Abstract: The hybrid pattern recognition systems based on multiple classification models, which are different from the integrated system by voting outputs of multiple classifiers, are addressed in this paper. One of them is the printed chinese character recognition system, and another the unconstrained handwritten digit recognition system. By means of multiple features and multi-stage classification process, discrimination for ambiguous characters, and the novel post-processing stage employing dynamic reference mask matching technique, the performance of both recognition systems is substantially improved as compared with-single classifier system. Experimental results show that hybrid methodology is a promising solution to complex pattern recognition and robustness of a pattern recognition system.