Recognizing handwritten Chinese characters by stroke segment matching

[[abstract]]The problem of handwritten Chinese character recognition is solved by matching character stroke segments using an iteration scheme. Length and orientation similarity properties, and coordinate overlapping ratios are used to define a measure of similarity between any two stroke segments. Based on the concept of at-most-one to one mapping, an iteration scheme is employed to adjust the match relationships, using the contextual information implicitly contained in the match network, so that the match relationships can get into a stable state. The experimental results show that the proposed approach is effective. For recognition of Chinese characters written by a specific person, the recognition rate is about 96%. If the characters of the first three ranks are checked in counting the recognition rate, the rate rises to 99.6%