-01

This study presents a new approach based on artificial neural networks for generating one biometric feature (faces) from another (only fingerprints). An automatic and intelligent system was designed and developed to analyze the relationships among fingerprints and faces and also to model and to improve the existence of the relationships. The new proposed system is the first study that generates all parts of the face including eyebrows, eyes, nose, mouth, ears and face border from only fingerprints. It is also unique and different from similar studies recently presented in the literature with some superior features. The parameter settings of the system were achieved with the help of Taguchi experimental design technique. The performance and accuracy of the system have been evaluated with 10-fold cross validation technique using qualitative evaluation metrics in addition to the expanded quantitative evaluation metrics. Consequently, the results were presented on the basis of the combination of these objective and subjective metrics for illustrating the qualitative properties of the proposed methods as well as a quantitative evaluation of their performances. Experimental results have shown that one biometric feature can be determined from another. These results have once more indicated that there is a strong relationship between fingerprints and faces. PMID:22399877

Fingerprint pattern classification approach based on the coordinate geometry of singularities

CSIR Research Space (South Africa)

Msiza, IS

2009-10-01

Full Text Available of fingerprint matching, it serves to reduce the duration of the query. The fingerprint classes discussed in this document are the Central Twins (CT), Tented Arch (TA), Left Loop (LL), Right Loop (RL) and the Plain Arch (PA). The classification rules employed...

Sex differences in fingerprint ridge density in a Turkish young adult population: a sample of Baskent University.

Science.gov (United States)

Oktem, Hale; Kurkcuoglu, Ayla; Pelin, Ismail Can; Yazici, Ayse Canan; Aktaş, Gulnihal; Altunay, Fikret

2015-05-01

Fingerprints are considered to be one of the most reliable methods of identification. Identification of an individual plays a vital part of any medico-legal investigations. Dermatoglyphics is a branch of science that studies epidermal ridges and ridge patterns. Epidermal ridges are polygenic characteristics that form intrauterine 10-18 weeks and considered fully developed by the sixth month of fetal growth. Fingerprints are permanent morphological characteristics and criminal detection based on fingerprints is based on the principle that no two people can have identical fingerprints. Sex determination from fingerprints has been examined in different population. In this study we aimed to study fingerprint ridge density in Turkish population sample of Baskent University students. Fingerprints were obtained from 118 women, 88 men a total of 206 students aged between 17 and 28 years old by means of simple inking method. Fingerprints from all right and left hands fingers were collected in three different area of each. The ridges on fingerprints were counted diagonally on squares measuring 5 mm × 5 mm on radial, ulnar and inferior areas. The fingerprint ridge density in radial, ulnar and inferior areas and between sexes was compared statistically Mann Whitney U test and Friedman test. The ridge density was significantly greater in women in every region studied and in all fingers when compared to men. The fingerprint ridge density in the ulnar and radial areas of the fingerprints was significantly greater than the lower area. Fingerprint ridge density can be used by medico-legal examination for sex identification. Copyright © 2015 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

DWI-based neural fingerprinting technology: a preliminary study on stroke analysis.

Science.gov (United States)

Ye, Chenfei; Ma, Heather Ting; Wu, Jun; Yang, Pengfei; Chen, Xuhui; Yang, Zhengyi; Ma, Jingbo

2014-01-01

Stroke is a common neural disorder in neurology clinics. Magnetic resonance imaging (MRI) has become an important tool to assess the neural physiological changes under stroke, such as diffusion weighted imaging (DWI) and diffusion tensor imaging (DTI). Quantitative analysis of MRI images would help medical doctors to localize the stroke area in the diagnosis in terms of structural information and physiological characterization. However, current quantitative approaches can only provide localization of the disorder rather than measure physiological variation of subtypes of ischemic stroke. In the current study, we hypothesize that each kind of neural disorder would have its unique physiological characteristics, which could be reflected by DWI images on different gradients. Based on this hypothesis, a DWI-based neural fingerprinting technology was proposed to classify subtypes of ischemic stroke. The neural fingerprint was constructed by the signal intensity of the region of interest (ROI) on the DWI images under different gradients. The fingerprint derived from the manually drawn ROI could classify the subtypes with accuracy 100%. However, the classification accuracy was worse when using semiautomatic and automatic method in ROI segmentation. The preliminary results showed promising potential of DWI-based neural fingerprinting technology in stroke subtype classification. Further studies will be carried out for enhancing the fingerprinting accuracy and its application in other clinical practices.

Motif-role-fingerprints: the building-blocks of motifs, clustering-coefficients and transitivities in directed networks.

