Single-character type identification

Different character recognition problems have their own specific characteristics. The state-of-art OCR technologies take different recognition approaches, which are most effective, to recognize different types of characters. How to identify character type automatically, then use specific recognition engines, has not brought enough attention among researchers. Most of the limited researches are based on the whole document image, a block of text or a text line. This paper addresses the problem of character type identification independent of its content, including handwritten/printed Chinese character identification, and printed Chinese/English character identification, based on only one character. Exploiting some effective features, such as run-lengths histogram features and stroke density histogram features, we have got very promising result. The identification correct rate is higher than 98% in our experiments.