计算机科学 ›› 2013, Vol. 40 ›› Issue (1): 282-285.

• 图形图像与模式识别 • 上一篇    下一篇

基于组件树滤波及快速区域合并的分水岭分割算法

闫沫   

  1. (西安电子科技大学雷达信号处理国家重点实验室 西安710071)
  • 出版日期:2018-11-16 发布日期:2018-11-16

Watershed Algorithm Based on Image Filtering by Using Component Tree and Fast Region Merging

  • Online:2018-11-16 Published:2018-11-16

摘要: 针对分水岭算法存在过分割的问题,提出一种结合组件树滤波及快速区域合并的图像分割算法。该算法在 图像预处理阶段利用组件树来表示梯度图像且根据顺序极值计算分水岭的相对势能和属性,并对其进行滤波,从而减 少梯度图像中的局部极小值。对滤波后的梯度图像进行分水岭初始分割,然后利用完美场景准则对初始分割结果进 行快速区域合并。实验结果表明,采用组件树对梯度图像进行滤波能够减少由于噪声而产生的局部极小值,大大减少 了分水岭初始分割区域数量,提高了区域合并的准确性,加快了合并速度。

关键词: 图像分割,分水岭,组件树,相对势能,区域合并

Abstract: An image segmentation algorithm combined with image filtering by using component tree and fast region merging was proposed to deal with over-segmentation. Firstly, the component tree was used to represent the gradient image, the relative potential energy and its properties were computed according to the ordered extremism. Then the gra- dicnt image was filtered to reduce the local minima in preprocessing stage. Then, the watershed algorithm was applied to the filtered gradient image to get the pr}segmentation result. Finally, a fast region merging algorithm was used to merge the prcsegmentation regions based on the perfect scene criterion to get the final segmentation. Experimental re- sups show that image filtering by using component tree can reduce the local minima disc to the noise and reduce the o- ver-segmentation. It can help improve the region merging accuracy and processing speed greatly.

Key words: Image segmentation, Watershed, Component tree, Relative potential energy, Region merging

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