Vein Features Research Articles

A novel fuzzy vault scheme based on fingerprint and finger vein feature fusion

Template security is a critical issue in biometric systems. As we know, our biometrics will not change when we reach adulthood. What will happen if our biometric template is lost or stolen? The classical fuzzy vault scheme uses a single biological template, and the biological feature parameters are directly present in the fuzzy vault, this will not effectively protect the biological template. To deal with this problem, we propose a novel fuzzy vault scheme based on fingerprint and finger vein feature fusion which can alleviate the limitation of the fuzzy vault using one biological template. It is difficult for attackers to restore each biological template from the fusion template. In addition, the fusion encoding not the feature point parameters is stored in our fuzzy vault, and this fusion encoding will not reveal the information of feature point. Our experiment results show that our scheme can also achieve a high genuine acceptance rate and a low false acceptance rate.

Cross-device hand vein recognition based on improved SIFT

The recognition rate of SIFT algorithm in single hand vein database has been as high as 99.5%. But with the development of Internet-plus technology, the demand for distributed systems becomes more and more significant. However, the problem of picture quality caused by cross-device makes the intraclass variations larger. For example, when gathering the dorsal hand vein images, subtle changes in relative distance and orientation among the imaging camera, the illumination LED arrays and the different location of users’ hand, as well as shielding by the external housing box from ambient light sources and so on, these will make large difference to one person’s hand images. So, including the contrast, the lightness, the shifting, the angle of rotation, the size and so on, these differences make it possible to use some traditional methods to recognize dorsal hand vein with a low recognition rate of less than 50%. Therefore, based on the traditional SIFT, this paper optimized the scale factor [Formula: see text], extreme searching neighborhood structure and matching threshold [Formula: see text]. It can be seen that the cross-device hand vein feature is more robust, and the recognition rate reached an average of 88.5%.

Multiple palm features extraction method based on vein and palmprint

Contactless acquisition enables palm identification device to be more easily accepted by people who worry about hygiene problems. The uncertainty of the position between the palm and the device leads to the horizontal rotation, translation, scaling of palm image. This paper proposes a novel feature extraction method which can reflect the geometric features of palmprint and palm vein without being affected by the scaling, rotation and translation. Firstly, the inscribed circle of palm is obtained, and then several radiation segments are made between the circle center and circumference. The wiring direction from the center to the root points of both middle finger and ring finger is as the direction of the first radiation segment. Secondly, the gradient value of pixels in the inscribed circle is calculated by creating template. The feature vector space is established by the relative radius of radiation segment’s centroids. Finally, the palm image database is established based on the application. The feature stability in different size of sub-template and recognition performance in different number of feature line segments are analyzed. In the size of sub-template is equal to three and the number of feature line segments is 60, the equal error rate is less than 0.4% and feature extraction time is 0.0019 s. The experimental results show that the method can extract out stable characteristics whenever the hand image is scaled, rotated or translated.

Reconstruction of a >200 Ma multi-stage “five element” Bi-Co-Ni-Fe-As-S system in the Penninic Alps, Switzerland

Hydrothermal five-element veins (Ag-Co-Ni-Bi-As) are mineral successions of native metals, encapsulated by Fe-Co-Ni arsenides and carbonates. Recent studies focused on the evolution from ordinary base-metal systems (sulfide-rich) to five-element veins (sulfide-poor) and revealed the importance of hydrocarbon-dominated fluids as essential redox agent in these systems. Although mineral successions reveal the natural subdivision into native As-, native Ag/Bi- or arsenide-dominated vein types and suggested processes explain the mineralogical variation to a certain degree, the Ni-Co-Fe-variations among the arsenides are not well understood yet.This is the first case study explaining compositional, mineralogical, and textural features of five-element veins by changing metal contents, arsenic/sulfur activities, pH and temperatures, applied to a multi-stage vein mineralization in the Penninic Alps, Switzerland. Textural relationships, mineral chemistry, fluid inclusion compositions (microthermometry and Raman spectroscopy), stable S-isotopes and in-situ U-Pb age dating of carbonates, magnetite and multi-mineral isochrons were investigated.U-Pb ages of paragenetic mineral fractions constrain a primary formation of löllingite-skutterudite-dolomite-dominated ores at 233 ± 10 Ma and niccolite-gersdorffite-skutterudite-ankerite-dominated ores at 188 ± 32 Ma, which links their formation to crustal thinning caused by the breakup of the Meliata ocean and Alpine Tethys. As secondary processes during the Alpine Orogeny, a in-situ remobilization of the ores occurred as mostly ternary Fe-Co-Ni sulfarsenides at ∼73–24 Ma due to continent-continent collision and neoformations of safflorite-cobaltite-skutterudite-dominated ores at ∼29–16 Ma due to transtensional strike-slip tectonics.Ore textures indicate that the dissolution of primary siderite, oxidation of ferrous iron and its precipitation as magnetite was the redox couple to precipitate native Bi, arsenides and sulfarsenides (Bi0, As3− and As−1) from their oxidized aqueous species Bi3+Cl4−, and As3+(OH)3 at temperatures between 200 and 300 °C. Ni and Co signatures of the arsenides/sulfarsenides show increasing mobilization from the host rocks during the successive evolution of the hydrothermal system in the Triassic, Jurassic and during the Alpine Orogeny. Stable S-isotopes and As/S signatures of the sulfarsenides indicate an increasing mobilization of host rock sulfides (i.e. fahlbands) from the primary to the secondary ores. Fluid inclusions and stable S-isotopes suggest involvement of fluid modification by water-rock interactions (i.e. cover rocks: carbonate, sulfate and halite dissolution; basement rocks: albitisation of plagioclase) during fluid descent.

