1) 2_D characteristic histogram
二维特征直方图
2) feature histogram
特征直方图
1.
The paper uses the technology of feature histogram equalization to transfer the laws to the uniform distribution law in 0,1],based on the analysis of the cell recognization feature database under the microscope.
实验表明,基于特征直方图均衡化技术实现的ID。
2.
Moreover,in order to reduce process time,the color-based feature histogram is presented based on the pixel position weight in tracking fields as an observing vector,and then it is used in the posterior estimation successfully.
为了减少计算量,在充分考虑跟踪区域各像素权重的条件下,建立基于颜色信息的特征直方图作为观测向量,并用于后验估计。
4) two-dimensional histogram
二维直方图
1.
Thresholding using two-dimensional histogram and watershed algorithm in the luggage inspection system;
基于分水线算法的二维直方图阈值化分割在箱包DR-CT检测系统中的应用
2.
In the experiments,we employ a weighted two-dimensional histogram WFCM algorithm to improve the image segmentation effect,since it takes account of spatial relation.
实验利用了加权二维直方图的WFCM算法,考虑像素间的空间信息,改善了图像分割效果。
3.
Aimed at the problem that traditional fuzzy entropy thresholding method based on one dimensional histogram is sensitive to the noise,a novel maximum fuzzy entropy thresholding method based on two-dimensional histogram is presented.
针对基于一维直方图的传统模糊熵算法对噪声敏感的问题,提出了一种新的基于二维直方图的最大模糊熵图像分割算法。
5) 2-D histogram
二维直方图
1.
Image threshold segmentation method based on an improved 2-D histogram;
一种改进的二维直方图的图像阈值分割方法
2.
To realize automatic segmentation and build a 2-D histogram using 2-D entropy,traditional methods research the central gray value and mean value of pixels in the same neighbor.
建立二维直方图并借助二维熵可以自动确定图像分割的阈值。
6) 2D histogram
二维直方图
1.
Image segmentation of mean shift based on improved 2D histogram
一种改进的二维直方图均值漂移分割算法
2.
This paper studies the application of fuzzy c-means(FCM) clustering algorithm in the image segmentation,and a fast image segmentation method is presented based on a 2D histogram weighting FCM algorithm.
提出一种基于二维直方图加权的模糊c均值图像快速分割算法。
3.
A two phased thresholding method is proposed which combines the wavelet transform (WT) with the traditional 2D histogram based thresholding method.
该方法首先对二维直方图进行小波分解，得其低频分量，然后在此低频分量上确定出门限矢量的范围，最后在此范围内确定出精确的门限矢量。
补充资料：半单Lie代数有限维表示的特征标
半单Lie代数有限维表示的特征标
imensional representation of a semi-simple Lie algebra character of a finite-
半单Lie代数有限维表示的特征标沁haracter of a 6nite-dimensio皿1 rePresenta600 ofa semi滋mPleLiealgebra:xapaRTep KO“e，“OMep“0r0 IIPe口CTa.Je”“翻no月ynpo-℃To曲a通.e6P‘加} 一个函数，它把表示的每一个仪对应到相应的权子空间的维数.如果勺是特征为O的代数闭域人仁半一单Lie代数g的一个Cartan子代数，甲:g争妇(v)是一个线性表示而代是对应于又〔为’的权子空间，那么表示华(或g模f)的特征标可以写成以下形式: eh于二艺(d;mF;)e’ e卜并且可以看成群环Z肠’」的一个元素如果人二C且甲=d小，其中。:G一GL(F)是以q为其Lie代数的一个Lie群G的解析线性表不，那么记法e汽可以看成b上的函数而ch价与函数x卜，场(e‘)伪〔专)一致，这卫x。是表示巾的特征标Lje代数的表示的特征标具有以下性质: ch( FI由VZ)二chF:一+ch卜2， eh(Vl⑧卜一2)=eh FI·eh否/2
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条