Stroke segmentation by bernstein-bezier curve fitting

Abstract Stroke segmentation is essential to the recognition of handwritten Chinese characters. Here some new and reliable techniques are proposed. First, the thinning process is applied to each character to obtain the skeleton, then a maximum circle technique is used to remove the spurious branches and merge the split 4- fork points. All possible pairs of stroke segments connected at the same fork point are considered, and the Bernstein-Bezier curve is used to fit each pair to smooth the data and find its trend. Then from the result of this curve fitting we can decide which pair belongs to the same stroke. Finally the inflection points with very small radius of curvature are found, and the stroke segmentation is carried out based on these inflection points. Experiments on some Chinese characters show that the proposed new techniques are reliable and time saving compared with the direction method.