ImageZoom

这是典型的图像分割Livewire算法的源码 结合OPENCV，配置一下就可以用了(This is a typical source image segmentation algorithm Livewire combination OPENCV, can be used to configure what)

SIFT特征提取 http://www.opencvchina.com/forum.php?mod=viewthread&tid=209&fromuid=267 (SIFT feature extraction http://www.opencvchina.com/forum.php?mod=viewthread& tid=209& fromuid=267)

C++，人脸变形，选择图片，在图片中选择一个四边形窗口（人物脸部），然后再在内部选择一个四边形窗口，逆时针选择，然后点击变形直接呈现变形结果，点击动画可以查看人脸变形过程(C++ program, select a picture, choose a quadrilateral window (human faces) in the picture, and then select a quadrilateral inside the window, counter-clockwise to select, then click on the deformation presented directly deformation results, click animated facial deformation process can be viewed)

不同信噪比下周期FRFT和FRFT两种方法对LFMCW信号的检测能力对比(FRFT different SNR period and the comparison of the two methods FRFT LFMCW signal detection capability)

图像拼接小程序，使用直接对比的方法进行拼接并用加权平均的方法进行融合 (a simple program for image splicing )

小波处理，滤波，复原，融合等VC源代码.(Wavelet processing, filtering, recovery, integration VC source code.)

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.)

静态画图，可以改变图形边框颜色与矩形或椭圆的填充颜色(Static drawing, you can change the fill color graphics border color and rectangular or oval)

医学图像配准，医学图像2D_3D配准，基于vc++开发。(The registration of pre-operative volumetric datasets to intra-operative two-dimensional images provides an im- provedway of verifying patient positionandmedical instru- ment location. In applications from orthopedics to neuro- surgery, it has a great value in maintaining up-to-date in- formation about changes due to intervention. We propose a mutual information-based registration algorithm which es- tablishes the proper alignment via a stochastic gradient as- centstrategy. Ourmaincontributionliesinestimatingprob- ability density measures of image intensities with a sparse histogrammingmethodwhichcouldlead to potentialspeed- up over existing registration procedures and deriving the gradient estimates required by the maximization procedure. Experimental results are presented on fluoroscopy and CT datasets of a real skull, and on a CT-derived dataset of a real skull, a plastic skull and a plastic lumbar spine seg- ment.)

说明：  图片自适应二值化处理，二值化处理使用简单方便。(Adaptive binarization image processing, binary processing easy to use.)