A Multi-scale Text Line Segmentation Method in Freestyle Handwritten Documents

Text lines in free-style handwritten documents are often curved, touch or overlap with each other, which presents a challenge for text line segmentation. In this paper, we proposed a novel text line segmentation method that utilizes the advantages of algorithms in both the small scale and large scale. A path is dynamically detected between each pair of neighboring text lines to separate them. During the process, the line-separating path's coordinate in each step is determined by a three-stage multi-scale method that combines (1) a simple local minima search algorithm, (2) the technique based on following the contour of the foreground component and (3) the piecewise projection profile. Without training, our method has achieved a high segmentation accuracy on plenty of samples, which proves its strong adaptability to various line conditions. Experimental results show that the proposed method outperforms traditional methods.