ART2

一种基于SIFT的图像配准方法，目前使用最广泛的一种配准方法。性能优。(One kind SIFT image registration method based on the most widely used kind of registration method. Excellent performance.)

三维重构的程序，包括角点检测，匹配，F矩阵的计算等(Three-dimensional reconstruction procedures, including corner detection, matching, F matrix calculation)

说明：  图像校正处理代码，能够运行，能够使用，并达到预期要求(Image correction processing code, able to run, use, and meet the expected requirements)

时空域下的信息隐藏技术，LSB ,MSB以及二值图像中的信息隐藏(When the airspace under the information hiding technology, LSB, MSB, as well as binary images of Information Hiding)

图像处理之Matlab特征提取和表达-一些规则图形的特征提取(Matlab feature extraction and expression in image processing - feature extraction of some regular patterns)

基于熵率的超像素分割，图像处理，图像分割技术(superpixel segmentation based on entropy rate, image processing, image segmentation technology)

labview图像预处理，子程序,包括转化为灰度图，二值化，腐蚀，膨胀，参数可调(labview IMAQ image pretreatment,sub vi，consist of conversion to grayscale, binary, erosion, dilation, adjustable parameters)

在统计学中，皮尔逊积矩相关系数（英语：Pearson product-moment correlation coefficient，又称作 PPMCC或PCCs[1], 文章中常用r或Pearson s r表示）用于度量两个变量X和Y之间的相关（线性相关），其值介于-1与1之间。在自然科学领域中，该系数广泛用于度量两个变量之间的相关程度。它是由卡尔·皮尔逊从弗朗西斯·高尔顿在19世纪80年代提出的一个相似却又稍有不同的想法演变而来的。这个相关系数也称作“皮尔森相关系数r”。(In statistics, Pearson product-moment correlation coefficient (English: Pearson product-moment correlation coefficient, also known PPMCC or PCCs [1], the article used or Pearson s r r representation) is a measure of the two variables X and Y between correlation (linear correlation), a value between-1 and 1. In the natural sciences, the coefficient is widely used to measure the degree of correlation between the two variables. It is made a similar Karl Pearson Francis Galton in the 1880s but made a slightly different idea evolved. The correlation coefficient is also called Pearson s correlation coefficient r .)

用wpf实现一个简单的手滑切换图片的实例

USB Composit example for HID