Resolving the semantic heterogeneity problem is crucial to allow interoperability between ontology-based systems. Ontology matching based on argumentation is an innovative research area that aims at solving this issue, where agents encapsulate different matching techniques and the distinct mapping results are shared, compared, chosen and agreed. In this paper, we compare three argumentation fra...

When multiple instances of single biometrics can be acquired from a single input simultaneously, a multiple-step acquisition at additional transaction time cost can be avoided. We present a rotation-invariant, peg-free multi-instance Fingerprint and Eigenfinger-based biometric system extracting multiple features from a palmar scan of the hand. Our evaluation targets (a) rankings of individual f...

An ensemble of 2D ear matchers is built by training each matcher using a set of Gabor filters and color spaces selected by a genetic algorithm (GA). First, using gray level images, we select the best Gabor filters applying Sequential Forward Floating Selection. Second, using the RGB images, several color spaces are obtained using a GA. Finally, an ensemble of 1-nearest neighbor matchers use the...

We present a robust and inherently parallel strategy for tracking "corner" features on independently moving (and possibly non-rigid) objects. The system operates over long, monocular image sequences and comprises two main parts. A matcher performs two-frame correspondence based on spatial proximity and similarity in local image structure, while a (racier maintains an image trajectory (and predi...

Ontology matching produces correspondences between entities of two ontologies. The OMReasoner is unique in that it creates an extensible framework for combination of multiple individual matchers, and reasons about ontology matching by using external dictionary WordNet and description logic reasoner. It handles ontology matching in both literal and semantic level, and it makes use of the semanti...