Investigation of adverse events associated with an off-label use of arterial stents and CE-marked iliac vein stents in the iliac vein: insights into developing a better iliac vein stent.

We analyzed the adverse events associated with an off-label use of arterial stents and CE-marked iliac vein stents for the treatment of iliac venous thromboembolism and investigated their relationships with the anatomical features of the iliac vein, to gain insights into the development of a better iliac vein stent. Reports of adverse events following the use of stents in the iliac vein were retrieved from the Manufacturer and User Facility Device Experience (MAUDE) database that contain suspected device-associated complications reported to the Food and Drug Administration. Data from 2006 to 2016 were investigated. The literature analysis was also conducted using PubMed, Cochrane Library, EMBASE, and Web of Science focusing on English articles published up to 4 October 2016. The analysis of 88 adverse events from the MAUDE database and 182 articles from the literature revealed that a higher number of adverse events had been reported following the use of arterial stents in the iliac vein compared to CE-marked iliac vein stents. While stent migration and shortening were reported only for the arterial stents, stent fracture and compression occurred regardless of the stent type, even though a vein does not pulsate. A study of the anatomical features of the iliac vein implies that bending, compression, and kink loads are applied to the iliac vein stents in vivo. For designing, developing, and pre-clinical testing of stents intended for use in the iliac vein, the above mechanical load environments induced by the anatomical features should be considered.

Relationship between pulsed wave Doppler ultrasonographic features of milk veins and CMT scores in Simmental cows

This study aimed to determine the distribution of pulsed wave Doppler ultrasonographic features of milk veins in lactating cows corresponding to udder health and the results of California Mastitis Test (CMT). Clinically healthy Simmental cows aged 3-5 years within the first 12 weeks of postpartum period were used for the study. End Diastolic Velocities (EDV), Systolic Peak Velocity (SPV), and Time-Averaged Maximum Velocity (TAMV) were the measured Doppler features of the milk veins. Numerical scales for Pulsatile Index (PI) and Resistant Index (RI) were devised in accordance with blood flow parameters. The animals were allocated to two groups according to CMT results as CMT positive (n=21) and CMT negative (n=5). No differences were found between the group regarding to PI, RI, EDV, or SPV (p>0.05). However, TAMV was found to be lower in CMT-positive animals (7.52 ± 0.85 cm/sec) compared to CMT-negative (13.90 ± 3.56 cm/sec) animals (p=0.021)

The role and significance of digital reconstruction technique in liver segments based on portal vein structure

