A method for spine segmentation based on adaptive mathematical morphology was proposed in order to increase the correct rate of Pyrrophyta recognitioa At first, the pixel-width was introduced, and the optimal structure element was computed by pixel-width histogram and area distribution automatically,and then the spine was extracted by mixed mathematical morphology operations. Finally, two kinds of local biological morphology feature parameters were constructed and their visual invariance was proved. The experiments results show that the optimal structure element can be computed by different Pyrrophyta cell and this method is of high precision and fast speed.%为了提高藻种显微图像识别率,提出了一种基于自适应形态学的快速藻种顶刺分割和特征提取方法.该方法引入像素宽度的概念,以藻种目标像素宽度直方图和面积分布图为判别依据,自动判定最佳结构元尺寸,以联合滤波、区域归并等形态学操作分割顶刺区域;最后构造了两类局部生物形态学特征提取参数.实验证明,该算法针对不同甲藻细胞目标可自动计算最佳结构元素大小,具有精度高、速度快的优点,且两类特征提取参数具有视觉不变性.
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