Writer Style from Oriented Edge Fragments

In this paper we evaluate the performance of edge-based directional probability distributions extracted from handwriting images as features in forensic writer identification in comparison to a number of non-angular features. We compare the performances of the features on lowercase and uppercase handwriting. In an effort to gain location-specific information, new versions of the features are computed separately on the top and bottom halves of text lines and then fused. The new features deliver significant improvements in performance. We report also on the results obtained by combining features using a voting scheme

Handwritten word image matching based on heat kernel signature

10.1007/978-3-642-40246-3_6Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)8048 LNCSPART 242-4

Automated Incremental Building of Weighted Semantic Web Repository

The chapter introduces an incremental algorithm creating a selforganizing repository and it describes the processes needed for updates and inserts into the repository, especially the processes updating estimated structure driving data storage in the repository. The process of building repository is foremost aimed at allowing the well-known Semantic web tools to query data presented by the current web sources. In order to respect features of current web documents, the relationships should be at least weighted by an additional indirect criteria, which allow the query result to be sorted accordingly to an estimated quality of data provided by web sources. The relationship weights can be based on relationship soundness or on the reputation of the source providing them. The extension of the relationships by the weights leads to the repository able to return a query result as complete as possible, where (possibly) inconsistent parts are sorted by the relationships weights. © 2009 Springer-Verlag Berlin Heidelberg