ImageBoard

This a very useful program from a book. It is mainly used for face-detecting.It also includes interface-program.

VisualC++数字图像处理技术详解第2版-光盘 第九章(VisualC++ digital image processing technology Detailed Version 2- CD Chapter IX)

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.)

苹果在线检测系统，实时性比较好，可用性更好，很好很好(Apple' s online testing system, real-time is better)

这是关于pca的文件，说明实现pca的降维(This is the file on pca, achieve pca dimensionality reduction)

说明：  LSA的第一步是要去创建词到标题（文档）的矩阵。在这个矩阵里，每一个索引词占据了一行，每一个标题占据一列。每一个单元（cell）包含了这个词出现在那个标题中的次数。例如，词”book”出现在T3中一次，出现在T4中一次，而”investing”在所有标题中都出现了一次。一般来说，在LSA中的矩阵会非常大而且会非常稀疏（大部分的单元都是0）。这是因为每个标题或者文档一般只包含所有词汇的一小部分。更复杂的LSA算法会利用这种稀疏性去改善空间和时间复杂度。(The Little Book of Common SenseInvesting: The Only Way to Guarantee Your Fair Share of StockMarket Returns ,)

这里的图像增强包括灰度修正、平滑、滤波、锐化等，是图像处理的基本操作，本代码调试通过(Here, including gray-level correction image enhancement, smoothing, filtering, sharpening, etc., is the basic image processing operations, the code debugging by)

著名专家写的计算机视觉方面的原著，希望对大家有所帮助(Writing a well-known experts in the computer vision aspects of the original, and they hope to help everyone)

利用VTK实现图像的放大缩小，基于对话框编写的，有助于学习VTK的朋友(Using VTK to achieve the image to zoom in, based on the dialog box, prepared to help a friend learn VTK)

运动检测 检测人体的头部位置、整体位置、滤除影子(Motion detection detect the body and head position, the overall position of the shadow filter)