Objective: To study the segment of liver according to the large amount of three-dimensional(3D) reconstructive images of normal human livers and the vascular system, and to recognize the basic functional liver unit based on the anatomic features of the intrahepatic portal veins. Methods: The enhanced CT primitive DICOM files of 1 260 normal human livers from different age groups who treated from October 2013 to February 2017 provided by 16 hospitals were analyzed using the computer-aided surgery system.The 3D liver and liver vascular system were reconstructed, and the digital liver 3D model was established.The vascular morphology, anatomical features, and anatomical distributions of intrahepatic portal veins were statistically analyzed. Results: The digital liver model obtained from the 3D reconstruction of CAS displayed clear intrahepatic portal vein vessels of level four.Perform a digital liver segments study based on the analysis of level four vascular distribution areas.As the less anatomical variation of left hepatic portal vein, the liver was classified into four types of liver segmentation mainly based on right hepatic portal vein.Type A was similar to Couinaud or Cho's segmentation, containing 8 segments(537 cases, 42.62%). Type B contained 9 segments as there are three ramifications of right-anterior portal vein(464 cases, 36.82%). The main difference for Type C was the variation of right-posterior portal vein which was sector shape(102 cases, 8.10%). Type D contained the cases with special portal vein variations, which needs three-dimensional simulation to design individualized liver resection plan(157 cases, 12.46%). These results showed that there was no significant difference in liver segmental typing between genders(χ(2)=2.179, P=0.536) and did not reveal any significant difference in liver segmental typing among the different age groups(χ(2)=0.357, P=0.949). Conclusions: The 3D digital liver model can demonstrate the true 3D anatomical structures, and its spatial vascular variations.The observation of anatomic features, distribution areas of intrahepatic portal veins and individualized liver segmentation achieved via digital medical 3D visualization technology is of great value for understand the complexity of liver anatomy and to guide the precise hepatectomy.

基于BSLDP和典型相关分析的掌纹掌脉融合识别

基于BSLDP和典型相关分析的掌纹掌脉融合识别

Vein recognition based on minutiae features in the dorsal venous network of the hand

This paper presents a novel, local feature-based vein representation method based on minutiae features from skeleton images of venous networks. The main motivation is to learn the most discriminative regions and features of dorsal hand veins to identify persons who are scanned. These minutiae features include end points and the arc lines between the two end points as measured along the boundary of the region of interest. In addition, we propose a dynamic pattern tree to accelerate matching performance and evaluate the discriminatory power of these feature points for verifying a person’s identity. In a comparison with six existing verification algorithms, the proposed method achieved the highest accuracy in the lowest tested matching time.

Pathophysiology of Venous Thromboembolism with Respect to the Anatomical Features of the Deep Veins of Lower Limbs: A Review

Here the pathophysiology of venous thromboembolism is reviewed with respect to the anatomical features of the deep veins of lower limbs. A thrombus is less likely to form in the thigh veins compared with that in the calf veins; however, clinical symptoms are more likely to appear in the thigh veins owing to vascular occlusion. When a patient is bedridden, thrombosis is more likely to occur in the intramuscular vein, which mainly depends on muscular pumping and the venous valve, rather than in the three crural branches, which mainly depends on the pulsation of the accompanying artery. Thrombi are prone to be generated in the soleal vein compared with those in the gastrocnemius vein because of the vein and muscle structures. A soleal vein thrombosis grows toward the proximal veins along the drainage veins. To prevent a sudden pulmonary thromboembolism-related death in bedridden patients, preventing soleal vein thrombus formation and observing the thrombus proximal propagation via the drainage veins are clinically important. When deep vein thrombosis occurs, avoiding embolization and sequela caused by the thrombus organization is necessary.

Histological characterization of umbilical cord in alpaca (Vicugna pacos).

The histomorphometric features of umbilical cord constituents in seven foetuses of alpaca (Vicugna pacos) from Cerro de Pasco, Department, Peru, were determined. Sections of 2-5cm of umbilical cord were fixed in 10% neutral buffered formalin and processed for light microscopy. Standard histological slides stained with haematoxylin and eosin, Masson's trichrome and Van Gieson's trichrome were obtained. Histologically, common features of umbilical artery and vein were observed as well as mucous connective tissue, some cell features that compound this tissue constituted by cells presented features of myofibroblasts. Among most important findings that were observed, the lumen of umbilical vein was obliterated into star-shaped form with the thinner umbilical artery wall; the smooth muscles and fibroblast were comparatively more in number in umbilical artery than that of umbilical vein, and the tunica media was larger in dimension than the tunica adventitia in umbilical vein. Conclusively, this histological study features an observation of the umbilical cord of alpaca foetuses and shows the similarity between them and those of other mammal species, including dromedaries and South American camelids.

On the influence of anisotropic diffusion filter on dorsal hand authentication using eigenveins

In this paper, we present a competent approach for dorsal hand vein features extraction from near infrared images and PCA matching. Which is the anisotropic diffusion filter; we present first a review about this filter most used for the image enhancement. The physiological features characterize the dorsal venous network of the hand. These networks are single to each individual and can be used as a biometric system for person identification/authentication. An active near infrared method is used for image acquisition. The proposed approach uses an anisotropic diffusion technique for contrast enhancement and morphological filtering to extract the venous network and principal component analysis.

