openvcfushi

可以显示图像并显示大话西游中的经典台词，还可以播放动听的背景音乐。(Can display images and display the classic Journey to the West in the lines, but also can play pleasant background music.)

利用Visual C++实现AVI文件的图像截取 实现对图像数据的读取显示 实现视频图像处理技术 编程中如何操作数据库中的图像字段 实现数字图像增强处理(Use Visual C++ AVI file image interception To read the image data display Video image processing technology Programming how to operate the database image field Digital image enhancement)

说明：  简单的数字图像处理程序，实现灰度化，二值化，边缘检测等(Simple digital image processing program, graying, binarization, edge detection, etc....)

《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.)

本系统中VIS欠缺的SIFT_VC.lib文件。。。 http://www.pudn.com/downloads224/sourcecode/math/detail1055031.html(This is lib file, which is used in Video Intelligent System (VIS) based on the Microsoft Visual Studio 2008 compiler environment and OpenCV 2.0 library. It includes foreground detection, motion object detection, motion object tracking, trajectories generation and analysis modules. It realizes a friendly interface based on dialog, which provides a convenient example for new learners. keywords: opencv, mixture of gaussian model, sift feature and ransac method, mean shift, particle filter, kalman filter, object detection and tracking, video intelligent system.)

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.)

数字音频水印的嵌入，提取，然后进行攻击性实验，检验其鲁棒性(Digital audio watermark embedding and extraction, and then attack experiment to test its robustness)

opencv,图像处理，关于物体粘连问题的检测，基于凹性分析的分割方法(opencv, image processing, object sticking problem on detection, segmentation method based on analysis of the recess)

本程序使用dcmtk库，可以显示大部分的DICOM图像。非压缩、压缩黑白图像以766灰阶显示，彩色图像正常显示。 对于初用dcmtk库的开发者来说，入门较难，本程序已使用VC6工程将主要库加入工程中，可以参考本工程的设置。另外，对于高于8位的黑白图像，本程序也提供一个处理方法的参考。(This procedure used dcmtk library, you can see that the majority of the DICOM image. Non-compressed, compressed to 766 gray-scale black-and-white images show that color image display. Dcmtk library used for the early developers, the entry more difficult, the procedure has been in use for the main library VC6 project will join the project, can refer to the project settings. In addition, higher than the 8-bit black-and-white images, the program also provides a reference method.)

基于边缘特征的图像配准算法源码 基于边缘特征的图像配准算法是将不同时间、不同的传感器（成像设备）或不同条件下（天候、照度、摄像位置和角度等）获取的同一场景的两幅或多幅图像根据其边缘特征进行匹配、叠加的处理，最终生成一幅全景图像的方法。该方法具有抗噪性强，匹配速度快，误匹配率低，适用于多种类型的图像等优点，主要可以运用于以下领域： （1）军事研究领域，如飞行器辅助导航系绞、武器投射系统的末制导以及寻地等应用研究； （2）医学图像分析，如数字剪影血管造影DSA血管造影术、肿瘤检测、白内障检测、CT、MRI、 PET、 SPECT图像结构信息融合； （3）模式识别，如特征识别、波形分析、签名证实、目标物运动跟踪、序列图像分析等； （4）计算机视觉，可用于目标定位、自动质量控制等； （5）遥感数据分析，多电磁波段图像信息融合，如多谱段的等场景分类、定位和识别定义好的或已知特征的场景、自然资源监控、核生长监控、市区增长检测等。 本算法实现使用VC++6.0为开发环境，目前只支持灰度图像，感兴趣的朋友可以进一步扩展。(Image registration is a fundamental problem in image processing, which is a process to match two or more images of the same scene taken at different times, from different viewpoints, or by different sensors. Image registration is an important technique for a great variety of applications such as medical image analysis, computer vision, remote image data analysis, image information fusion, and the recovery of the 3–D characteristics of a scene.)