A candidate reduction method for handwritten Kanji character recognition

This paper describes a method for reducing the number of candidates in Kanji character recognition. Such reduction is vital to increasing the speed of such applications as Kanji address recognition. Further, it also reduces the probability of misreadings in linguistic postprocessing. First, we define a confidence value by which we can express the potential correctness of recognition candidates. Next, we define "accumulated confidence value" and use it as a measure to express a threshold for candidate acceptance in Kanji character recognition. The efficiency of the proposed method is evaluated in an experiment using IPTP CD-ROM2 Japanese address images. Results show that a roughly 31% reduction in the number of candidates was obtained without reducing the number of correct candidates