An improved image segmentation algorithm based on the watershed transform

Xuemei Cui, Guowei Yang, Yan Deng, Shaolong Wu
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引用次数: 7

Abstract

The watershed transform has a good response to the weak edge, but it is unable to obtain meaningful segmentation results directly by using the watershed transform to the phenomenon of excessive segmentation in image segmentation. A new segmentation algorithm base on improved watershed algorithm is proposed in this paper. By the different marks on the foreground and background objects, we can obtain better effect of segmentation with the application of watershed algorithm. Through the study of the characteristics of gradient image and morphological open close function reconstruction operations in image processing, a new tag extraction method will be designed by the new algorithm, which is by using the method of opening and closing by reconstruction operators to obtain marks and by controlling the closed reconstruction of structural elements in order to interested in the gradient image area the size of the tag. Then, extracted tag using morphological minimum calibration technology forces as an original local minimum value of the gradient image, and shields the original all local minimum value in the gradient image. In the end, watershed which is modified by the gradient of the image will have a image segmentation, in such aspects as outline eliminate over-segmentation and regional positioning have a very good segmentation effect.
一种改进的分水岭变换图像分割算法
分水岭变换对弱边缘有很好的响应,但对图像分割中的过度分割现象直接使用分水岭变换无法得到有意义的分割结果。提出了一种基于改进分水岭算法的分割算法。利用前景和背景物体上的不同标记,应用分水岭算法可以获得较好的分割效果。通过研究梯度图像的特点和图像处理中的形态学开闭函数重构操作,采用新算法设计了一种新的标签提取方法,即利用重构算子的开闭方法获取标记,通过控制结构元素的闭合重构来对梯度图像区域的标签大小感兴趣。然后,利用形态最小标定技术提取标签作为梯度图像的原始局部最小值,并屏蔽梯度图像中原始的所有局部最小值。最后,通过对图像的梯度进行修改后的分水岭进行图像分割,在轮廓消除过分割和区域定位等方面都有很好的分割效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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