Eaves are precious Chinese heritage which possess profound historical and cultural significance. However

eaves' characters images have obvious characteristics of high wear resistance

high noise and complex topology. In order to achieve eaves' characters recognition and make a contribution to digital protection of cultural heritage objects

a new Method based on improved gradient vector flow field is proposed to extract skeleton of eaves' characters. The algorithm proposed in this paper is based on classic level set Methods which are usually implemented by fast matching Method. What is different is that traditional medial function of level set Method is replaced by gradient vector flow based medial function

which is more automatic and accurate. It is also the innovation point of this paper. The new algorithm is mainly achieved by two wave propagations. Experiments verify the effectiveness and accuracy of the algorithm. The skeleton is 98.03% similar to the standard skeleton of specific models constructed by Matlab2012a. when Gaussian

multiplicative

salt and pepper noise are added into the image

we got a skeleton 99.15% similar to the former one without any noise in it. Improved level set Method surpasses Hilditch thinning algorithm and distance transform algorithm and gets the best skeleton of eaves' characters

which is homotopy

thinness

centered and smoothness. The Results of the experiments indicate that our algorithm proves to be a useful and effective technique to extract skeleton of 2D objects with complex topology.