资源列表
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- 该代码实现了把一个视频分割成若干个图片的功能-The code for a video is divided into a number of pictures
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- 这个代码实现了用opencv从摄像头读取视频并且识别出人脸的功能-The code to read the video from the camera with opencv and identify a person' s face
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- 该代码实现了在一张图片中设置ROI区域并存储下来的功能-The code to set the ROI region in a picture and store down
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- 该代码实现了对一张图片进行cvErode处理的功能-The code to achieve the functions of a picture cvErode processing
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- 该程序实现了对摄像头的调用并将拍摄结果现实出来-The program call and filming the results of reality out of camera
fourierDescriptor_cPP
- fourierDescr iptor.rar, 抽取目标图形的轮廓及其fourier Descr iptor算子, 然后对此fourier descr iptor进行标准化(normalized), 标准化以后的算子满足orientation，scale 和translation invariant。 再将此算子与某标准图形的fourier 算子进行比较， 若各项差的平方小雨某范围，则断定与此标准图像类似。 -fourierDescr iptor.rar extract the targe
generalHough_CPP
- 通过generall Hough Transformation来识别图形。 通过对两组图像进行相关而完成R table。 这样就加快了速度。-Generall Hough Transformation to identify the graphics. Through the correlation of the two graphics, the R table will be finished. In this way the progress is greatly accerlorated
ridgeDetection_CPP
- 把图像放置在Gaussian Scale Space，并求出各层图像的Hessian 矩阵。 通过Hessian举证，来求出图像中的blob和ridge。-The image is placed in the Gaussian Scale Space, and calculate the Hessian matrix of the layers of the image. At last the blob and ridge of the image will be detected.
expectaionMaximation_CPP
- 通过gaussian mixture Model 产生一组点， 通过 Expectation Maximation方法对这些等进行划分。 结果表明，此算法能够很好的确认gaussian mixture model。-Gaussian mixture Model is used to produce a set of points. And through Expecation Maximation Method the points will be classified. The results
countor
- 统计运动物体的数目，但是在并排行走时不能进行精确统计，所以还有很多需要完善的地方。-count the number of moving objects，you can refer to it。but it can not count too many people，so it is just a demo which is mature。please
chap3
- 介绍了最小二乘法的相关知识原理应 用。。。以及最小二乘法在曲线拟合中的应用-Knowledge of the principle of least squares method application. . . And the least squares method of curve fitting
vcPopencv
- opencv vc++ 实现图像旋转 矫正已经倾斜的图像 得到倾斜角度-opencv mfc vc++ image skew you can get the skew angle