CvThrehold

对BMP文件进行图像处理，包括：边缘检测、频域变换、几何变换、图像变换校正、灰度变换、图像编码、平滑和匹配(BMP files for image processing, comprising: an edge detection, a frequency domain transformation, geometric transformation, image transformation correction gradation conversion, image coding, and matching the smooth)

26个不同影像处理程序,以VC++开发,是了解影像入门好帮手(26 different image processing procedures to VC++ Development is helpful to understand the image entry)

老外写的程序，可对三角形进行渲染，有详细的算法介绍。非常棒(A good Triangle Renderer Project，with detailed introduction.)

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)

一种基于non-sample的纹理合成demo，程序性能还有待优化，效果还不错.(texture synthesis demo.)

小波处理，滤波，复原，融合等VC源代码.(Wavelet processing, filtering, recovery, integration VC source code.)

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)

绣花问题是连续型的填充，在不同区域的缝制过程中，缝针不能提针，因此不能用一般的离散型区 域填充方法处理。本文运用几何计算和图论理论提出了一个绣花缝针轨迹自动生成算法：先对轮廓走向进行 定义，通过轮廓铅垂方向的局部极值点的分割线将图案从上向下进行分割，采用交点的特征值比较彻底的解 决了分割时的重点问题，将图案区域准确的划分成缝针能一次完成的若干个节点。在此基础上根据节点的邻 接关系建立节点的邻接“图”，通过图论中半哈密尔顿路径或深度遍历方法找到节点的遍历（缝制）序列和每 个节点的缝制方向，最后可对设定的起点、终点和缝针间隔的条件自动提供缝针的走向轨迹。(In the process of embroidering, needle can not hang up for changing to a different area. Therefore, Embroider problem could be abstract as a continuous area-filling work. Considering disperse area-filling methods can not process this problem well. Based on geometry computing and graph theory, an algorithm of finding path of embroidering needle are proposed in this paper. First, outline orientations are defined, and finding all local extreme points of inner outline on their gravitational orientation to build sectioning lines so as to divide the picture. By using intersection point character the overlap point problem was solved perfectly. Therefore, the picture is divided into some nodes which can be finished alone. