Malignant melanoma is nowadays one of the most malignant tumors among white-skinned populations around the world. The key element in malignant melanoma treatment is the detection of melanomas and their changes at an early stage, before they develop irreversible clinically significant and potentially fatal damage to the patients. Computer automatic diagnosis of skin lesions using early symptoms would be particularly useful as an aid in primary care. During such computer systems, there is a significant clinical demand for accurate dermatological image registration. In this paper, we introduce a new algorithm for the registration of melanomas in successive dermatological image. We reduce the melanoma registration problem to a bipartite graph matching problem. The Voronoi cells are used to measure the similarity between melanomas and build the weighted bipartite graph. A minimum weight maximum cardinality matching is employed to find the global correspondences between dermatological images. Distances order and dynamic programming method are applied into the bipartite graph matching to preserve topology of melanoma distribution. The dermatoscopy images are used to validate the effectiveness of our approach. Since our method is a general registration method for melanomas, it can also be used in other dermatological images.