Combining Sources of Evidence to Resolve Ambiguities in Toponym Recognition in Cartographic Maps

Graphical documents such as cartographic maps contain a great variety of textual elements appearing in different spatial positions, in different fonts, sizes, and colors, touching and overlapping graphical symbols. This greatly complicates automatic optical recognition of such textual elements in the process of raster-to-vector conversion of graphical documents. In this work, we propose a method that combines OCR-based text recognition in rasterscanned maps with heuristics specially adapted for cartographic data to resolve the recognition ambiguities using various sources of evidence. Our goal is to form in the vector thematic layers geographically meaningful words correctly attached to the cartographic objects.