This article presents a model of character recognition and the experiments used to develop and test it. The model applies to foveal viewing of blurred or unblurred characters and to tactile sensing of raised characters using the fingerpad. The primary goal of the model is to account for variations in legibility across character sets; a secondary goal is to account for variations in the cell entries of the confusion matrix for a given character set. The model consists of two distinct processing stages. The first involves transformation of each stimulus into an internal representation; this transformation consists of linear low-pass spatial filtering followed by nonlinear compression of stimulus intensity. The second stage involves both template matching of the transformed test stimulus with each of the stored internal representations of the characters within the set and response selection, which is assumed to conform to the unbiased choice model of Luce (1963). Though purely stimulus driven, the model accounts quite well for differences in the legibility of character sets differing in character type, size of character, and number of characters within the set; it is somewhat less successful in accounting for the details of each confusion matrix.