Generating One Biometric Feature from Another: Faces from Fingerprints

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

Discriminative common vector based finger knuckle recognition

The main issue in personal authentication systems for military, security, industrial and social applications is accuracy. This paper presents a finger knuckle print (FKP) recognition approach to identity authentication. It applies a discriminative common vectors (DCV) based method to obtain the unique feature vectors, called discriminative common vectors, and the Euclidean distance as matching strategy to achieve the identification and verification tasks. The recognition process can be divided into the following phases: capturing the image; pre-processing; extracting the discriminative common vectors; matching and, finally, making a decision. In order to test and evaluate the proposed approach both the most representative FKP public databases and an established non-uniform FKP database were used. Experiments with these databases confirm that the DCV-based FKP recognition method achieves the authentication tasks effectively. The results showed the performance of the system in terms of the recognition rate had 100% accuracy for both training data and unseen test data. (C) 2014 Elsevier Inc. All rights reserved

An intelligent face features generation system from fingerprints

In this study, a novel intelligent system based on arti?cial neural networks was designed and introducedfor generating faces from ?ngerprints with high accuracy. The proposed system has a number of modulesincluding two feature enrolment modules for acquiring the ?ngerprints and faces into the system, two featureextractors for extracting the feature sets of ?ngerprint and face biometrics, an arti?cial neural network modulethat was con?gured with the help of Taguchi experimental design method for establishing relationships amongthe biometric features, a face re-constructor for building up face features from the results of the system, anda test module for test the results of the system. 10-fold cross validation technique was used for evaluatingthe performance of the system. The results have shown that the face features can be successfully generatedfrom only ?ngerprints. It can be concluded that the proposed study signi?cantly and directly contributes tobiometrics and its new applications.</div

Intelligent Face Mask Prediction System

Biometric based person identification systems are used to provide alternative solutions for security. Although many approaches and algorithms for biometric recognition techniques have been developed and proposed in the literature, relationships among biometric features have not been studied in the field so far. In this study, we have analysed the existence of any relationship between biometric features and we have tried to obtain a biometric feature of a person from another biometric feature of the same person. Consequently, we have designed and introduced a new and intelligent system using a novel approach based on artificial neural networks for generating face masks including eyes, nose and mouth from fingerprints with 0.75-3.60 absolute percent errors. Experimental results have demonstrated that it is possible to generate face masks from fingerprints without knowing any information about faces. In addition it is shown that fingerprints and faces are related to each other closely. In spite of the proposed system is initial study and it is still under development, the results are very encouraging and promising. Also proposed work is very important from view of the point that it is a new research area in biometrics

Quality of life in children with chronic kidney disease (with child and parent assessments)

WOS: 000278951200013PubMed ID: 20383649Herein the results of a multicenter study from the Turkish Pediatric Kidney Transplantation Study Group are reported. The aims of this study were to compare the quality of life (QoL) scores of Turkish children who are dialysis patients (DP), renal transplant recipients (TR), and age-matched healthy controls and to compare child-self and parent-proxy scores. The Turkish versions of the Kinder Lebensqualitat Fragebogen (KINDLA (R)) questionnaires were used as a QoL measure. The study group consisted of 211 children and adolescents with chronic kidney disease (CKD) (139 TR and 72 DP aged between 4-18 years; 13.7 A +/- 3.5 years) from 11 university hospitals, 129 parents of these patients, 232 age-matched healthy children and adolescents (aged between 4-18 years; 13.1 +/- 3.5 years) and 156 of their parents. Patients with CKD had lower scores in all subscales except for physical well-being than those in the control group. TR had higher scores in physical well-being, self-esteem, friends' subscales, and total scores than DP. Child-self scores were lower than parent-proxy scores, especially in CKD, DP, and control groups. Concordance between parent-proxy and child-self reports in the TR, DP, CKD, and control groups was only moderate for the majority of subscales (r = 0.41-0.61). It was concluded that parent-proxy scores on the QoL were not equivalent to child-self scores and that evaluating both children's and parents' perspectives were important. Additionally, psychosocial counseling is crucial not only for patients with CKD but also for their parents