Recognition of handwritten Chinese address with writing variations

Abstract

Handwritten Chinese address recognition is a challenging task, not only because of the large quantity of Chinese characters and unconstraint of handwriting, but also due to irregularities of various address formats. The existing techniques generally solve the problem by transforming the address database to a large scale character-level-tree (CLT) and then utilizing the nodes of the generated CLT to match with the candidate patterns. However, the CLT is unable to cover all the variations of address formats. A more compact tree is proposed in this paper to cover the variations of address formats as many and complete as possible by building the structure tree at word level. Specifically, the segment candidate patterns are firstly recognized by a character classifier, then are mapped to candidate address words by matching with the proposed word-level-tree (WLT) address database. Finally, the address recognition result is obtained in the path matching phase by summing the scores of candidate address words in each match path. The proposed scheme was tested with real mail address images captured by an automatic letter sorting machine. Experimental results have demonstrated that the performance of the proposed WLT based method outperforms the four benchmarking methods.