基于自适应标记提取的分水岭彩图分割算法

针对分水岭算法过分割问题，提出一种基于自适应提取标记的改进算法。该算法结合极小值深度和汇水盆地尺度信息提取与物体相关的极小值标记，根据梯度图像中极值点的统计信息自适应设定标记提取的阈值。提取到的标记采用形态学极小值标定技术强制作为原始梯度图像的极小值，在修改过的梯度图像上进行分水岭分割。仿真结果表明，该算法能有效解决分水岭算法的过分割问题，具有更强的抗噪性能和边缘定位能力，且计算复杂度较小。

Watershed Algorithm for Color Image Segmentation Based on Adaptive Marker-extraction

An adaptive marker extraction-based watershed algorithm is proposed to overcome the over-segmentation problem. By combining local minima depth and water basin scale information, markers are adaptively extracted for local minima, and the threshold for marker-extraction is automatically calculated according to the statistics of local extreme points in the gradient map. These markers are imposed on the original gradient map as its local minima. The watershed algorithm is applied on the modified gradient map to segment the image. Simulation results show that the proposed method can efficiently reduce over-segmentation with scarcely computational complexity increase. It has better anti-noise performance and edge-location capability as well.