This paper proposes an algorithm of image segmentation based on pattern classification according to the features of soil microphotographs.
该文针对土壤显微图片特征，基干模式分类对图象实施分割；
This thesis applies data mining techniques to customer segmentation based on customer value matrix and builds the classification model of customer with different value.
本文把数据挖掘技术应用于基于客户价值矩阵的客户价值细分中，建立各类价值客户的分类模型。
In this paper, a level set segmentation algorithm based on Bayesian classification for medical image segmentation was proposed.
本文提出了一种结合贝叶斯分类的水平集方法用于医学图像分割。
The classification research of regional shape after image segmentation is brought forward in this paper based on RS theory.
本文主要利用粗集理论针对图像分割后的区域形状进行分类研究。
And a set of features combining color, shape and topological are extracted from each object. Based on the features, a classification criterion is employed to perform the map segmentation.
通过提取对象的颜色、形状和近邻关系等特征，建立分类标准，实现地形图的自动分层。
Third, the initial segmentation is refined scale by scale to get the final segmentation of the SAR image based on the posterior probability of classification which is estimated by the mixture model.
最后根据SAR图像的统计性质，利用基于混合模型估计的分类后验概率将初始分割结果逐尺度进行细化得到SAR图像的最终分割。
In the paper, firstly, using the classification theory in pattern recognition, approach of multithreshold stone image segmentation based on improved 2D class variance is presented.
文章从模式识别的分类理论出发，提出了改进的二维类间方差的多门限阈值石块分割方法。
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.
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。
应用推荐