-TV-platform-

VIBE用于视频背景建模，经典算法，C++和matlab代码都有，文件是全的。(VIBE for video background modeling, classical algorithms, C++ and matlab code has a file is complete.)

说明：  图形图像出来库文件，挺好用的，直接包含进工程就可以用了 (Graphic images from the library files, good used directly included into the project can be used)

实验一 直线生成算法 实验二 圆弧生成算法 实验三 窗口菜单交互界面 实验四 区域填充算法 实验五 裁剪算法算法 实验六 图形软件开发包/库应用 实验七 曲线的生成算法 实验八 曲面生成算法 实验九 二维图形变换(Experimental line generation algorithm experiment two arcs to generate the algorithm experimental three-window menu interface experiment four regional filling algorithm experimental five-clipping algorithm algorithm experiment six graphics software development package/library application experiment seven curve generation algorithm experiment eight surface generation algorithm experiments ninety-two dimensional graphics transform)

视频编解码技术，在有限带宽的情况下，能够大幅度的压缩编码比特数，图像的质量没有丝毫的下降。(Video codec technology, in the case of limited bandwidth can be substantial coding bits, the image quality is not the slightest decline.)

采用MFC，实现遥感图像的基本增强，滤波，变换等功能。还可以保存数据。(Using MFC, to achieve the basic enhancement of remote sensing images, filtering, transformation and other functions. You can also save data)

通过点云数据的格网化，建立格网分块索引，这是一种有效的点云数据存储方式。( Through the point cloud data grid , the establishment of a grid block index, which is a valid point cloud data storage. )

特征点匹配时，采用构造KD-tree，用最优节点优先法寻找最佳匹配点(Matching feature points, the tectonic KD-tree, with the optimal node is preferred method to search for the optimal matching point)

说明：  这是一个在vc6.0基于OpenCV的控制台程序，本例给出一个椭圆曲线拟合的例子，程序首先发现图像的轮廓，然后用椭圆逼近它。(This is a vc6.0 console based on the OpenCV procedures, in this case gives an example of elliptic curve fitting, the program first to discover the outline of the image, and then close it with an oval.)

模式识别经典方法之一 K均值算法（KMeans）进行图像分割 有完善的图形界面 可以通过柱状图的形式动态展示聚类程序(One of the classical method of pattern recognition K means algorithm (KMeans) for image segmentation has improved graphical interface can be dynamically displayed in the form of histogram clustering procedure)

根据D. Comaniciu, P. Meer: Mean Shift: A robust approach toward feature space analysis 以及 C. Christoudias, B. Georgescu, P. Meer: Synergism in low level vision.这两篇文献提供的方法编写的图像分割代码，作者是 Chris M. Christoudias, Bogdan Georgescu，代码经我看了后加了丰富的中文注释，希望可以给各位带来阅读上的方便。 基于meanshift的聚类分割方法包括滤波、区域融合等操作，通过调整sigma和sigmar来调整分割效果。(According to D. Comaniciu, P. Meer: Mean Shift: A robust approach toward feature space analysis, and C. Christoudias, B. Georgescu, P. Meer: Synergism in low level vision. These two documents prepared by the methods provided by image segmentation code , the author is Chris M. Christoudias, Bogdan Georgescu, after I read the code, add a rich Chinese notes, hoping to bring you the convenience of reading. Segmentation method based on clustering meanshift including filtering, regional integration and other operations, and by adjusting the sigma sigmar to adjust segmentation results.)