Deep Representation-Based Feature Extraction and Recovering for Finger-Vein Verification

Finger-vein biometrics has been extensively investigated for personal verification. Despite recent advances in finger-vein verification, current solutions completely depend on domain knowledge and still lack the robustness to extract finger-vein features from raw images. This paper proposes a deep learning model to extract and recover vein features using limited a priori knowledge. First, based on a combination of the known state-of-the-art handcrafted finger-vein image segmentation techniques, we automatically identify two regions: a clear region with high separability between finger-vein patterns and background, and an ambiguous region with low separability between them. The first is associated with pixels on which all the above-mentioned segmentation techniques assign the same segmentation label (either foreground or background), while the second corresponds to all the remaining pixels. This scheme is used to automatically discard the ambiguous region and to label the pixels of the clear region as foreground or background. A training data set is constructed based on the patches centered on the labeled pixels. Second, a convolutional neural network (CNN) is trained on the resulting data set to predict the probability of each pixel of being foreground (i.e., vein pixel), given a patch centered on it. The CNN learns what a finger-vein pattern is by learning the difference between vein patterns and background ones. The pixels in any region of a test image can then be classified effectively. Third, we propose another new and original contribution by developing and investigating a fully convolutional network to recover missing finger-vein patterns in the segmented image. The experimental results on two public finger-vein databases show a significant improvement in terms of finger-vein verification accuracy.

Exploring finger vein based personal authentication for secure IoT

Personal authentication is getting harder and harder in the internet of things (IoT). Existing methods used for personal authentication, such as passwords and the two-factor authentication (2FA), are inadequate and ineffective due to human error and other attacks. To support more secure IoT, this paper proposes a finger vein based personal authentication method by exploring competitive orientations and magnitudes from finger vein images. Finger vein recognition has been proven to be a reliable and promising solution for biometric-based personal authentication. The stable and rich piecewise line features in finger vein images can be used to clearly represent finger vein patterns for personal authentication. In this paper, we propose an efficient local descriptor for finger vein feature extraction, namely the histogram of competitive orientations and magnitudes (HCOM). For a finger vein image, two types of local histograms are extracted and fused together to efficiently and adequately represent the competitive information: the histogram of competitive orientations (HCO) and the local binary pattern histogram generated from the image of competitive magnitudes (named as HCMLBP). The extensive experimental results from the application of the proposed method to the public finger vein database MMCBNU_6000, demonstrate that the proposed method outperforms state-of-the-art orientation coding (OC)-based methods and other commonly used local descriptors. Additionally, the proposed method can be used for finger vein image enhancement.

Differences in subependymal vein anatomy may predispose preterm infants to GMH–IVH

Background and purposeThe anatomy of the deep venous system plays an important role in the pathogenesis of brain lesions in the preterm brain as shown by different histological studies. The...

Vulvar varicosities: diagnosis, treatment, and prevention.

ObjectiveVulvar varicosity is a relatively common venous disorder in women with varicose veins of the pelvis and lower extremities and in pregnant women, but there is little information in the medical literature concerning its diagnosis and management. The aim of this study was to describe our experience with 101 women with vulvar varicosities who were examined and treated at our center during 2000–2014.Patients and methodsPatients were divided into two groups: group 1 with 61 women with varicose veins of the pelvis and enlarged vulvar veins, and group 2 with 40 pregnant women (11–38 weeks of pregnancy) with vulvar varicosities.ResultsIn most cases, vulvar varicosities were able to be diagnosed at clinical examination. In both groups, duplex ultrasound of the veins of the pelvis and lower extremities was used to confirm the presence of varicose veins, identify any retrograde flow, accurately determine vein diameter, and to reveal any anatomical feature of the intrapelvic veins. Treatment approaches varied significantly between the two groups from purely conservative measures during pregnancy to surgical procedures on the ovarian and vulvar veins in group 1. The venoactive agent, micronized purified flavonoid fraction, was effective at reducing the symptoms of vulvar varicosities in both groups.ConclusionA tailored approach to the diagnosis and treatment of vulvar varicosities can significantly improve the quality of care of women with this disorder.

Role of four-dimensional echocardiography with high-definition flow imaging and spatiotemporal image correlation in detecting fetal pulmonary veins.

