Image segmentation with complicated background by using seeded region growing
This study proposes a novel seeded region growing based image segmentation method for complicated background in both color and gray level images. The proposed fuzzy edge detection method, that only detects the connected edge, is used with fuzzy image pixel similarity to automatically select the initial seeds not in the detail and complicated background. The fuzzy distance is used to determine the difference between the pixel and region in the consequent region growing and the difference between two regions in the region merging. The conventional region growing is modified in this study to ensure that the pixel on the edge is processed later than other pixels. Finally, the simulations in study prove that the proposed method is better than other existing segmentation methods.
image segmentation seeded region growing gray level image edge detection fuzzy theory color image