Fngprnt

可以进行背景减除法-三帧法-高斯背景建模法运动检测( This file (the project file) contains information at the project level and is used to build a single project or subproject. Other users can share the project (.dsp) file, but they should export the makefiles locally. )

VC摄像图捕捉程序，简单实用，对初学者有帮助(VC camera Figure capture, simple and practical for beginners)

用Visual C编的用于语音的频频谱的检测，能显示出来语音的频谱图。 (Visual C series of the spectrum for voice detection, displayed the frequency spectrum of the voice.)

中值滤波程序 对图象选定区域进行排列中值 滤波(median filtering of images selected procedures region with median filtering)

此程序利用openCV中人脸识别于模版匹配实现机器人的运动控制功能，其中机器人控制用了Aria的库和模拟器，使用者可根据控制需要替换这部分程序。 本程序的核心部分一直用于只能轮椅的人脸控制。(This process us face recognition in openCV and template matching to achieve robot motion control functions, which used the Aria library and robot simulator, user need replace this part of the control procedures to achieve their application.)

粗化细化程序很好用的，大家试市啊，(crude refining procedures of the good, we take the city ah,!)

源码包括了常用的图像处理方法，代码详细，适合初学者(Source code, including the commonly used image processing method, the code in detail, suitable for beginners)

说明：  使用gpu、cpu并行进行sift算子计算匹配，能够在原来的基础上加速处理，但对显卡要求较高，具体环境配置使用方法可以参照mannual(SiftGPU is an implementation of SIFT [1] for GPU. SiftGPU processes pixels parallely to build Gaussian pyramids and detect DoG Keypoints. Based on GPU list generation[3], SiftGPU then uses a GPU/CPU mixed method to efficiently build compact keypoint lists. Finally keypoints are processed parallely to get their orientations and descriptors. SiftGPU is inspired by Andrea Vedaldi s sift++[2] and Sudipta N Sinha et al s GPU-SIFT[4] . Many parameters of sift++ ( for example, number of octaves, number of DOG levels, edge threshold, etc) are also available in SiftGPU. The shader programs are dynamically generated according to the parameters that user specified. SiftGPU also includes a GPU exhaustive/guided sift matcher SiftMatchGPU. It basically multiplies the descriptor matrix on GPU and find closest feature matches on GPU. Both GLSL and CUDA implementations are provided. )

本程序的细化算法要应用于含线条的黑白二值图像才可以看出细化效果。(This procedure should be applied to the thinning algorithm with two lines of black-and-white image before thinning effect can be seen.)

基于opencv 实现毛衣的瑕疵检测 属于毕业设计 功能完整(it is perfect)