Calibration in optical graph recognition

Abstract

Graph drawing is the process of transforming the topological structure of a graph into a graphical representation. Primarily, it maps vertices to points and displays them by icons, and it maps edges to Jordan curves connecting the endpoints. Optical graph recognition (OGR) is the inverse and transforms the digital image of a drawn graph into its topological structure. It consists of four phases: preprocessing, segmentation, topology recognition, and postprocessing. OGR is based on established digital image processing techniques. Its novelty is the topology recognition where the edges are recognized with emphasis on the attachment to their vertices and on edge crossings. Our prototypical implementation OGRup shows the effectiveness of the approach and produces a GraphML file, which can be used for further algorithmic studies and graph drawing tools. It has been tested both on hand made graph drawings and on drawings generated by graph drawing algorithms. Here we report on experiments for the calibration of parameters, which are critical for topology recognition.