Directory of Open Access Journals (Sweden)

Mark D McDonnell

Full Text Available Complex networks are frequently characterized by metrics for which particular subgraphs are counted. One statistic from this category, which we refer to as motif-role fingerprints, differs from global subgraph counts in that the number of subgraphs in which each node participates is counted. As with global subgraph counts, it can be important to distinguish between motif-role fingerprints that are 'structural' (induced subgraphs and 'functional' (partial subgraphs. Here we show mathematically that a vector of all functional motif-role fingerprints can readily be obtained from an arbitrary directed adjacency matrix, and then converted to structural motif-role fingerprints by multiplying that vector by a specific invertible conversion matrix. This result demonstrates that a unique structural motif-role fingerprint exists for any given functional motif-role fingerprint. We demonstrate a similar result for the cases of functional and structural motif-fingerprints without node roles, and global subgraph counts that form the basis of standard motif analysis. We also explicitly highlight that motif-role fingerprints are elemental to several popular metrics for quantifying the subgraph structure of directed complex networks, including motif distributions, directed clustering coefficient, and transitivity. The relationships between each of these metrics and motif-role fingerprints also suggest new subtypes of directed clustering coefficients and transitivities. Our results have potential utility in analyzing directed synaptic networks constructed from neuronal connectome data, such as in terms of centrality. Other potential applications include anomaly detection in networks, identification of similar networks and identification of similar nodes within networks. Matlab code for calculating all stated metrics following calculation of functional motif-role fingerprints is provided as S1 Matlab File.

Challenges and Specifications for Robust Face and Gait Recognition Systems for Surveillance Application

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BUCIU Ioan

2014-05-01

Full Text Available Automated person recognition (APR based on biometric signals addresses the process of automatically recognize a person according to his physiological traits (face, voice, iris, fingerprint, ear shape, body odor, electroencephalogram – EEG, electrocardiogram, or hand geometry, or behavioural patterns (gait, signature, hand-grip, lip movement. The paper aims at briefly presenting the current challenges for two specific non-cooperative biometric approaches, namely face and gait biometrics as well as approaches that consider combination of the two in the attempt of a more robust system for accurate APR, in the context of surveillance application. Open problems from both sides are also pointed out.

Surveillance of a nuclear reactor core by use of a pattern recognition method

International Nuclear Information System (INIS)

Invernizzi, Michel.

1982-07-01

A pattern recognition system is described for the surveillance of a PWR reactor. This report contains four chapters. The first one succinctly deals with statistical pattern recognition principles. In the second chapter we show how a surveillance problem may be treated by pattern recognition and we present methods for surveillances (detection of abnormalities), controls (kind of running recognition) and diagnotics (kind of abnormality recognition). The third chapter shows a surveillance method of a nuclear plant. The signals used are the neutron noise observations made by the ionization chambers inserted in the reactor. Abnormality is defined in opposition with the training set witch is supposed to be an exhaustive summary of normality. In the fourth chapter we propose a scheme for an adaptative recognition and a method based on classes modelisations by hyper-spheres. This method has been tested on simulated training sets in two-dimensional feature spaces. It gives solutions to problems of non-linear separability [fr

Comparison of fingerprint and facial biometric verification technologies for user access and patient identification in a clinical environment

Science.gov (United States)

Guo, Bing; Zhang, Yu; Documet, Jorge; Liu, Brent; Lee, Jasper; Shrestha, Rasu; Wang, Kevin; Huang, H. K.

2007-03-01

As clinical imaging and informatics systems continue to integrate the healthcare enterprise, the need to prevent patient mis-identification and unauthorized access to clinical data becomes more apparent especially under the Health Insurance Portability and Accountability Act (HIPAA) mandate. Last year, we presented a system to track and verify patients and staff within a clinical environment. This year, we further address the biometric verification component in order to determine which Biometric system is the optimal solution for given applications in the complex clinical environment. We install two biometric identification systems including fingerprint and facial recognition systems at an outpatient imaging facility, Healthcare Consultation Center II (HCCII). We evaluated each solution and documented the advantages and pitfalls of each biometric technology in this clinical environment.

Soil-gas diffusivity fingerprints of the dual porosity system in fractured limestone

DEFF Research Database (Denmark)

Claes, Niels; Chamindu, D.T.K.K.; Jensen, Jacob Birk

2010-01-01

processes are mostly limited to hydrogeological (water and solute) transport studies with very poor attention to the gaseous phase transport studies (Kristensen et al. 2010). This study characterizes fractured limestone soils for gas diffusion based on three different gas diffusivity fingerprints. The first...... fingerprint is a two-parameter exponential model, which mainly describes the gas diffusivity in the limestone matrix while taking both fracture connectivity and matrix pore connectivity into account. With the second fingerprint, we make a close observation of the tortuous matrix pore network by means...... of a modified Buckingham (1904) pore connectivity factor (X*). The third fingerprint of the fracture network involves the average angle of diffusion α (Moldrup et al. 2010), a parameter which characterizes the average angle at which the fractures are penetrating the sample....

[Study on the fingerprint of Morus alba from different habitats by HPLC].

