汉字识别中以词为分类单位的分类器研究

汉字识别中,以往的分类器设计都是以字为单位的“字分类器”。字分类器的输出总是与待识字结构相似的一个侯选字集合。这是使后级识别容易产生误识的主要原因。为克服字分类器的缺点,本文给出了以词为单位的词分类器设计的策略与方法,并实验验证了词分类器在分类率及分类速度方面均优于字分类器。

Study on Phrase Classifier in Chinese Character Recognition

In Chinese Character Recognition,the classifier was designed as word classifier whose classification unit is a word in the past.The output of word classifier is always a set of candidate words that are similar with await-recognised words in structure of word.It is the primary reason that make mistakes in post-level recognition. To overcome disadvantage of word classifier, the strategy and method of phrase classifier designing whose classification unit is phrase are proposed. The experiments results prove that phrase classifier is superior to word classifier in rate and speed of classification.