ImageFusion_PCA

零相位带通滤波源代码,可以对信号进行滤波处理提高信噪比.(Zero-phase band-pass filtering the source code, you can filter the signal-noise ratio improve treatment.)

基于Visual C++的图像边缘检测工程，以Canny为例(Visual C++-based image edge detection works to Canny Case)

Image processing using sobel operator

一款VC++图像开场加载效果，向大家演示了几种图像装载的特效实现的方法，比如扫描显示、滑动显示、渐入显示和马赛克显示等，大家在使用一些幻灯片软件的时候，经学会看到类似的效果，如果你有一定的VC++基础，你可以借鉴一下本效果的具体方法，再次扩展，可以制作出一款带特效的图像查看器(The opening loading effect of a VC++ image to demonstrate the effects achieved in several image loading, such as scanning, slide show, getting into the display and mosaic display, we learn to look at some slides software to similar effect, if you have certain VC++ basis, you can learn about the effects of specific methods, extended again, can create the image of a band effects Viewer)

在VC6.0环境下，借助openCV函数库，对视频中的人脸进行检测，并实时跟踪，然后用Haar特征的分类器定位人脸，并检测瞳孔存在与否，提取关于眼睛的疲劳信息(In VC6.0 environment, with the aid of openCV function library, to detect human faces in video, and real-time tracking, positioning and use characteristics of Haar classifier faces, and examine the pupil existence, to extract the information about the fatigue of the eye)

稀疏矩阵的实例，讲述如何用稀疏矩阵进行实际的编程。本例是以超市购物为实际背景。(Examples of sparse matrix)

说明：   最简单的差分格式有向前、向后和中心3种。 向前差分：f (n)=f(n+1)-f(n) 向后差分：f (n)=f(n)-f(n-1) 中心差分：f (n)=[f(n+1)-f(n-1)]/2(The easiest difference format forward, backward, and three kinds of centers. Forward differencing: f (n) = f (n+ 1)-f (n) Backward difference: f (n) = f (n)-f (n-1) Central difference: f (n) = [f (n+ 1)-f (n-1)]/2)

用Visual C++实现基于数学形态学的数字图像处理,包括二值图像的腐蚀,膨胀,开,闭,细化及中轴变换等运算.(Visual C++ using mathematical morphology-based digital image processing, including binary image erosion and dilation, opening, closing, thinning, and the central axis transform operations.)

图像分割方法中有关感兴趣区域处理的程序代码(Image segmentation method for region of interest processing code)

输入一个带权无向图的顶点数、边数、各条边信息（两个顶点和权值），建立该图的邻接矩阵结构，输出该邻接矩阵。将上述无向图邻接矩阵转换为邻接表结构，输出该邻接表；根据该邻接表对无向图进行深度优先遍历序列和广度优先遍历序列，并输出遍历结果；用prim算法实现构造该带权无向图的最小生成树，并将该最小生成树的各条边信息输出。(Enter a weighted undirected graph with vertices, edges, each of the side information (two vertices and weights), the establishment of the adjacency matrix structure, the output of the adjacency matrix. The above undirected graph adjacency matrix into adjacency list structure, the output of the adjacency list according to the adjacency table undirected graph depth-first traversal sequence and breadth-first traversal sequence, and outputs through the results using prim algorithm construct the weighted undirected graph minimum spanning tree, and the minimum spanning tree information on respective sides of the output.)