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Image segmentation with complicated background by using seeded region growing

机译:利用种子区域增长技术进行复杂背景图像分割

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摘要

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.
机译:这项研究提出了一种新颖的基于种子区域增长的图像分割方法,用于彩色和灰度图像中的复杂背景。提出的仅检测连通边缘的模糊边缘检测方法与模糊图像像素相似度结合使用,可以自动选择初始种子,而无需考虑细节和复杂背景。模糊距离用于确定结果区域增长中像素和区域之间的差异以及区域合并中两个区域之间的差异。在这项研究中,对常规区域生长进行了修改,以确保边缘像素比其他像素晚处理。最后,通过仿真研究证明了该方法优于现有的其他分割方法。

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