Binary images of machine-printed characters are essentially graphical objects composed of nodes (extremes, intersections) and lines connecting them. Provided distinction is made between straight lines and curves, this is a fair representation of individual characters. Only a few carefully located pixels convey the most significant part of the information concerning the curvature of the path connecting two nodes. These pixels may be thought of as additional nodes connected by straight lines in a graph that represents the machine-printed character. In this paper, a character is represented by nodes (character extremes, intersections and additional nodes replacing curves) and straight lines connecting them. This graphical object carries two kinds of information about the character that is represented: geometric information concerning the location of nodes with the relative length and orientation of the connecting lines, and the topological information about the existing connections between different pairs of nodes given by the connectivity matrix or a corresponding graph. Due to its geometric properties, this object can be used for character recognition by template matching, which is insensitive to broken characters caused by missing (or parasite) pixels. On the other hand, its graph, as a mathematical object, can be used for structure based optical character recognition, so that the character can be recognized under wide variations in character styles. Combining template matching of graphs as geometric objects with spectral distance of graphs meant as sets of relations between nodes and edges, seems to be a promising way to achieve high accuracy multifont character recognition. The procedure to obtain the graph representation of machine-printed characters is based on morphological processing of their binary images.