Science.gov (United States)

Chen, Cheng; Li, Hong-Bo; Wang, Liu-Ping; Li, Yun-Rong; Xin, Ning

2012-12-01

To establish HPLC fingerprint of Morus alba from different habitats by HPLC and provide basis for its quality control. HPLC analysis was performed on an Agilent XDB C18 Column (4.6 mm x 250 mm, 5 microm), gradient eluted composed of acetonitrile and 0.3% phosphate acid. The column temperature was set at 35 degrees C and the flow rate was 0.5 mL/min. The detective wavelength was 290 nm. The HPLC fingerprint for 10 batches of Morus alba was studied on their similarity. There were twelve common peaks in the fingerprint. The similarity of 7 batches was above 0.9 and the other batches had low similarity. The HPLC fingerprint can be used for quality control of Morus alba with high characteristics and specificity.

Chemical Visualization of Sweat Pores in Fingerprints Using GO-Enhanced TOF-SIMS.

Science.gov (United States)

Cai, Lesi; Xia, Meng-Chan; Wang, Zhaoying; Zhao, Ya-Bin; Li, Zhanping; Zhang, Sichun; Zhang, Xinrong

2017-08-15

Time-of-flight secondary ion mass spectrometry (TOF-SIMS) has been used in imaging of small molecules (SIMS was used to detect and image relatively high mass molecules such as poison, alkaloids (>600 Da) and controlled drugs, and antibiotics (>700 Da) in fingerprints. Detail features of fingerprints such as the number and distribution of sweat pores in a ridge and even the delicate morphology of one pore were clearly revealed in SIMS images of relatively high mass molecules. The detail features combining with identified chemical composition were sufficient to establish a human identity and link the suspect to a crime scene. The wide detectable mass range and high spatial resolution make GO-enhanced TOF-SIMS a promising tool in accurate and fast analysis of fingerprints, especially in fragmental fingerprint analysis.

Similarity analyses of chromatographic herbal fingerprints: A review

International Nuclear Information System (INIS)

Goodarzi, Mohammad; Russell, Paul J.; Vander Heyden, Yvan

2013-01-01

Graphical abstract: -- Highlights: •Similarity analyses of herbal fingerprints are reviewed. •Different (dis)similarity approaches are discussed. •(Dis)similarity-metrics and exploratory-analysis approaches are illustrated. •Correlation and distance-based measures are overviewed. •Similarity analyses illustrated by several case studies. -- Abstract: Herbal medicines are becoming again more popular in the developed countries because being “natural” and people thus often assume that they are inherently safe. Herbs have also been used worldwide for many centuries in the traditional medicines. The concern of their safety and efficacy has grown since increasing western interest. Herbal materials and their extracts are very complex, often including hundreds of compounds. A thorough understanding of their chemical composition is essential for conducting a safety risk assessment. However, herbal material can show considerable variability. The chemical constituents and their amounts in a herb can be different, due to growing conditions, such as climate and soil, the drying process, the harvest season, etc. Among the analytical methods, chromatographic fingerprinting has been recommended as a potential and reliable methodology for the identification and quality control of herbal medicines. Identification is needed to avoid fraud and adulteration. Currently, analyzing chromatographic herbal fingerprint data sets has become one of the most applied tools in quality assessment of herbal materials. Mostly, the entire chromatographic profiles are used to identify or to evaluate the quality of the herbs investigated. Occasionally only a limited number of compounds are considered. One approach to the safety risk assessment is to determine whether the herbal material is substantially equivalent to that which is either readily consumed in the diet, has a history of application or has earlier been commercialized i.e. to what is considered as reference material. In order

Similarity analyses of chromatographic herbal fingerprints: A review

Energy Technology Data Exchange (ETDEWEB)

Goodarzi, Mohammad [Department of Analytical Chemistry and Pharmaceutical Technology, Center for Pharmaceutical Research, Vrije Universiteit Brussel, Laarbeeklaan 103, B-1090 Brussels (Belgium); Russell, Paul J. [Safety and Environmental Assurance Centre, Unilever, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ (United Kingdom); Vander Heyden, Yvan, E-mail: yvanvdh@vub.ac.be [Department of Analytical Chemistry and Pharmaceutical Technology, Center for Pharmaceutical Research, Vrije Universiteit Brussel, Laarbeeklaan 103, B-1090 Brussels (Belgium)

