A metasynthetic approach for segmenting handwritten Chinese character strings

In this paper, a metasynthetic method is proposed to segment handwritten Chinese character strings. The Viterbi algorithm is firstly applied to search segmentation paths and several rules are used to remove redundant paths. Then a background-thinning method is further adopted to obtain non-linear segmentation paths. If there are not touching characters, a dynamic programming algorithm is applied to merge components. For touching characters, we apply background and foreground information to obtain candidate segmentation paths and the feature vectors are constructed in terms of peripheral features. Then the mixture probabilistic density function whose parameters are obtained by the EM algorithm is used to choose the best segmentation path. Experimental results demonstrate that the proposed scheme effectively segments handwritten Chinese characters and achieves an improvement over previous methods.