Voronoi

delaunay三角化程序 delaunay三角化程序 delaunay三角化程序(delaunay triangulation delaunay triangulation process procedures delaunay triangulation process)

VTK读取BMP序列图片实现MC算法面绘制，并且将绘制结果保存为STL格式。(VTK read BMP image sequences to achieve MC surface rendering algorithm, and the results will be drawn saved as STL format.)

用C++编写的产生文章的程序，方便有需要的人(C generated articles prepared by the procedures that are accessible to people in need)

实现运动目标的跟踪，首先用鼠标选取一个区域。之后能自动跟踪这个目标(Tracking of moving objects, first use the mouse to select a region. After automatic tracking of this objective)

第27章 透明位图背景上的滚动字幕实例该程序可以方便实现字幕的滚动效果，程序简单易懂(transparent bitmap on the background of rolling subtitles examples of the procedures to facilitate the achievement of subtitles rolling results, procedures simplified)

利用visualC++和图像处理的知识，编写程序对果蔬进行自动识别(Using visualC++ and image processing knowledge, write a program for automatic identification of fruits and vegetables)

halcon图像处理软件用来检检测图像的圆状物体。可直接使用。 (halcon image processing software is used to check the oblong object detection image. Can be used directly.)

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.)

说明：  利用c++实现的PCA算法，直接对数据进行处理，适合初步学习(C++ implementation using PCA algorithm to process the data directly)

用AAM算法进行人脸特征点的标定，即对人脸的眼睛，眉毛，嘴巴，鼻子及脸的轮廓进行标记，此代码标记了68个特征点。(AAM algorithm for facial feature points calibration, calibration of this code is the 68 feature points, see the instance document.)