A Fast Watershed-Based Image Segmentation Algorithm Using Local Merging Strategy

In this paper, a fast watershed-based image segmentation algorithm is proposed. Firstly, a homogeneity gradient image named after H-image is produced, and then the traditional watershed segmentation is used to initially segment the H-image to produce over-segmented image regions (objects), and at last local optimum merging strategy is utilized to merge neighbor regions to construct a hierarchical network of image objects according to different scales. Textural, color and shape information of segments is utilized in the merging process. Experiments demonstrate the validity of the algorithm proposed in this paper.