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。
A method is presented to calculate automatically the best gray threshold, which is suitable for images under different scanning resolutions.
提出一种灰度阈值自动计算方法，适合于自动计算不同扫描分辨率下的图像的最佳灰度阈值。
In this paper, the method for the optimal gray threshold is given, which is based on the maximum class separation distance criterion of pattern recognitive decision theory.
利用基于模式识别决策理论的最大类间距准则，给出了求解最佳分割灰度门限的方法。
The images of bubbles in flow were segmented by means of dynamic threshold technology and gray weighted method was used to improve the precision of locating the central positions of bubbles.
采用动态阈值技术实现了对气泡图像的正确分割，利用灰度加权方法提高了气泡颗粒的定位精度。
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.
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。
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。
The contrast of the image was enhanced by gray expanding and the key threshold of the binarization algorithm was determined based on the dynamical threshold method.
通过灰度拉伸增强图像对比度，通过二值化处理实现图像中背景和对象的分割。
The contrast of the image was enhanced by gray expanding and the key threshold of the binarization algorithm was determined based on the dynamical threshold method.
通过灰度拉伸增强图像对比度，通过二值化处理实现图像中背景和对象的分割。
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