A Gradient Vector Flow-Based Method for Video Character Segmentation

In this paper, we propose a method based on gradient vector flow for video character segmentation. By formulating character segmentation as a minimum cost path finding problem, the proposed method allows curved segmentation paths and thus it is able to segment overlapping characters and touching characters due to low contrast and complex background. Gradient vector flow is used in a new way to identify candidate cut pixels. A two-pass path finding algorithm is then applied where the forward direction helps to locate potential cuts and the backward direction serves to remove the false cuts, i.e. those that go through the characters, while retaining the true cuts. Experimental results show that the proposed method outperforms an existing method on multi-oriented English and Chinese video text lines. The proposed method also helps to improve binarization results, which lead to a better character recognition rate.