Enhanced Fuzzy Feature Match Algorithm for Mehndi Fingerprints

The performance of biometric system is degraded by the distortions occurred in finger print image acquisition. This paper focuses on nonlinear distortions occurred due to �Mehndi / Heena drawn on the palm/fingers. The present invention is to detect and rectify such distortions using feedback paradigm. If image is of good quality, there is no need to renovate features. So, quality of whole image is checked by generating exponential similarity distribution. Quality of local region is checked by the ridge continuity map and ridge clarity map. Then, we check whether feedback is needed or not. The desired features such as ridge structure, minutiae point, orientation, etc. are renovated using feedback paradigm. Feedback is taken from top K matched template fingerprints registered in the database. Fuzzy logic handles uncertainties and imperfections in images. For matching, we have proposed the Enhanced Fuzzy Feature Match (EFFM) for estimating triangular feature set of distance between minutiae, orientation angle of minutiae, angle between the direction of minutiae points, angle between the interior bisector of triangle and the direction of minutiae, and a minutiae type. The proposed algorithm incorporates an additional parameter minutiae type that assists to improve accuracy of matching algorithm. The experimentation on 300 Mehndi fingerprints acquired using Secugen fingerprint scanner is conducted. The results positively support EEFM for its efficiency and reliability to handle distorted fingerprints matching

Fingerprint Recognition with Identical Twin Fingerprints

Fingerprint recognition with identical twins is a challenging task due to the closest genetics-based relationship existing in the identical twins. Several pioneers have analyzed the similarity between twins' fingerprints. In this work we continue to investigate the topic of the similarity of identical twin fingerprints. Our study was tested based on a large identical twin fingerprint database that contains 83 twin pairs, 4 fingers per individual and six impressions per finger: 3984 (83*2*4*6) images. Compared to the previous work, our contributions are summarized as follows: (1) Two state-of-the-art fingerprint identification methods: P071 and VeriFinger 6.1 were used, rather than one fingerprint identification method in previous studies. (2) Six impressions per finger were captured, rather than just one impression, which makes the genuine distribution of matching scores more realistic. (3) A larger sample (83 pairs) was collected. (4) A novel statistical analysis, which aims at showing the probability distribution of the fingerprint types for the corresponding fingers of identical twins which have same fingerprint type, has been conducted. (5) A novel analysis, which aims at showing which finger from identical twins has higher probability of having same fingerprint type, has been conducted. Our results showed that: (a) A state-of-the-art automatic fingerprint verification system can distinguish identical twins without drastic degradation in performance. (b) The chance that the fingerprints have the same type from identical twins is 0.7440, comparing to 0.3215 from non-identical twins. (c) For the corresponding fingers of identical twins which have same fingerprint type, the probability distribution of five major fingerprint types is similar to the probability distribution for all the fingers' fingerprint type. (d) For each of four fingers of identical twins, the probability of having same fingerprint type is similar

Robocrystallographer: Automated crystal structure text descriptions and analysis

Our ability to describe crystal structure features is of crucial importance when attempting to understand structure-property relationships in the solid state. In this paper, the authors introduce robocrystallographer, an open-source toolkit for analyzing crystal structures. This package combines new and existing open-source analysis tools to provide structural information, including the local coordination and polyhedral type, polyhedral connectivity, octahedral tilt angles, component-dimensionality, and molecule-within-crystal and fuzzy prototype identification. Using this information, robocrystallographer can generate text-based descriptions of crystal structures that resemble descriptions written by human crystallographers. The authors use robocrystallographer to investigate the dimensionalities of all compounds in the Materials Project database and highlight its potential in machine learning studies

State of the Art in Biometric Key Binding and Key Generation Schemes

Direct storage of biometric templates in databases exposes the authentication system and legitimate users to numerous security and privacy challenges. Biometric cryptosystems or template protection schemes are used to overcome the security and privacy challenges associated with the use of biometrics as a means of authentication. This paper presents a review of previous works in biometric key binding and key generation schemes. The review focuses on key binding techniques such as biometric encryption, fuzzy commitment scheme, fuzzy vault and shielding function. Two categories of key generation schemes considered are private template and quantization schemes. The paper also discusses the modes of operations, strengths and weaknesses of various kinds of key-based template protection schemes. The goal is to provide the reader with a clear understanding of the current and emerging trends in key-based biometric cryptosystems

Protection of privacy in biometric data

Biometrics is commonly used in many automated veri cation systems offering several advantages over traditional veri cation methods. Since biometric features are associated with individuals, their leakage will violate individuals\u27 privacy, which can cause serious and continued problems as the biometric data from a person are irreplaceable. To protect the biometric data containing privacy information, a number of privacy-preserving biometric schemes (PPBSs) have been developed over the last decade, but they have various drawbacks. The aim of this paper is to provide a comprehensive overview of the existing PPBSs and give guidance for future privacy-preserving biometric research. In particular, we explain the functional mechanisms of popular PPBSs and present the state-of-the-art privacy-preserving biometric methods based on these mechanisms. Furthermore, we discuss the drawbacks of the existing PPBSs and point out the challenges and future research directions in PPBSs