2013-12-04

Graphical abstract: -- Highlights: •Similarity analyses of herbal fingerprints are reviewed. •Different (dis)similarity approaches are discussed. •(Dis)similarity-metrics and exploratory-analysis approaches are illustrated. •Correlation and distance-based measures are overviewed. •Similarity analyses illustrated by several case studies. -- Abstract: Herbal medicines are becoming again more popular in the developed countries because being “natural” and people thus often assume that they are inherently safe. Herbs have also been used worldwide for many centuries in the traditional medicines. The concern of their safety and efficacy has grown since increasing western interest. Herbal materials and their extracts are very complex, often including hundreds of compounds. A thorough understanding of their chemical composition is essential for conducting a safety risk assessment. However, herbal material can show considerable variability. The chemical constituents and their amounts in a herb can be different, due to growing conditions, such as climate and soil, the drying process, the harvest season, etc. Among the analytical methods, chromatographic fingerprinting has been recommended as a potential and reliable methodology for the identification and quality control of herbal medicines. Identification is needed to avoid fraud and adulteration. Currently, analyzing chromatographic herbal fingerprint data sets has become one of the most applied tools in quality assessment of herbal materials. Mostly, the entire chromatographic profiles are used to identify or to evaluate the quality of the herbs investigated. Occasionally only a limited number of compounds are considered. One approach to the safety risk assessment is to determine whether the herbal material is substantially equivalent to that which is either readily consumed in the diet, has a history of application or has earlier been commercialized i.e. to what is considered as reference material. In order

Use of pattern recognition for unaliasing simultaneously acquired slices in simultaneous multislice MR fingerprinting.

Science.gov (United States)

Jiang, Yun; Ma, Dan; Bhat, Himanshu; Ye, Huihui; Cauley, Stephen F; Wald, Lawrence L; Setsompop, Kawin; Griswold, Mark A

2017-11-01

The purpose of this study is to accelerate an MR fingerprinting (MRF) acquisition by using a simultaneous multislice method. A multiband radiofrequency (RF) pulse was designed to excite two slices with different flip angles and phases. The signals of two slices were driven to be as orthogonal as possible. The mixed and undersampled MRF signal was matched to two dictionaries to retrieve T 1 and T 2 maps of each slice. Quantitative results from the proposed method were validated with the gold-standard spin echo methods in a phantom. T 1 and T 2 maps of in vivo human brain from two simultaneously acquired slices were also compared to the results of fast imaging with steady-state precession based MRF method (MRF-FISP) with a single-band RF excitation. The phantom results showed that the simultaneous multislice imaging MRF-FISP method quantified the relaxation properties accurately compared to the gold-standard spin echo methods. T 1 and T 2 values of in vivo brain from the proposed method also matched the results from the normal MRF-FISP acquisition. T 1 and T 2 values can be quantified at a multiband acceleration factor of two using our proposed acquisition even in a single-channel receive coil. Further acceleration could be achieved by combining this method with parallel imaging or iterative reconstruction. Magn Reson Med 78:1870-1876, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Converting Panax ginseng DNA and chemical fingerprints into two-dimensional barcode.

Science.gov (United States)

Cai, Yong; Li, Peng; Li, Xi-Wen; Zhao, Jing; Chen, Hai; Yang, Qing; Hu, Hao

2017-07-01

In this study, we investigated how to convert the Panax ginseng DNA sequence code and chemical fingerprints into a two-dimensional code. In order to improve the compression efficiency, GATC2Bytes and digital merger compression algorithms are proposed. HPLC chemical fingerprint data of 10 groups of P. ginseng from Northeast China and the internal transcribed spacer 2 (ITS2) sequence code as the DNA sequence code were ready for conversion. In order to convert such data into a two-dimensional code, the following six steps were performed: First, the chemical fingerprint characteristic data sets were obtained through the inflection filtering algorithm. Second, precompression processing of such data sets is undertaken. Third, precompression processing was undertaken with the P. ginseng DNA (ITS2) sequence codes. Fourth, the precompressed chemical fingerprint data and the DNA (ITS2) sequence code were combined in accordance with the set data format. Such combined data can be compressed by Zlib, an open source data compression algorithm. Finally, the compressed data generated a two-dimensional code called a quick response code (QR code). Through the abovementioned converting process, it can be found that the number of bytes needed for storing P. ginseng chemical fingerprints and its DNA (ITS2) sequence code can be greatly reduced. After GTCA2Bytes algorithm processing, the ITS2 compression rate reaches 75% and the chemical fingerprint compression rate exceeds 99.65% via filtration and digital merger compression algorithm processing. Therefore, the overall compression ratio even exceeds 99.36%. The capacity of the formed QR code is around 0.5k, which can easily and successfully be read and identified by any smartphone. P. ginseng chemical fingerprints and its DNA (ITS2) sequence code can form a QR code after data processing, and therefore the QR code can be a perfect carrier of the authenticity and quality of P. ginseng information. This study provides a theoretical

[An analysis of the DNA fingerprinting of intestinal flora in inflammatory bowel disease].