Prenatal diagnosis of fetal total anomalous pulmonary vein connection (TAPVC) remains challenging for most screening sonographers. The purpose of this study was to evaluate the use of four-dimensional echocardiography with high-definition flow imaging and spatiotemporal image correlation (4D-HDFI) in identifying pulmonary veins in normal and TAPVC fetuses. We retrospectively reviewed and performed 4D-HDFI in 204 normal and 12 fetuses with confirmed diagnosis of TAPVC. Cardiac volumes were available for postanalysis to obtain 4D-rendered images of the pulmonary veins. For the normal fetuses, two other traditional modalities including color Doppler and HDFI were used to detect the number of pulmonary veins and comparisons were made between each of these traditional methods and 4D-HDFI. For conventional echocardiography, HDFI modality was superior to color Doppler in detecting more pulmonary veins in normal fetuses throughout the gestational period. 4D-HDFI was the best method during the second trimester of pregnancy in identifying normal fetal pulmonary veins. 4D-HDFI images vividly depicted the figure, course, and drainage of pulmonary veins in both normal and TAPVC fetuses. HDFI and the advanced 4D-HDFI technique could facilitate identification of the anatomical features of pulmonary veins in both normal and TAPVC fetuses; 4D-HDFI therefore provides additional and more precise information than conventional echocardiography techniques.

Pathophysiology of Venous Thromboembolism with Respect to the Anatomical Features of the Deep Veins of Lower Limbs: A Review.

Here the pathophysiology of venous thromboembolism is reviewed with respect to the anatomical features of the deep veins of lower limbs. A thrombus is less likely to form in the thigh veins compared with that in the calf veins; however, clinical symptoms are more likely to appear in the thigh veins owing to vascular occlusion. When a patient is bedridden, thrombosis is more likely to occur in the intramuscular vein, which mainly depends on muscular pumping and the venous valve, rather than in the three crural branches, which mainly depends on the pulsation of the accompanying artery. Thrombi are prone to be generated in the soleal vein compared with those in the gastrocnemius vein because of the vein and muscle structures. A soleal vein thrombosis grows toward the proximal veins along the drainage veins. To prevent a sudden pulmonary thromboembolism-related death in bedridden patients, preventing soleal vein thrombus formation and observing the thrombus proximal propagation via the drainage veins are clinically important. When deep vein thrombosis occurs, avoiding embolization and sequela caused by the thrombus organization is necessary.

A Comparative Study of Palm Vein Feature Extraction and Classification

Live blood palm vessel pattern for person identification demands palm-vein authentication method. Biometric authentication with contact palm vein is the traditional method. This method found to be not hygienic and not reliable with age factor. The present paper explains the challenges involved in sensor development, segmentation and detection of contactless palm vein pattern. This paper focuses several clustering method for segmentation. Like Principal Component Analysis (PCA) and Self Organizing Map (SOM) algorithms proven efficient to recognize desired vein pattern in huge data.

Discriminating Leaves Affected with Tomato Yellow Leaf Curl through Fluorescence Imaging Using Texture and Leaf Vein Features

<abstract> Tomato yellow leaf curl disease (TYLCD), one of the most common diseases in tomato production, spreads rapidly and results in huge yield losses. This study aims to investigate the feasibility of discriminating TYLCD through fluorescence imaging. Fluorescence images (FI) of healthy and infected plants were collected with a high-speed camera, filters (690 nm), and three excitation LEDs (430 nm). Automatic iterative threshold selection and region filling methods were used to separate the leaf pixels of each image from the background. The segmented subimages containing 100% leaf pixels were selected as central images (CI). Leaf vein images (LI) were obtained from CIs through hit-or-miss transformation. In contrast to the vein morphologies of the infected leaves, those of the CIs and LIs of the healthy leaves were uniformly distributed. Gray-level co-occurrence matrix was used to extract texture features (TF) from CIs and leaf vein features (LF) from LIs. Sixteen features were evaluated using the receiver operating characteristic (ROC) curve, and rational features were selected by the area under the curves (AUC). All features were categorized into three groups: TF, LF, and their combination. For each group, features without ROC selection (TF, LF, and TF+LF) and after ROC selection (selected TF, selected LF, and selected features) were used as inputs to three classifiers: k-nearest neighbor (KNN), liner discrimination analysis (LDA), and binary logistic regression (BLR). Finally, six TF and six LF were selected. Without ROC selection, all classifiers performed with accuracies ranging from 95% to 100% in identifying infected leaves. For the TF+LF group, BLR exhibited the highest overall accuracy (100%), whereas LDA showed the lowest. After ROC selection, BLR had significantly increased classification accuracy, with higher accuracy for identifying infected leaves than for healthy leaves. This method could be used with TF and LF extracted from FI to discriminate TYLCD.