Intra-modal Score level Fusion for Off-line Signature Verification

Signature is widely used as a means of personal verification which emphasizes the need for a signature verification system. Often the single signature feature may produce unacceptable error rates. In this paper, Intra-modal Score level Fusion for Off-line Signature Verification (ISFOSV) is proposed. The scanned signature image is skeletonized and exact signature area is obtained by preprocessing. In the first stage 60 centers of signature are extracted by horizontal and vertical splitting. In the second stage the 168 features are extracted in two phases. The phase one consists of dividing the signature into 128 blocks using the center of signature by counting the number of black pixels and the angular feature in each block is determined to generate 128 angular features. In the second phase the signature is divided into 40 blocks from each of the four corners of the signature to generate 40 angular features. Totally 168 angular features are extracted from phase one and two to verify the signature. The centers of signature are compared using correlation and the distance between the angular features of the genuine and test signatures is computed. The correlation matching score and distance matching score of the signature are fused to verify the authenticity. A mathematical model is proposed to further optimize the results. It is observed that the proposed model has better FAR, FRR and EER values compared to the existing algorithms

High security human recognition system using iris images

In this paper, efficient biometric security technique for Integer Wavelet Transform based Human Recognition System (IWTHRS) using Iris images verification is described. Human Recognition using Iris images is one of the most secure and authentic among the other biometrics. The Iris and Pupil boundaries of an Eye are identified by Integro-Differential Operator. The features of the normalized Iris are extracted using Integer Wavelet Transform and Discrete Wavelet Transform. The Hamming Distance is used for matching of two Iris feature vectors. It is observed that the values of FAR, FRR, EER and computation time required are improved in the case of Integer Wavelet Transform based Human Recognition System as compared to Discrete Wavelet Transform based Human Recognition System (DWTHRS)

OSPCV: Off-line Signature Verification using Principal Component Variances

Signature verification system is always the most sought after biometric verification system. Being a behavioral biometric feature which can always be imitated, the researcher faces a challenge in designing such a system, which has to counter intrapersonal and interpersonal variations. The paper presents a comprehensive way of off-line signature verification based on two features namely, the pixel density and the centre of gravity distance. The data processing consists of two parallel processes namely Signature training and Test signature analysis. Signature training involves extraction of features from the samples of database and Test signature analysis involves extraction of features from test signature and it’s comparison with those of trained values from database. The features are analyzed using Principal Component Analysis (PCA). The proposed work provides a feasible result and a notable improvement over the existing systems

Risk profiles and one-year outcomes of patients with newly diagnosed atrial fibrillation in India: Insights from the GARFIELD-AF Registry.

BACKGROUND: The Global Anticoagulant Registry in the FIELD-Atrial Fibrillation (GARFIELD-AF) is an ongoing prospective noninterventional registry, which is providing important information on the baseline characteristics, treatment patterns, and 1-year outcomes in patients with newly diagnosed non-valvular atrial fibrillation (NVAF). This report describes data from Indian patients recruited in this registry. METHODS AND RESULTS: A total of 52,014 patients with newly diagnosed AF were enrolled globally; of these, 1388 patients were recruited from 26 sites within India (2012-2016). In India, the mean age was 65.8 years at diagnosis of NVAF. Hypertension was the most prevalent risk factor for AF, present in 68.5% of patients from India and in 76.3% of patients globally (P < 0.001). Diabetes and coronary artery disease (CAD) were prevalent in 36.2% and 28.1% of patients as compared with global prevalence of 22.2% and 21.6%, respectively (P < 0.001 for both). Antiplatelet therapy was the most common antithrombotic treatment in India. With increasing stroke risk, however, patients were more likely to receive oral anticoagulant therapy [mainly vitamin K antagonist (VKA)], but average international normalized ratio (INR) was lower among Indian patients [median INR value 1.6 (interquartile range {IQR}: 1.3-2.3) versus 2.3 (IQR 1.8-2.8) (P < 0.001)]. Compared with other countries, patients from India had markedly higher rates of all-cause mortality [7.68 per 100 person-years (95% confidence interval 6.32-9.35) vs 4.34 (4.16-4.53), P < 0.0001], while rates of stroke/systemic embolism and major bleeding were lower after 1 year of follow-up. CONCLUSION: Compared to previously published registries from India, the GARFIELD-AF registry describes clinical profiles and outcomes in Indian patients with AF of a different etiology. The registry data show that compared to the rest of the world, Indian AF patients are younger in age and have more diabetes and CAD. Patients with a higher stroke risk are more likely to receive anticoagulation therapy with VKA but are underdosed compared with the global average in the GARFIELD-AF. CLINICAL TRIAL REGISTRATION-URL: http://www.clinicaltrials.gov. Unique identifier: NCT01090362

Standard scores correlation based off-line signature verification system

The fact that the signature is widely used as a means of personal verification emphasizes the need for a signature verification system. In this paper, Standard Scores Correlation based Off-line Signature Verification (SSCOSV) System is presented. The comparison is made on the basis of Pixel density and geometric feature points. Before extracting the features, preprocessing of a scanned signature image is performed to isolate the signature part and to remove any spurious noise present. The concept of Correlation is used to compare the genuine signature with the test signature. If the value of Correlation Coefficient is greater than the predefined threshold (corresponding to minimum acceptable degree of similarity), the test signature is verified to be that of the claimed subject else detected as a forgery. It is found that the values of FAR, FRR and EER for optimal threshold correlation are better compared to that of existing systems. © 2009 IEEE

Efficient off-line signature verification by correlation of geometric centers

he signature verification system is widely used as a means of personal authentication. In this paper, we present Efficient Off-line Signature Verification by correlation of Geometric Centers (OSV-CGC). The noise reduction, resizing and skeletonization are performed on the scanned signature image to extract the features efficiently. The signature is split vertically and horizontally based on the number of black pixels to generate the geometric centers, which constitute the features. The Correlation is used to compare the genuine signature with the test signature. If the value of Correlation Coefficient is greater than the predefined threshold, the test signature is verified to be that of the claimed subject else detected as a forgery. It is found that the values of FAR, FRR and EER for optimal threshold correlation are better compared to the existing techniques. Keywords: Biometrics, Off-line Signature Verification, Geometric