Comparison of the Minutiae Quadruplets and Minutiae Triplets Techniques

Identifying distorted ngerprint images is a major problem in ngerprint recog-nition systems. Several techniques, such as the minutiae triplets technique, have been proposed for minutiae matching and indexing. The minutiae triplets technique however is largely aected by minutiae distortions and occlusions and hence can rarely produce a stable feature set. In this paper, the characteristics of the minutiae quadruplets and the minutiae triplets structures are compared. The minutiae quadruplet technique is proposed as a better technique because the features are robust to minutiae distortions and occlusions and it eliminates the known drawbacks of the minutiae triplet technique

Indexing techniques for fingerprint and iris databases

This thesis addresses the problem of biometric indexing in the context of fingerprint and iris databases. In large scale authentication system, the goal is to determine the identity of a subject from a large set of identities. Indexing is a technique to reduce the number of candidate identities to be considered by the identification algorithm. The fingerprint indexing technique (for closed set identification) proposed in this thesis is based on a combination of minutiae and ridge features. Experiments conducted on the FVC2002 and FVC2004 databases indicate that the inclusion of ridge features aids in enhancing indexing performance. The thesis also proposes three techniques for iris indexing (for closed set identification). The first technique is based on iriscodes. The second technique utilizes local binary patterns in the iris texture. The third technique analyzes the iris texture based on a pixel-level difference histogram. The ability to perform indexing at the texture level avoids the computational complexity involved in encoding and is, therefore, more attractive for iris indexing. Experiments on the CASIA 3.0 database suggest the potential of these schemes to index large-scale iris databases

Identifying individuals from average quality fingerprint reference templates, when the best do not provide the best results !

International audienceThe fingerprint is one of the most used biometric modalities because of its persistence, uniqueness characteristics and ease of acquisition. Nowadays, there are large country-sized fingerprint databases for identification purposes, for border access controls and also for Visa issuance procedures around the world. The objective usually is to identify an input fingerprint among a large fingerprint database. In order to achieve this goal, different fingerprint pre-selection, classification or indexing techniques have been developed to speed up the research process to avoid comparison of the input fingerprint template against each fingerprint in the database. Although these methods are fairly accurate for identification process, we think that all of them assume the hypothesis to have a good quality of the fingerprint template for the first step of enrollment. In this paper, we show how the quality of reference templates can impact the performance of identification algorithms. We collect information and implement differents methods from the state of the art of fingerprint identification. Then, for these differents methods, we vary the quality of reference templates by using NFIQ2 metric quality. This allowed us to build a benchmark in order to evaluate the impact of these different enrollment scenarios on identification

OrChem - An open source chemistry search engine for Oracle®

<p>Abstract</p> <p>Background</p> <p>Registration, indexing and searching of chemical structures in relational databases is one of the core areas of cheminformatics. However, little detail has been published on the inner workings of search engines and their development has been mostly closed-source. We decided to develop an open source chemistry extension for Oracle, the de facto database platform in the commercial world.</p> <p>Results</p> <p>Here we present OrChem, an extension for the Oracle 11G database that adds registration and indexing of chemical structures to support fast substructure and similarity searching. The cheminformatics functionality is provided by the Chemistry Development Kit. OrChem provides similarity searching with response times in the order of seconds for databases with millions of compounds, depending on a given similarity cut-off. For substructure searching, it can make use of multiple processor cores on today's powerful database servers to provide fast response times in equally large data sets.</p> <p>Availability</p> <p>OrChem is free software and can be redistributed and/or modified under the terms of the GNU Lesser General Public License as published by the Free Software Foundation. All software is available via <url>http://orchem.sourceforge.net</url>.</p

A Review of Fingerprint Feature Representations and Their Applications for Latent Fingerprint Identification: Trends and Evaluation

Latent fingerprint identification is attracting increasing interest because of its important role in law enforcement. Although the use of various fingerprint features might be required for successful latent fingerprint identification, methods based on minutiae are often readily applicable and commonly outperform other methods. However, as many fingerprint feature representations exist, we sought to determine if the selection of feature representation has an impact on the performance of automated fingerprint identification systems. In this paper, we review the most prominent fingerprint feature representations reported in the literature, identify trends in fingerprint feature representation, and observe that representations designed for verification are commonly used in latent fingerprint identification. We aim to evaluate the performance of the most popular fingerprint feature representations over a common latent fingerprint database. Therefore, we introduce and apply a protocol that evaluates minutia descriptors for latent fingerprint identification in terms of the identification rate plotted in the cumulative match characteristic (CMC) curve. From our experiments, we found that all the evaluated minutia descriptors obtained identification rates lower than 10% for Rank-1 and 24% for Rank-100 comparing the minutiae in the database NIST SD27, illustrating the need of new minutia descriptors for latent fingerprint identification.This work was supported in part by the National Council of Science and Technology of Mexico (CONACYT) under Grant PN-720 and Grant 63894