Image segmentation is important for identifying targets in images. A new algorithm was created to improve the watershed segmentation method, which tends to over-segment and be sensitive to noise. The new algorithm combines K-means clustering with watershed segmentation, resulting in better segmentation of image targets. The experimental results show that this new algorithm effectively solves the over-segmentation issue and accurately segments image targets.