To avoid over segmentation produced by watershed segment algorithm, an image segment algorithm based on the adaptive preprocessing is proposed in this paper.
为了防止分水岭算法过分割问题，该文提出了一种基于自适应预处理的图像分割算法。
But the traditional watershed transformation has a serious problem of over segmentation, and noise of the image and fake textures may submerge the wanted edge information.
但传统分水岭变换过分割问题严重，图像的噪声和虚假纹理会淹没真正想得到的边缘信息。
Experiment results of over-segmentation, under-segmentation and incorrect segmentation rates show that DCMIS has better validity and correctness than DENCLUE and FCM for medical image segmentation.
实验结果中的欠分割率、过分割率和错误分割率表明DCMIS比DENCLUE和FCM算法有更好的性能和较好的医学图像分割效能。
Due to noise and irregularity of the gradient image, watershed algorithm used to segment images generally leads to over-segmentation, which is unacceptable.
分水岭算法用于图像分割时通常由于噪声的存在和梯度的不规则造成过度分割。
In the application of the image segmentation, the new model solves the over-segmentation of the original Fuzzy ART neural network algorithm due to the vigilance's increase.
将该模型应用于图像分割，解决了传统模糊art网络图像分割结果随警戒参数的升高而出现的过度分割。
This paper suggests an improved marker-based watershed image-segmentation method to reduce the over-segmentation of the watershed algorithm.
为了降低分水岭算法的过分割问题，提出一种新改进的基于标记的分水岭图像分割方法。
The experimental results show that the proposed method is feasible and can give better image segmentation. It does not only avoid the over-segmentation, but also preserves the edge information.
实验结果表明此方法是可行的，既减少了分水岭变换的过分割现象，又较好地保持了图像中的边缘信息，能得到良好的分割效果。
The result shows that the image is effectively segmented without over-segmentation.
结果表明，该算法分割效果较好，无过分割情况。
The result shows that the image is effectively segmented without over-segmentation.
结果表明，该算法分割效果较好，无过分割情况。
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