Watershed segmentation based on gradient images usually has over segmentation result. To solve over segmentation problem

we propose a new Hierarchical image segmentation method based on Watershed filling and Overlap rate measuring (HWO). Firstly

we transform RGB color space to Lab and statistic the histogram according to a and b dimensions. The watershed segmentation algorithm is applied to 2D histogram and the initial segmentation result is achieved. Then

we associate the segmentation region with the Gaussian distributing

and estimate the parameter value. Finally

we measure the Overlap rate for a hierarchical region merging and get the final result. In the experiment

the two parameters are determined. We then evaluate the segmentation performance with a standard database of human segmented natural images. Results show our method can efficiently solve over segmentation problem

and the combined value of precision and recall measures is 0.609

while is 0.79 when the segmentation is done manually. In addition

the new method also has much less computing complexity.