Elias N. Zois

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Writer identi"cation is carried out using handwritten text. The feature vector is derived by means of morphologically processing the horizontal pro"les (projection functions) of the words. The projections are derived and processed in segments in order to increase the discrimination e$ciency of the feature vector. Extensive study of the statistical(More)
A fusion approach is proposed for improving the e$ciency of writer veri"cation systems. A short handwritten sentence is employed for this purpose. Each word of the sentence is used to tackle an individual veri"cation problem. Then, the word-level (local) decisions are fused in order to obtain a more reliable global decision by means of the Neyman}Pearson(More)
This work presents the development of an intelligent system able to classify different music genres with increased accuracy. The proposed approach is based on radial basis function (RBF) networks, trained with the non-symmetric fuzzy means particle swarm optimization-based (PSO-NSFM) algorithm. PSO-NSFM, which has been shown to produce highly accurate(More)
This work presents a feature extraction method for writer verification based on their handwriting. Motivation for this work comes from the need of enchancing modern eras security applications, mainly focused towards real or near to real time processing, by implementing methods similar to those used in signature verification. In this context, we have(More)
In this work, a new approach for off-line signature recognition and verification is presented and described. A subset of the line, concave and convex family of curvature features is used to represent the signatures. Two major constraints are applied to the feature extraction algorithm in order to model the two step transitional probabilities of the(More)
We discuss the dynamics of signatures in the light of recent findings in motor learning, according to which a signature is a highly automated motor task and, as such, it is stored in the brain as both a trajectory plan and a motor plan. We then conjecture that such a stored representation does not necessarily include the entire signature, but can be limited(More)
In this paper a feature vector, which has been used for curve coding, is evaluated in case of a signature verification scheme using a real time digital signal processor. The feature extraction method is based on morphologically processing the vertical projections of prescaled signature images. Coding of the curve profiles is carried out using morphological(More)