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区域生长的原理SRG

区域生长的基本**是将具有相似性质的像素集合起来构成区域。具体先对每个需要分割的区域找一个种子像素作为生长起点,然后将种子像素和周围邻域中与种子像素有相同或相似性质的像素(根据某种事先确定的生长或相似准则来判定)合并到种子像素所在的区域中。将这些新像素当作新的种子继续上面的过程,直到没有满足条件的像素可被包括进来。这样一个区域就生长成了。 区域生长是一种古老的图像分割方法,最早的区域生长图像分割方法是由Levine等人提出的。该方法一般有两种方式,一种是先给定图像中要分割的目标物体内的一个小块或者说种子区域(seed point),再在种子区域基础上不断将其周围的像素点以一定的规则加入其中,达到最终将代表该物体的所有像素点结合成一个区域的目的;另一种是先将图像分割成很多的一致性较强,如区域内像素灰度值相同的小区域,再按一定的规则将小区域融合成大区域,达到分割图像的目的,典型的区域生长法如T. C. Pong等人提出的基于小面(facet)模型的区域生长法,区域生长法固有的缺点是往往会造成过度分割,即将图像分割成过多的区域

区域生长实现的步骤如下:

  1. 对图像顺序扫描!找到第1个还没有归属的像素, 设该像素为(x0, y0);
  2. 以(x0, y0)为中心, 考虑(x0, y0)的4邻域像素(x, y)如果(x0, y0)满足生长准则, 将(x, y)与(x0, y0)合并(在同一区域内), 同时将(x, y)压入堆栈;
  3. 从堆栈中取出一个像素, 把它当作(x0, y0)返回到步骤2;
  4. 当堆栈为空时!返回到步骤1;
  5. 重复步骤1 - 4直到图像中的每个点都有归属时。生长结束。

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