搜索资源列表
FACE_Detetion_Recognition
- 基礎的人臉識別程式，使用OpenCV,Boost與Qt，一樣使用haarcascades方法，內附Binary可使用。環境Visual C-Based face recognition program using OpenCV, Boost, and the Qt, the same use haarcascades methods included Binary can be used.
MVC_VideoPlayer.10132012
- Kernel regression image processing code ported to C++ source code with QT and OpenCV libraries - work in progre-Kernel regression image processing code ported to C++ source code with QT and OpenCV libraries - work in progress
QtOpenCVWidgets
- 使用Qt c++库进行OpenCV开发时的一些库函数，并且有这些库函数使用说明和示例程序可以进行学习和研究。-Use Qt c++ library OpenCV library functions during development, and use of these library functions and example programs can learn and study.
testgaussion
- opencv+qt+c++ 为图片添加高斯噪声-opencv+qt+c++ for the picture to add Gaussian noise
testsaltpepper
- opencv+qt+c++ 为图片添加椒盐噪声-Add salt and pepper to picture noise opencv+qt+c++
wiener
- opencv+qt+c 实现维纳滤波功能-opencv+qt+c achieve Wiener filtering
differencing
- opencv+qt+c++ 两图片相减（二值图像）-opencv+qt+c++ two subtraction image (binary image)
HarrisCorner
- 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
savevideos.tar
- 用c++在QT上编写的视频保存的程序，能够根据已有视频的个数，自动给新生成的视频编号保存。很实用哦。-With QT on the c++ prepared by the video stored procedures, can be based on the number of existing video, automatically to save the new generation of video. Very practical oh.
OpenCamera
- windows平台下c++编写使用opencv+qt打开摄像头并显示轮廓的程序(Windows platform, c++ prepared to use opencv+qt to open the camera and display outline procedures)
KinectCoordination
- 利用了微软的Kinect v2 开发了基于深度图像的人体目标的检测跟踪与定位，结合了VS2013，Qt以及opencv视觉库，设计了该系统的GUI界面(Using Microsoft's Kinect V2, we have developed the detection, tracking and positioning of human targets based on depth images. Combining the VS2013, Qt and opencv visual libr
fruit-recognition-master
- 运用了OpenCV、C++、水果识别、Qt界面、颜色识别、边缘检测、图像处理 ，能够实现对不同种类水果进行识别分类。(Using OpenCV, C++, fruit recognition, Qt interface, color recognition, edge detection, and image processing, it is possible to identify and classify different types of fruits.)