UIC

图像识别的小软件，识别率还算凑合吧，大家共同学习(Small image recognition software, the recognition rate still make it, we learn together )

说明：  视频动态报警开发,动态处理视频轨迹(Dynamic development of video alarm, dynamic video trajectory treatment)

计算机图像处理，MFC实现图像的直方图显示、直方图的均衡化，以及中值滤波等功能(Computer image processing, MFC histogram of image display, histogram equalization and median filter and other functions)

图像处理的IPP库使用手册，包括每个函数的使用说明，以及参数的意义。(IPP library of image processing using the manual, including instructions for each function, as well as the significance of the parameters.)

网格简化， 将复杂的带有很多细节的物体的三维立体网格进行任意比例的简化，使得其减少点和面片的数量并保持物体的基本特征，以达到加快图像显示及压缩文件的效果。(Mesh simplification, the complex three-dimensional grid with many of the details of the object simplified in any proportion, such that it reduce the number of points and surfaces of the sheet and keep the basic characteristics of the object, in order to achieve the speed up of the image display and the effect of the compressed file .)

基于规格化Hough变换的天波超视距雷达检测前跟踪算法(Hough transform based on the normalized horizon radar detection and tracking algorithms)

将图片转化为BMP位图，然后通过逐行扫描识别图片中的数字。(A picture into a BMP bitmap, and then through the progressive scanned image in the figure.)

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. )

用Visual C++实现基于数学形态学的数字图像处理,包括二值图像的腐蚀,膨胀,开,闭,细化及中轴变换等运算.(Visual C++ using mathematical morphology-based digital image processing, including binary image erosion and dilation, opening, closing, thinning, and the central axis transform operations.)

椭圆拟合，输入中心坐标及椭圆长半轴和短半轴即可画出相应椭圆(ellipse fitting)