Science.gov (United States)

Li, Run-mei; Han, Ying; Wang, Ji-heng; Wang, Zhi-hong

2007-02-01

DNA fingerprinting for inflammatory bowel disease (IBD) patients and healthy subjects was carried out to compare the difference of intestinal flora between the two groups. DNA fingerprinting for IBD patients and healthy persons was set up with enterobacterial repetitive intergenic consensus (ERIC-PCR) technology and the difference of intestinal flora between the two groups compared. DNA fingerprinting of the IBD patients and healthy subjects was identified and a significant difference was noticed between them. There were lots of bands in the DNA fingerprinting of the healthy subjects but few in that of the IBD patients. Strikingly, same distribution of the principal band of DNA fingerprinting was noticed in IBD patients. The variety of intestinal flora in healthy subjects is more apparent than that in IBD patients. An unique principal band might be the sequence of the presence of specific etiopathogenetic bacterium, or it might be the combined sequence of mixed bacterial flora.

In Silico Genomic Fingerprints of the Bacillus anthracis Group Obtained by Virtual Hybridization

Directory of Open Access Journals (Sweden)

Hueman Jaimes-Díaz

2015-02-01

Full Text Available In this study we evaluate the capacity of Virtual Hybridization to identify between highly related bacterial strains. Eight genomic fingerprints were obtained by virtual hybridization for the Bacillus anthracis genome set, and a set of 15,264 13-nucleotide short probes designed to produce genomic fingerprints unique for each organism. The data obtained from each genomic fingerprint were used to obtain hybridization patterns simulating a DNA microarray. Two virtual hybridization methods were used: the Direct and the Extended method to identify the number of potential hybridization sites and thus determine the minimum sensitivity value to discriminate between genomes with 99.9% similarity. Genomic fingerprints were compared using both methods and phylogenomic trees were constructed to verify that the minimum detection value is 0.000017. Results obtained from the genomic fingerprints suggest that the distribution in the trees is correct, as compared to other taxonomic methods. Specific virtual hybridization sites for each of the genomes studied were also identified.

High perfomance liquid chromatography fingerprint analysis for quality control of brotowali (Tinospora crispa)

Science.gov (United States)

Syarifah, V. B.; Rafi, M.; Wahyuni, W. T.

2017-05-01

Brotowali (Tinospora crispa) is widely used in Indonesia as ingredient of herbal medicine formulation. To ensure the quality, safety, and efficacy of herbal medicine products, its chemical constituents should be continuously evaluated. High performance liquid chromatography (HPLC) fingerprint is one of powerful technique for this quality control process. In this study, HPLC fingerprint analysis method was developed for quality control of brotowali. HPLC analysis was performed in C18 column and detection was performed using photodiode array detector. The optimum mobile phase for brotowali fingerprint was acetonitrile (ACN) and 0.1% formic acid in gradient elution mode at a flow rate of 1 mL/min. The number of peaks detected in HPLC fingerprint of brotowali was 32 peaks and 23 peaks for stems and leaves, respectively. Berberine as marker compound was detected at retention time of 20.525 minutes. Evaluation of analytical performance including precision, reproducibility, and stability prove that this HPLC fingerprint analysis was reliable and could be applied for quality control of brotowali.

Biometric Fingerprint System to Enable Rapid and Accurate Identification of Beneficiaries

OpenAIRE

Storisteanu, Daniel Matthew L; Norman, Toby L; Grigore, Alexandra; Norman, Tristram L

2015-01-01

Inability to uniquely identify clients impedes access to services and contributes to inefficiencies. Using a pocket-sized fingerprint scanner that wirelessly syncs with a health worker's smartphone, the SimPrints biometric system can link individuals' fingerprints to their health records. A pilot in Bangladesh will assess its potential.

Perancangan Aplikasi Presensi Dosen Realtime Dengan Metode Rapid Application Development (RAD Menggunakan Fingerprint Berbasis Web

Directory of Open Access Journals (Sweden)

Darma Setiawan Putra

2018-05-01

Full Text Available The fingerprint is one of the biometric methods which is can be used in the education field. Attendance monitoring system using fingerprint will make the leaders easily to monitor the attendance of the lecturer and to make decisions. The fingerprint attendance is used to easy students detecting quickly and accurately the lecturer in the classroom. This system aims to provide the lecturer status information, entry or exit for teaching when every lecturer performs a fingerprint scanning. This study uses rapid application development (RAD method to develop attendance system and involves the lecturer who have a teaching schedule in the current semester. To test the system, the lecturer was required to record the fingerprint in fingerprint machine. The result shows that the application of lecturer attendance in real time web-based can be a system provides the lecturers attendance information effectively and efficiently.

Fingerprint detection on counterfeit US dollar banknotes: the importance of preliminary paper examination.

