搜索资源列表
freak_test
- 基于人眼视觉特性的特征描述子 Freak 的测 试源代码，运行环境OPENCV2.4.3.-Test test source code for freak descr iptor based on the characteristics of the human visual system . running environment OPENCV2.4.3.
gaussian_avi
- 读入avi,利用混合高斯模型，检测出运动的前景和背景信息。VS2008+opencv2.4.3-Read into avi, Gaussian mixture model to detect the movement of the foreground and background information. VS2008+opencv2.4.3
Pyramid-final
- 基于OpenCV2.4.3、VS2010的控制台程序，按照自己的OpenCV路径进行配置，修改读取图像的位置，之后便可运行。运行结果为可修改层数的图像金字塔构建。-The console program based on OpenCV2.4.3, VS2010, according to their own OpenCV path configuration, modify the position of the image, and then you can run. The results
test
- 利用非局部均值算法（NLM）去除含噪声图像中的噪声，环境配置为vs2010+OpenCV2.4.4.程序中首先对输入图像添加噪声，然后再对噪声图像进行NLM去噪处理，并与其它算法在处理速度上进行了比较。-Non-local means algorithm (NLM) to remove image noise with noise, the environment is configured to vs2010+OpenCV2.4.4.
kalman_camshift-object-tracking
- 基于vs2010+opencv2.4.4调试通过的kalman_camshift跟踪运动物体，测试视频比较简单。-Based on vs2010+ opencv2.4.4 through debugging kalman_camshift tracking moving objects, test video is relatively simple.
GrabCutExercise
- 基于vs2008和opencv2.4.2的图像分割程序，该程序实现从给定图像中分割出前景ROI并显示分割后的结果。包含矩形窗口分割和掩码图像分割两种模式，采用掩码图像分割时，按Ctrl和鼠标左键添加背景，按Shift键和鼠标左键添加前景-Image segmentation based on vs2008 and opencv2.4.2 program, the program implementation from a given image segment the foreground RO
Kinect3DColor-20130719
- Kinect+Opencv2.4.5录视频-video capturing with Kinect and Opencv2.4.5
main
- opencv2.4.4直方图均衡化代码，使用时请将均衡化图片命名为11.jpg。若不是jpg文件，请修改程序中的加载文件名-opencv2.4.4 histogram equalization code, please use equalization picture named 11.jpg. If a jpg file, modify the program to load the file name
main
- opencv2.4.4图像加亮函数，本程序默认每个像素加亮25个单位，可以根据个人需要修改程序中的增量-opencv2.4.4 images highlight function, the program defaults for each pixel to highlight 25 units, you can modify the program according to individual needs of the incremental
sift(zddmail)
- 在原作者的基础上进行了一些修改，编译环境为OPENCV2.4.4，GTK+2.0-On the basis of the original author some modifications OPENCV2.4.4，GTK+2.0
showtest
- 这个程序在ubuntu 中的OpenCV2.4.4能运行，没试过其他平台，但应该是大同小异的。其中代码都是C++风格，用了surf算法寻找特征点，用flann算法匹配特征点，有简单拼接模式和加权平均匹配模式-This program can run in ubuntu in OpenCV2.4.4, have not tried other platforms, but it should be pretty much the same. Where the code is C++ style,
matching
- 特征点匹配，采用RANSAC算法过滤噪点，在vs2008+opencv2.4.4下编译过，有运行结果，效果不错-Feature point matching, noise filtering using RANSAC algorithm, compiled in vs2008+ opencv2.4.4 too, have the results, good results
sharpen
- 本程序是在vs2010+opencv的平台上运行的，利用的是opencv2.4.9，C++写的，利用多种方法来遍历图像，例如通过创建迭代器的方法来遍历图像，通过指针的方法来遍历图像等方法来对图像进行处理。最后的得到的效果令人满意。-This program is run on a platform vs2010+opencv, the use of the opencv2.4.9, C++ write, using a variety of methods to traverse the ima
ViBe
- ViBe是现在最成熟、速度最快的背景建模算法。代码已分装好，亲测可用。需要配置Opencv2.4.2以上的版本.-ViBe is now the most mature and fastest background modeling algorithm. The Code has been dispensed well, pro-test available.Using the code,you should install Opencv 2.4.4 and uper vision.
full-view-image-stitching
- 下载即可在VS2010+opencv2.4.4运行的将两张有重叠部分的图像(可能是不同时间、不同视角或者不同传感器获得的)拼成一幅大型的无缝高分辨率图像，得到全景图。-The 2 pieces of overlap image (which may be different time, different Angle of view or different sensors to obtain) Mosaic of a large seamless high-resolution images,
MOG2_OPENCV2.4.9
- 经典背景减除方法，MOG2(或GMM)，从opencv2.4.9中单独提取出来的，经过实验调试通过的，可同其他背景减除方法结合或对比。-It is a typical background subtraction mathod, which is OpenCV 2.4.9. It was proposed by Zivkovic in 2014ICPR and proved effective.
DarkChannelPiror
- 基于暗原色先验去雾处理程序，在visualstudio2010环境下配置好OpenCV2.4.4版本，效果较好-Prior to fog handler in visualstudio2010 environment configuration based on dark colors good OpenCV2.4.4 version better
face_test
- 基于vs2010+opencv2.4.4的人脸的检测，可以供各位初学的读者越来，以快速掌握人脸人检测，对于大神级人物，就不用读了。谢谢各位支持哦，祝各位学者，学习进步，事业有成。愿计算机视觉都能给你我带来美好的明天。-Face detect
FaceDetection
- 开发平台vs2012+opencv2.4.10;可以实现基于boosting的人脸检测。(Development platform vs2012 + opencv2.4.10; can be achieved based on boosting face detection.)
ImageStitch
- 开发环境vs2012+opencv2.4.10;可以将多幅图片拼接成一幅完整的图片(Development environment vs2012 + opencv2.4.10; can be a number of pictures into a complete picture)