imagejiansuo

说明：  多边形裁剪是逐次多边裁剪法，它的基本思想是以窗口的四条边界线单一逐次对多边形裁剪(polygon clipping is Successive multilateral cutting, its basic idea is a window four successive boundaries of a single polygon clipping)

粗化细化程序很好用的，大家试市啊，(crude refining procedures of the good, we take the city ah,!)

利用棋盘格对相机进行标定，加入误差判定及像素空间到实际物理空间的距离计算(The camera is calibrated by checkerboard, the error is added and the distance of pixel space to the actual physical space is calculated)

《基于计算机视觉的普适性三维重建方法研究》源代码，实现了一种将二维图像重建成三维场景的方法。(Source code of <General Sense Three-Dimension Reconstruction Research Based on Computer Vision>, a technique which can convert 2D images into 3D sence.)

图像分割处理的小波变换算法源代码，使用vc++(Wavelet transform image segmentation algorithm source code vc++)

说明：  转载的，通过眨眼前后灰度图对比是别人眼，一个学习opencv工具的好例程。(Reproduced by blinking eyes of others around the grayscale contrast, a learning tool opencv good routine.)

利用Artoolkit实现了虚拟现实的算法，VS2008下测试通过(Use Artoolkit algorithm to achieve a virtual reality, VS2008 under test)

三维激光点云配准是点云三维建模的关键问题之一。经典的 ICP 算法对点云初始位置要求较高且配准 效率较低，提出了一种改进的 ICP 点云配准算法。该算法首先利用主成分分析法实现点云的初始配准，获得较好 的点云初始位置，然后在经典 ICP 算法的基础上，采用 k － d tree 结构实现加速搜索，并利用方向向量夹角阈值去除 错误点对，提高算法的效率。实验表明，本算法流程在保证配准精度的前提下，显著提高了配准效率。 (Three-dimensional laser point cloud registration is one of the key three-dimensional point cloud model. High classical ICP algorithm to the initial position of the point cloud registration requirements and low efficiency, proposed an improved ICP point cloud registration algorithm. Firstly, the use of principal component analysis of the initial point cloud registration, get a better initial position of the point cloud, then the basis of classical ICP algorithm using k- d tree structure to achieve speed up the search, and using the direction vector angle the removal of the threshold point error and improve the efficiency of the algorithm. Experiments show that the algorithm processes to ensure the accuracy of registration under the premise, significantly improve the efficiency of registration.)

对输入的一张彩色图像，自己写代码实现Harris Corner 检测算法： 1. 不能直接调用OpenCV 里面与Harris 角点检测相关的一些函数； 2. 只能用C/C++，不能用其他语言； 3. GUI 只能用自带的HighGUI，不能用QT 或其他的； 4. 平台可以用Windows， Linux, MacOS； 5. 显示中间的处理结果及最终的检测结果，包括最大特征值图，最小特征值图，R 图（可以考虑彩色 展示），原图上叠加检测结果等，并将这些中间结果都输出成图像文件； 6. 命令格式： “xxx.exe 图片文件 k 参数(=0.04) Aperture_size(=3)”。(The input of a color image, write your own code to achieve Harris Corner Detection Algorithm: 1. Can not be called directly inside OpenCV some functions associated with the Harris corner detection 2. To only use C/C++, can not be used in other languages 3. GUI only with their own HighGUI, can not use QT or other 4. The platform can be used Windows, Linux, MacOS 5. Display intermediate and final results of the test results, including the largest eigenvalues diagram, the minimum feature value graph , R chart (you can consider color display), picture superimposed on the test results, etc., and these intermediate results are output as an image file 6. Command Format: " xxx.exe picture file k parameters (= 0.04) Aperture_size (= 3 ). " )

用Visual C编的用于语音的频频谱的检测，能显示出来语音的频谱图。 (Visual C series of the spectrum for voice detection, displayed the frequency spectrum of the voice.)