Image character information is dug up with dividing up threshold value.
用阈值分割方法对图像信息特征进行提取。
Based on maximum between-cluster variance method and uniformity measure, this paper USES maximum entropy principle to select the gray-level threshold value for image segmentation.
在最大类间方差法和一致性准则法的基础上，运用最大熵原理来选择灰度阈值对图像进行分割。
This paper introduces a new whole binarization method by using image gray statistical characteristic value as threshold.
本文给出了一种利用图像灰度统计特征值为阈值的全局二值化方法。
After scanning the object image and labeling the connected component, the background and foreground noise could be removed easily by threshold value area expunction.
该方法仅需对图像作一次全扫描即可标记物体所有连通部分，统计标识号，根据阈值面积消除法即可快速去除图像中所有前景和背景噪声。
Every child image of the local regions is calculated, and the best threshold value of child image with the method of the biggist proportion of squase deviations is calculated.
对子图像进行局部直方图计算，由最大方差比例阈值确定方法计算出子图像的最佳阈值。
Then, the best threshold value is calculated basing on the gradient magnitude mean and the variance of the image.
再由图像的梯度幅值均值和方差计算出图像的最佳阈值。
In preprocessing, optimal threshold value method and smooth technology are adopted to process sample form image.
预处理阶段，使用最佳阈值二值化方法和平滑技术处理样本表格图像。
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。
After researching the image segmentation, we get the two-value image of the image of down with the threshold of it.
以及图像分割技术的研究，用最佳的阈值对羽绒图像进行阈值分割，得到满足羽绒检测要求的二值图像。
Based on the multilevel threshold de-noising method foundation, mean value approximation (MVA) was used to pretreat the noising image.
在多层阈值去噪方法的基础上，采用均值逼近法对含噪图像进行预处理。
This new algorithm USES the background subtraction method to get the foreground image, and then gets the binary image using threshold value and makes the morphology processing.
该算法利用背景差法获得前景图像，然后进行二值化和形态学处理，再和背景帧进行比较来对滞留和搬移物体进行检测和分类。
An approach for color image gray processing based on threshold of gray scale statistic mean value and global standard deviation of each color component is presented.
给出了一种基于图像各彩色分量灰度统计特征期望值和全局标准差作为阈值的彩色图像灰度化方法。
For the method, the threshold value matrix of a second screen with a different screen Angle and width is read out and compared with the color values of a halftone image presented.
对于该方法，将具有不同加网角度和加网线数的第二网屏的阈值矩阵读出并且与所提供的半色调图像的色值比较。
For the method, the threshold value matrix of a second screen with a different screen Angle and width is read out and compared with the color values of a halftone image presented.
对于该方法，将具有不同加网角度和加网线数的第二网屏的阈值矩阵读出并且与所提供的半色调图像的色值比较。
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