In process of recognizing Chinese handwritten text, Chinese character segmentation is the key point of the recognition. Therefore, study on how to segment Chinese characters effectively plays an important role in improving the overall performance of Chinese character recognition system. This paper researches and improves algorithms in process of segmenting Chinese handwritten text. First, after image binarization processing and smooth filtering, a multi-step extract algorithm for searching nonlinear row is presented, segmenting text image into character rows. After that, segment single Chinese characters from character rows by modified Viterbi algorithm, stroke analysis and other algorithms. The paper mainly addresses the issues of row overlapping, non-touching character segmentation, touching character segmentation in process of segmentation and emerging of excessive segmentation. The experimental results show that the segmentation algorithm presented in this paper has a high anti-interference capability and a good stability, and its accuracy rate is higher.