利用图像分割法，提出了基于图像分割和SVD的数字水印算法。
Using image segmentation, a novel watermarking algorithm based on image segmentation and SVD is proposed.
针对传统的基于方差法的指纹图像分割法存在的问题，提出了一种改进的指纹图像分割算法。
Address the traditional variance-based method for fingerprint image segmentation problems, put forward an improved algorithm for fingerprint image segmentation.
提出了一种基于最大相关准则的图像阈值分割法。该算法比基于最大熵原理的图像分割法更简便。
Based on maximum relativity criterion, a new thresholding algorithm for image segmentation is proposed which is more simple than the thresholding algorithm based on maximum entropy.
我们提出了等高地图分割法用于激光共焦显微生物医学图像分割。
We propose a contour map segmentation method for laser scanning confocal microscopic (LSCM) biomedical images.
最后一种方法是交互分割法，它依赖人工输入来指定所要分割的感兴趣目标，将图像目标从背景中分离出来。
The last is an interactive method separating objects of interest from the background by the user's input specifying the object of interest manually.
本文在介绍了三种具有代表性的图像阈值分割法的基础上，通过对它们的性能进行分析比较，给出了这三种阈值分割法的适用范围。
Based on the representation of three typical thresholding methods for image segmentation and the analysis of their performances, the scope of each method was mentioned.
利用形态学水线区域分割法对图像进行分割，分离目标区域。
Segmenting infrared image by regional method of morphology watershed, the target region can be isolated.
针对红外图像，采用双门限分割法进行图像分割，然后采用分段灰度变换法进行图像增强。
An infrared image processing solution is proposed. It USES bi-threshold method to segment image and enhance the image with segmentation gray scale transform method.
实验结果表明，该修改是可行的，对有些图像相对求和型模糊熵分割法能获得更好的分割效果。
Experimental results show that the segmentation quality of some images using new fuzzy entropy thresholding method is better than that of classical fuzzy entropy.
接着根据靶标图像和光斑图像在灰度特征上的差异，采用了最大类间方差自适应分割法实现了光靶图像的分割。
Thirdly, according to the differences of target images and spot images in gray-scale features, Otsu adaptive segmentation method is adopt to realize the image segmentation.
采用基于最大类间方差的遗传分割法通过反复迭代搜索得到较优的分割阈值，实现了憎水性图像的准确分割，可满足后续基于BP神经网络的憎水性等级的判定。
The optimum threshold value was obtained and accurate segmentation of hydrophobic image was realized, which can meet the need of the classification of hydrophobicity levels based on BP neural network.
采用基于最大类间方差的遗传分割法通过反复迭代搜索得到较优的分割阈值，实现了憎水性图像的准确分割，可满足后续基于BP神经网络的憎水性等级的判定。
The optimum threshold value was obtained and accurate segmentation of hydrophobic image was realized, which can meet the need of the classification of hydrophobicity levels based on BP neural network.
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