2D and 3D face recognition: A survey

实现了图像参数的获取，中值滤波，迭代阈值分割，半阈值分割等等图像处理功能-Realize the image parameters of the acquisition, median filtering, iterative threshold segmentation, semi-threshold segmentation image processing functions, etc.

对图象的对比度进行处理，不同于一般的对比度增强处理-the contrast of image processing, from a general contrast enhancement

经典书籍-数字图像处理-冈萨雷斯-3。解决各位敲代码的烦恼！These MATLAB functions were created for the book Digital Image Processing Using MATLAB (DIPUM), by R.C. Gonzalez, R.E. Woods, and S.L. Eddins, Prentice Ha-Classic books- digital image processing- Gonzalez-3. To resolve the trouble code you knock! These MATLAB functions were created for the book Digital ImageProcessing Using MATLAB (DIPUM), by RC Gonzalez, RE Woods, andS.L. Eddins, Prentice Ha

VC++实现的一个简单的图像检索程序，有参考价值。-VC++ to achieve a simple image retrieval process, a valuable reference.

用OpenCV写的采用Canny算法进行边缘检测的程序-Canny

LK稀疏光流Demo 可以在场景中自动找出关键点并自动跟踪，也可以使用鼠标在指定位置添加关键点，此程序是很好的学习光流的示例。本程序基于OpenCV。-LK Sparse Optical Flow Demo automatically in the scene to identify the key points and automatic tracking, you can also use the mouse to add the key points in the specified location, this program is a good example of the optical flow of learning. The program is based on OpenCV.

神经网路分割 神经网路分割 神经网路分割-neural network segmentation ne ural network segmentation ne ural network segmentation neural network segmentation Neural network segmentation

区域生长: 标注详细,参数可在程序中调整-Regional Growth: tagging detailed parameters can be adjusted in the procedure

图像处理论述，包括各个方面，主要涉及图形的处理，滤波等方面，值得一看-On image processing, including all aspects, mainly related to graphics processing, filtering, etc., see

30个图像处理的VC++ 源代码，包括256色转灰度图,Hough变换,image_j1,PCA,Walsh变换,对比度拉伸,二值化变换,反色, 方块编码,傅立叶变换,高斯平滑,灰度均衡,均值滤波,拉普拉斯锐化（边缘检测）, 离散余弦变换,亮度增减,逆滤波处理,取对数,取指数,梯度锐化,图象处理,图像镜像, 图像平移,图像缩放,图像细化,图像旋转,维纳滤波处理,用Canny算子提取边缘,阈值变换,直方图均衡.-30 image processing VC++ Source code, including 256 colors to grayscale, Hough transform, image_j1, PCA, Walsh transform, contrast stretching, binarization transformation, anti-color, box encoding, Fourier Transform , Gaussian smoothing, gray balance, mean filter, Laplacian sharpening (edge detection), discrete cosine transform, the brightness increases and decreases in inverse filtering deal, check on the number of check index, the gradient sharpening, image processing, mirror image, image translation, image scaling, image thinning, image rotation, Wiener filtering treatment using Canny edge extraction operator, threshold transform, histogram equalization.