A combination method of two classifiers based on the information of confusion matrix

Abstract

This paper describes some of research results related to the development of a character recognizer appropriate for fast handwritten Korean address reading. Our goal is to design a handwritten Korean character recognizer retaining the following three characteristics: reliable recognition scores indicating probability, high speed, and naturally acceptable cumulative recognition rates. We have adopted two statistical classifiers to satisfy the first characteristic and proposed methods coupling the two classifiers to meet the second and third ones. The superiority of the proposed combination methods has been proven through experiments done with the PE92 database.