Science.gov (United States)

Azoury, Myriam; Cohen, Drorit; Himberg, Kimmo; Qvintus-Leino, Pia; Saari, Terhi; Almog, Joseph

2004-09-01

Two seizures of counterfeit 100 US dollar bills related to the same indicative number were submitted for processing of latent fingerprints. On one group of notes, identifiable fingerprints could be detected by the routine application of amino acid reagents. In the second case, this technique gave no results, even on deliberately deposited prints. Fingerprints could be revealed, however, by cyanoacrylate fuming followed by magnetic powder. Comprehensive paper analysis showed that banknotes from both seizures differed remarkably by chemical composition as well as paper macroscopic properties. The difference in surface free energy (related to surface tension) of the banknotes in the two groups seemed to be the major factor responsible for the great variance in fingerprint detectability.

Nonintrusive Finger-Vein Recognition System Using NIR Image Sensor and Accuracy Analyses According to Various Factors

Directory of Open Access Journals (Sweden)

Tuyen Danh Pham

2015-07-01

Full Text Available Biometrics is a technology that enables an individual person to be identified based on human physiological and behavioral characteristics. Among biometrics technologies, face recognition has been widely used because of its advantages in terms of convenience and non-contact operation. However, its performance is affected by factors such as variation in the illumination, facial expression, and head pose. Therefore, fingerprint and iris recognitions are preferred alternatives. However, the performance of the former can be adversely affected by the skin condition, including scarring and dryness. In addition, the latter has the disadvantages of high cost, large system size, and inconvenience to the user, who has to align their eyes with the iris camera. In an attempt to overcome these problems, finger-vein recognition has been vigorously researched, but an analysis of its accuracies according to various factors has not received much attention. Therefore, we propose a nonintrusive finger-vein recognition system using a near infrared (NIR image sensor and analyze its accuracies considering various factors. The experimental results obtained with three databases showed that our system can be operated in real applications with high accuracy; and the dissimilarity of the finger-veins of different people is larger than that of the finger types and hands.

Nonintrusive Finger-Vein Recognition System Using NIR Image Sensor and Accuracy Analyses According to Various Factors.

Science.gov (United States)

Pham, Tuyen Danh; Park, Young Ho; Nguyen, Dat Tien; Kwon, Seung Yong; Park, Kang Ryoung

2015-07-13

Biometrics is a technology that enables an individual person to be identified based on human physiological and behavioral characteristics. Among biometrics technologies, face recognition has been widely used because of its advantages in terms of convenience and non-contact operation. However, its performance is affected by factors such as variation in the illumination, facial expression, and head pose. Therefore, fingerprint and iris recognitions are preferred alternatives. However, the performance of the former can be adversely affected by the skin condition, including scarring and dryness. In addition, the latter has the disadvantages of high cost, large system size, and inconvenience to the user, who has to align their eyes with the iris camera. In an attempt to overcome these problems, finger-vein recognition has been vigorously researched, but an analysis of its accuracies according to various factors has not received much attention. Therefore, we propose a nonintrusive finger-vein recognition system using a near infrared (NIR) image sensor and analyze its accuracies considering various factors. The experimental results obtained with three databases showed that our system can be operated in real applications with high accuracy; and the dissimilarity of the finger-veins of different people is larger than that of the finger types and hands.

Provenancing Flower Bulbs by Analytical Fingerprinting: Convallaria Majalis

Directory of Open Access Journals (Sweden)

Saskia M. van Ruth

2015-01-01

Full Text Available The origin of agricultural products is gaining in appreciation while often hard to determine for various reasons. Geographical origin may be resolved using a combination of chemical and physical analytical technologies. In the present case of Lily of the Valley (Convallaria majalis rhizomes, we investigated an exploratory set of material from The Netherlands, three other European (EU countries and China. We show that the geographical origin is correlated to patterns of stable isotope ratios (isotope fingerprints and volatile organic carbon (VOC compounds (chemical fingerprints. These fingerprints allowed clear distinction using exploratory and supervised statistics. Isotope ratio mass spectrometry of 12C/13C, 14N/15N and 16O/18O isotopes separated materials from Europe and China successfully. The VOC patterns measured by Proton Transfer Reaction Mass Spectrometry (PTR-MS allowed distinction of three groups: material from The Netherlands, the other EU countries and China. This knowledge is expected to help developing a systematic and efficient analytical tool for authenticating the origin of flower bulbs.

Donor-derived metastatic melanoma in a liver transplant recipient established by DNA fingerprinting.

