Strokes recovering from static handwriting
This paper presents a novel stroke tracing approach to recovering the strokes from the handwriting images. It is carried out not only based on pixel by pixel, but considering the local relation of handwriting strokes. Firstly the primary skeletons of handwriting are produced through the binarization and thinning. Secondly, after the reliable skeletons and unreliable skeletons are classified based on the width information of handwriting, the strokes segments are obtained by the connecting and tracing on the reliable skeletons. Finally, for making the recovered strokes more natural, the post-processing of tracing is discussed. Experimental results show the effectiveness of the approach.