A method of watershed segmentation using the edge gradient combined with distance transformation for segmentation of microscopic images is proposed. This method aims to solve the problem of cell extraction and segmentation of overlapped cells. First

a topographic map from the binary image of cells is generated by transforming distance

after which the local extreme point or set of points are used as the marks of foreground and the first time distance watershed transformation is processed. Then

the resulting watershed ridge line from the previous step is used as the mark of the background region

and the mark of foreground is unchanged. The gradient magnitude is used as the topographic map so that the gradient watershed transformation is achieved

after which the results of segmentation are obtained. Before the two watershed transformations are achieved

the method of mandatory minimum value is used to modify the topographic map so that controlling the local minimum value in the topographic map can only be done within the region of the selected mark. The resulting ridgeline is used as the mark of the background in gradient watershed transformation

which can effectively separate the adhesion target. This method not only retains the advantages of edge positioning accuracy in watershed transform based on gradient images

but also solves the problems of adhesion objectives that cannot be segmented or adhesion objective that is oversegmented. As verified by many clinical image segmentation experiments

the method can extract the cells from the images and segment the overlapped cells automatically. Thus

the method successfully meets the requirements of medical image segmentation.