Science.gov (United States)

Bilal, Muhammad; Eason, James D; Das, Kanak; Sylvestre, Pamela B; Dean, Amanda G; Vanatta, Jason M

2013-10-01

Metastatic melanoma is a donor-derived malignancy that has rarely been reported in liver allograft recipients. We present a case of a transmitted donor-derived melanoma to a liver allograft recipient in whom the diagnosis was established by polymerase chain reaction-based DNA fingerprinting. A 52-year-old African-American man underwent a successful orthotropic liver transplant for alcohol-induced cirrhosis. One year after the orthotropic liver transplant, he presented at our institution with diffuse abdominal pain, and a computed tomography scan of the abdomen and chest showed innumerable masses diffusely involving the liver and multiple subcutaneous nodules in the abdominal and chest wall. A liver biopsy confirmed the diagnosis of metastatic melanoma. The origin of melanoma was traced to the donor by DNA fingerprinting of the native liver, the donor liver, and the donor gallbladder. Chemotherapy was initiated with temozolomide (75 mg/m² daily) and thalidomide (50 mg daily), to which he responded within 8 weeks with radiologic improvement in metastatic lesions. Tacrolimus was switched to sirolimus because of renal insufficiency as well as reported effectiveness against melanoma. Our patient survived for 9 months after the diagnosis of metastatic melanoma. He ultimately died of brain metastases. Donor-derived metastatic melanoma is a rare cancer with the highest transmission and mortality rates, which requires better recognition. Prompt diagnosis of donor-derived melanoma is critical and can be achieved reliably with polymerase chain reaction-based DNA analysis. Management options after diagnosis include de-escalation of immunosuppression, with or without urgent organ removal or retransplant. The roles of chemotherapy, immunotherapy, and radiotherapy require further study.

Comparative Study on Feature Selection and Fusion Schemes for Emotion Recognition from Speech

Directory of Open Access Journals (Sweden)

Santiago Planet

2012-09-01

Full Text Available The automatic analysis of speech to detect affective states may improve the way users interact with electronic devices. However, the analysis only at the acoustic level could be not enough to determine the emotion of a user in a realistic scenario. In this paper we analyzed the spontaneous speech recordings of the FAU Aibo Corpus at the acoustic and linguistic levels to extract two sets of features. The acoustic set was reduced by a greedy procedure selecting the most relevant features to optimize the learning stage. We compared two versions of this greedy selection algorithm by performing the search of the relevant features forwards and backwards. We experimented with three classification approaches: Naïve-Bayes, a support vector machine and a logistic model tree, and two fusion schemes: decision-level fusion, merging the hard-decisions of the acoustic and linguistic classifiers by means of a decision tree; and feature-level fusion, concatenating both sets of features before the learning stage. Despite the low performance achieved by the linguistic data, a dramatic improvement was achieved after its combination with the acoustic information, improving the results achieved by this second modality on its own. The results achieved by the classifiers using the parameters merged at feature level outperformed the classification results of the decision-level fusion scheme, despite the simplicity of the scheme. Moreover, the extremely reduced set of acoustic features obtained by the greedy forward search selection algorithm improved the results provided by the full set.

Cluster analysis of Helicobacter pylori genomic DNA fingerprints suggests gastroduodenal disease-specific associations.

Science.gov (United States)

Go, M F; Chan, K Y; Versalovic, J; Koeuth, T; Graham, D Y; Lupski, J R

1995-07-01

Helicobacter pylori infection is now accepted as the most common cause of chronic active gastritis and peptic ulcer disease. The etiologies of many infectious diseases have been attributed to specific or clonal strains of bacterial pathogens. Polymerase chain reaction (PCR) amplification of DNA between repetitive DNA sequences, REP elements (REP-PCR), has been utilized to generate DNA fingerprints to examine similarity among strains within a bacterial species. Genomic DNA from H. pylori isolates obtained from 70 individuals (39 duodenal ulcers and 31 simple gastritis) was PCR-amplified using consensus probes to repetitive DNA elements. The H. pylori DNA fingerprints were analyzed for similarity and correlated with disease presentation using the NTSYS-pc computer program. Each H. pylori strain had a distinct DNA fingerprint except for two pairs. Single-colony DNA fingerprints of H. pylori from the same patient were identical, suggesting that each patient harbors a single strain. Computer-assisted cluster analysis of the REP-PCR DNA fingerprints showed two large clusters of isolates, one associated with simple gastritis and the other with duodenal ulcer disease. Cluster analysis of REP-PCR DNA fingerprints of H. pylori strains suggests that duodenal ulcer isolates, as a group, are more similar to one another and different from gastritis isolates. These results suggest that disease-specific strains may exist.

DNA fingerprinting of Chinese melon provides evidentiary support of seed quality appraisal.

