earticle

영어

The image segmentation technology is of great significance to the target identification. The watershed segmentation algorithm has wide application in image segmentation. The traditional watershed segmentation often causes the problems of over segmentation and noise sensitivity. Therefore, a medical image segmentation algorithm is proposed based on K-means clustering algorithm and improved watershed algorithm. First, K - means clustering algorithm is used for initial segmentation, and then the concept of similarity is put forward to improve the original watershed algorithm. Finally, the adjacent tiles of the initial segmentation is merged. The magnetic resonance image is regarded as the segmentation object. The experimental result shows that the proposed algorithm effectively solves the problem of the over-segmentation of traditional watershed algorithm, and achieves a satisfactory effect for the image segmentation.