1,720,961 research outputs found
Offline signature verification using geometric and orientation features with multiple experts fusion
No full textThis paper reports a weighted fusion of multiple classifiers for offline signature verification using geometric and orientation features. The proposed system uses three different classifiers for identity verification, namely, Gaussian empirical rule, Mahalanobis and Euclidean distance metrics. Initially, Geometric global and local features are extracted from signature image. Further, a novel feature extraction technique is applied to signature image for extraction of orientation features. These feature sets are then fused and make a concatenated feature set which is then passed through the three classifiers. Matching scores obtained from these three classifiers are finally fused using weighted sum rule. The proposed system is tested on IIT Kanpur signature database which consists of 1800 offline signatures. The experimental results are found to be convincing and encouraging. The aim of the proposed system is to provide such a system which can overcome the problem of skilled forgery detection efficiently with less computational complexity
Investigating the Usability of SIFT Features in Biometrics
No full textRecent advancements of biometrics identity verification are growing rapidly in this vastly interconnected techno-savvy society. In this information age, protection of valuable contents from the unauthorised intruders or illegal entry to high security zones has made these biometric systems crucial mechanism towards establishing a robust identity verification system. The thrust for reliable authentication methodologies are increasing due to security consciousness of people and also for growing advancement of civilian infrastructures by means of networking, communication, E-Governance, IT knowledge-based civic environment, etc. In the last two decades, a large number of computational intelligence (CI) based and non-linear synchronization based approaches have been thoroughly investigated in biometric authentication in terms of automatic feature detection, feature matching and association of adaptive parameters to the system. Although, it has been felt that the robust and invariant ways are necessary to process the system development from one biometric application to another. However, some incapable and negative constraints have made these biometric systems lack of inconvenience to a large group of end users. To cope up with these incapable factors in biometric systems successfully, Scale Invariant Feature Transform (SIFT) operator has been thoroughly investigated and proved to be invariant to image rotation, scaling, partly illumination changes, biometric authentication towards efficient identity verification
Maximized posteriori attributes selection from facial salient landmarks for face recognition
No full textThis paper presents a robust and dynamic face recognition technique based on the extraction and matching of devised probabilistic graphs drawn on SIFT features related to independent face areas. The face matching strategy is based on matching individual salient facial graph characterized by SIFT features as connected to facial landmarks such as the eyes and the mouth. In order to reduce the face matching errors, the Dempster-Shafer decision theory is applied to fuse the individual matching scores obtained from each pair of salient facial features. The proposed algorithm is evaluated with the ORL and the IITK face databases. The experimental results demonstrate the effectiveness and potential of the proposed face recognition technique also in case of partially occluded faces
Face Identification Using Local Ternary Tree Pattern Based Spatial Structural Components
No full textThis paper reports a face identification system which makes use of a novel local descriptor called Local Ternary Tree Pattern (LTTP). Exploiting and extracting distinctive local descriptor from a face image plays a crucial role in face identification task in the presence of a variety of face images including constrained, unconstrained and plastic surgery images. LTTP has been used to extract robust and useful spatial features which use to describe the various structural components on a face. To extract the features, a ternary tree is formed for each pixel with its eight neighbors in each block. LTTP pattern can be generated in four forms such as LTTP–Left Depth (LTTP-LD), LTTP–Left Breadth (LTTP-LB), LTTP–Right Depth (LTTP-RD) and LTTP–Right Breadth (LTTP-RB). The encoding schemes of these patterns are very simple and efficient in terms of computational as well as time complexity. The proposed face identification system is tested on six face databases, namely, the UMIST, the JAFFE, the extended Yale face B, the Plastic Surgery, the LFW and the UFI. The experimental evaluation demonstrates the most promising results considering a variety of faces captured under different environments. The proposed LTTP based system is also compared with some local descriptors under identical conditions
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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