Science.gov (United States)

Gao, Peng; Ma, Hongyan; Luan, Feishi; Song, Haibin

2012-01-01

Melon, Cucumis melo L. is an important vegetable crop worldwide. At present, there are phenomena of homonyms and synonyms present in the melon seed markets of China, which could cause variety authenticity issues influencing the process of melon breeding, production, marketing and other aspects. Molecular markers, especially microsatellites or simple sequence repeats (SSRs) are playing increasingly important roles for cultivar identification. The aim of this study was to construct a DNA fingerprinting database of major melon cultivars, which could provide a possibility for the establishment of a technical standard system for purity and authenticity identification of melon seeds. In this study, to develop the core set SSR markers, 470 polymorphic SSRs were selected as the candidate markers from 1219 SSRs using 20 representative melon varieties (lines). Eighteen SSR markers, evenly distributed across the genome and with the highest contents of polymorphism information (PIC) were identified as the core marker set for melon DNA fingerprinting analysis. Fingerprint codes for 471 melon varieties (lines) were established. There were 51 materials which were classified into17 groups based on sharing the same fingerprint code, while field traits survey results showed that these plants in the same group were synonyms because of the same or similar field characters. Furthermore, DNA fingerprinting quick response (QR) codes of 471 melon varieties (lines) were constructed. Due to its fast readability and large storage capacity, QR coding melon DNA fingerprinting is in favor of read convenience and commercial applications.

DNA Fingerprinting of Chinese Melon Provides Evidentiary Support of Seed Quality Appraisal

Science.gov (United States)

Gao, Peng; Ma, Hongyan; Luan, Feishi; Song, Haibin

2012-01-01

Melon, Cucumis melo L. is an important vegetable crop worldwide. At present, there are phenomena of homonyms and synonyms present in the melon seed markets of China, which could cause variety authenticity issues influencing the process of melon breeding, production, marketing and other aspects. Molecular markers, especially microsatellites or simple sequence repeats (SSRs) are playing increasingly important roles for cultivar identification. The aim of this study was to construct a DNA fingerprinting database of major melon cultivars, which could provide a possibility for the establishment of a technical standard system for purity and authenticity identification of melon seeds. In this study, to develop the core set SSR markers, 470 polymorphic SSRs were selected as the candidate markers from 1219 SSRs using 20 representative melon varieties (lines). Eighteen SSR markers, evenly distributed across the genome and with the highest contents of polymorphism information (PIC) were identified as the core marker set for melon DNA fingerprinting analysis. Fingerprint codes for 471 melon varieties (lines) were established. There were 51 materials which were classified into17 groups based on sharing the same fingerprint code, while field traits survey results showed that these plants in the same group were synonyms because of the same or similar field characters. Furthermore, DNA fingerprinting quick response (QR) codes of 471 melon varieties (lines) were constructed. Due to its fast readability and large storage capacity, QR coding melon DNA fingerprinting is in favor of read convenience and commercial applications. PMID:23285039

DNA fingerprinting of Chinese melon provides evidentiary support of seed quality appraisal.

Directory of Open Access Journals (Sweden)

Peng Gao

Full Text Available Melon, Cucumis melo L. is an important vegetable crop worldwide. At present, there are phenomena of homonyms and synonyms present in the melon seed markets of China, which could cause variety authenticity issues influencing the process of melon breeding, production, marketing and other aspects. Molecular markers, especially microsatellites or simple sequence repeats (SSRs are playing increasingly important roles for cultivar identification. The aim of this study was to construct a DNA fingerprinting database of major melon cultivars, which could provide a possibility for the establishment of a technical standard system for purity and authenticity identification of melon seeds. In this study, to develop the core set SSR markers, 470 polymorphic SSRs were selected as the candidate markers from 1219 SSRs using 20 representative melon varieties (lines. Eighteen SSR markers, evenly distributed across the genome and with the highest contents of polymorphism information (PIC were identified as the core marker set for melon DNA fingerprinting analysis. Fingerprint codes for 471 melon varieties (lines were established. There were 51 materials which were classified into17 groups based on sharing the same fingerprint code, while field traits survey results showed that these plants in the same group were synonyms because of the same or similar field characters. Furthermore, DNA fingerprinting quick response (QR codes of 471 melon varieties (lines were constructed. Due to its fast readability and large storage capacity, QR coding melon DNA fingerprinting is in favor of read convenience and commercial applications.

Spiral MR fingerprinting at 7T with simultaneous B1 estimation.

Science.gov (United States)

Buonincontri, Guido; Schulte, Rolf F; Cosottini, Mirco; Tosetti, Michela

2017-09-01

Magnetic resonance fingerprinting is an efficient, new approach for quantitative imaging with MR. We aimed to extend this technique to cases with B1+ inhomogeneities within the imaging volume. Previous approaches have used abrupt changes in flip angles to estimate the B1+ field simultaneously with T1 and T2, using a Cartesian approach in a small-animal scanner at 4.7T. Here, we evaluated whether a similar approach would be suitable for imaging human brains using spiral readouts with a 7T scanner. We found that our modified scheme could significantly reduce the adverse effects of B1+ inhomogeneities even in extreme cases, reducing both the bias and the variance in T2 estimations by an order of magnitude when compared to literature methods. Acquisitions used less than 1.5W/kg SAR and could be performed in 12s per slice. In conclusion, our approach can be used to perform quantitative imaging of the brain at 7T in a short time, simultaneously estimating the B1+ profile. Copyright © 2017 Elsevier Inc. All rights reserved.