Handwritten numeral recognition using flexible matching based on learning of stroke statistics

The purpose of this study is to learn shapes and structures of a given learning set of handwritten numerals and to develop a flexible matching method for recognition based on the learning. First, this paper proposes a method of how to obtain a set of standard character patterns and the ranges of variations varying statistically from the given learning character samples. Then the recognition is made as follows: each standard pattern is deformed to match with the input character; and the matching is evaluated by the energy of deformation; and the closeness of the standard pattern to the input.