In this paper we present two modified and improved versions of the formerly published Fuzzy-Based Single-Stroke Character Recognizer (FUBAR) algorithm. After introducing the original method, the study investigates the effects of two different improvements of the designed algorithm. The first extension is the use of symbol-dependent fuzzy grids to extract symbol features; the second one is the use of rule weights in hierarchical rule-bases. The accuracy and efficiency of the extended FUBAR algorithms are compared to previous results. © 2013 IEEE.