point_range

基于silvaco平台 利用athena软件做的一款PN结二极管的二维图仿真(Based on silvaco platform using the officer software do a 2 d figure of the p-n junction diode simulation)

建立几何畸变模型，实现畸变矫正。通过获取模板图像的坐标值，求取变换模型参数，求出变换多项式的系数。(IMAGECORRECT M-file for imageCorrect.fig IMAGECORRECT, by itself, creates a new IMAGECORRECT or raises the existing singleton*.)

2D转3D中的深度图生成模块，内部有图片例子。(depth map generation module, 2D to 3D)

实现三维对象的平移,旋转变换,以及投影变换,不错的(Realize 3 d object of translation, rotation transformation and projection transformation, good)

可以实现图像篡改检测，附带有几张图片，检测效果一般(Image tamper detection can be achieved, with pictures, the detection effect is general)

对模糊变量进行随机化,并用高斯分布进行概率求解,无密码(To randomization of fuzzy variables, and probability to solve with the gaussian distribution, no password)

Gabor小波提取特征一幅输入的图形进行特征提取基于gabor小波变换 (Gabor wavelet feature extraction of an input graphics gabor feature extraction based on wavelet transform)

高级数据呈现技术,是一门比较先进的技术,希望对大家有所帮助.(dfgdfgdfsdfsdafasgvasdfgsafasdgfdgasdfsdafsdfsdfs)

边沿检测与提取轮廓跟踪，来自于源码中国 www.Cn700.com(edge detection and extraction of contour tracking, source from China www.Cn700.com)

一个比例和方向自适应均值漂移跟踪算法（SOAMST） 提出本文所要解决的问题，如何估计的规模和方向 改变均值漂移下的目标跟踪框架。在原来的均值偏移 跟踪算法，可以很好地估计目标的位置，规模的同时， 方向的变化，不能自适应估计。考虑到图像（重量） 是来自于目标运动模型和候选模型可以代表的可能性，一个 像素属于目标，我们证明了原来的均值漂移跟踪算法可以 推导出的重量图像的零阶和一阶矩。随着零阶 矩和目标模型和候选模型之间的Bhattacharyya系数， 提出了简单而有效的方法来估计的规模为目标。然后一种方法， 利用估计的区域和第二阶中心矩，提出 自适应地估计目标的宽度，高度和方向的变化。广泛 实验来证实所提出的方法，并验证其可靠性 规模和方向变化的目标。(A scale and orientation adaptive mean shift tracking (SOAMST) algorithm is proposed in this paper to address the problem of how to estimate the scale and orientation changes of the target under the mean shift tracking framework. In the original mean shift tracking algorithm, the position of the target can be well estimated, while the scale and orientation changes can not be adaptively estimated. Considering that the weight image derived from the target model and the candidate model can represent the possibility that a pixel belongs to the target, we show that the original mean shift tracking algorithm can be derived using the zeroth and the first order moments of the weight image. With the zeroth order moment and the Bhattacharyya coefficient between the target model and candidate model, a simple and effective method is proposed to estimate the scale of target. Then an approach, which utilizes the estimated area and the second order center moment, is proposed to adaptively e)