CepstrumPWiner

对脑部ct图像的头骨形状进行区域生长算法的运算(Ct images of the brain the skull shape of region growing algorithm for computing)

图象的冲击滤波程序,用于图象增强,用MATLAB语言编写(image filtering impact procedures for image enhancement, using MATLAB language)

在成像平台运动的情况下通过对因为平台运动的补偿实现目标运动信息获取(Imaging platform in the case of movement of movement as a platform to achieve the objectives of the compensation information acquisition campaign)

希尔伯特黄变换方法的安全评估matlab源程序(Hilbert-Huang Transformation security assessment)

读取图像，将RGB图像转化为灰度图像，显示并保存(The RGB image is transformed into gray image)

说明：  利用支持向量机实现到道路图像的分割功能，自行鼠标点击采样(Road segmentation using SVM)

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 .)

sift算法的完整matlab程序,本人测试过，很好，稍加修改即可！(complete sift algorithm matlab program, I tested, well, a few minor changes!)

基于模板匹配的另一种人脸识别的算法，很实用，利用肤色建模来建立人脸皮肤模型(Another based on template matching algorithm for face recognition, very practical, using skin color modeling to create a human face skin model)

由于前台开发人员经常需要通过RGB值指定各种各样的颜色，而通过这几个图片就可以马上找到某个颜色的RGB值，从而更快地编写网页(Foreground developers often need a variety of colors through RGB values ​ ​ specified by these pictures can immediately find the RGB value of a color, so to write Web pages faster)