prient

说明：  VC的一些工程案例，包括车牌识别，人脸识别，图像处理基本操作等(car license recognization system)

高斯混合模型的源代码。从文件中读取数据，用三个高斯混合模型进行处理(Gaussian mixture model of the source code. Read from the file data, using three Gaussian mixture model for processing)

说明：  用于物体目标轮廓的提取与跟踪，能更好的识别出物体轮廓。(Target contour for object extraction and tracking, to better identify the contours of objects.)

对火焰图像进行二值化 边缘检测 链码提取 并计算火焰图像的面积和周长 绝对好用！(Binarization flame image edge detection chain code extraction and absolutely easy to calculate the area and perimeter of the flame image!)

图像处理中图像几何畸变校正程序，用于图像的广角畸变的校正。(Image processing procedures for image geometric distortion correction for images of wide-angle distortion correction.)

非常好的klt算法的事例程序源码，大大家多多下在亚，谢谢大家乐 (Very good klt algorithm example program source code, large lot next in Asia, and thank you for music)

说明：  分块直方图均衡化处理图像 用户输入分块的x,y方向的分块个数，即可将图形分成各个小块进行直方图均衡化。 大津法处理图形，包括一维大津法和二维大津法的实现 (the realization of the Histogram equalization algorithm. the realization of otsu algorithm to process the images)

EDLines是一种快速直线检测算子，2012年在ICCV上提出，也是目前处理直线检测最快的算法之一，该算法包含三个步骤：（1）边缘提取：利用Edge Drawing (ED)算法[28,29]从灰度图像中提取边缘片段；（2）线段检测：利用最小二乘法提取直线段；（3）线段确认：遵循Helmholtz定律，从已提取的直线段中摒弃虚假线段。EDLines算法的优越性得益于Edge Drawing (ED)算法能够从灰度图像中准确、快速、稳定地提取出光滑、完整的边缘片段。Edge Drawing (ED)算法包含以下步骤： （1）采用size=5*5,σ=1的高斯核对灰度图像进行平滑滤波，去除噪声； （2）采用一种常用的梯度算子，如Prewitt、Sobel或Scharr等计算平滑后图像中每个像素点的梯度幅度和梯度方向； （3）将梯度图中邻域内幅度最大的像素点标记为锚点，这些锚点成为图像边缘点(edge elements)的概率很大； （4）将相邻的锚点连接成边缘线。从一个锚点起始，ED利用相邻像素的梯度幅度和方向在梯度为最大值的锚点之间游走。 (Edge Drawing (ED) is our recently-proposed, novel, fast edge detection algorithm. What makes ED stand out the existing edge detectors, e.g., Canny, is the following: While the other edge detectors give out a binary edge image as output, where the etected edge pixels are usually independent, discontinuous entities ED produces a set of edge segments, which are clean, contiguous, i.e., connected, chains of edge pixels. Thus, while the output of the other edge detectors requires urther processing to generate potential object boundaries, which may not even be possible or result in inaccuracies ED not only produces perfectly connected object boundaries by default, but it also achieves this in blazing speed compared to other edge detector.)

打开24位彩色bmp文件, 显示该图像 将图像内容顺时针旋转90度后显示出来 将图像分成等大小的4块，将第1和第3块像素互换后保存 将旋转后的图像转换成灰度图像显示，并保存 对灰度图像求Sobel边缘图，显示出来，并保存 对灰度图像进行Gaussian平滑，并保存（需要体会平滑的作用） 对灰度图像进行2值化(Open 24-bit color bmp files, displays the image will rotate clockwise image content displayed image is divided into four equal-sized 90 degrees, the first and three pixels after swap to save the rotated image conversion ashes of the image display, and save images to grayscale seeking Sobel edge map is displayed, and save the gray image Gaussian smoothing, and save (experience required smoothing effect) grayscale image binarized)

源点定位程序，可用于检测连通域等功能，代码是c/c++的，放心使用。(Source point positioning procedures, can be used to detect other functions connected domain, the code is c/c++, and ease of use.)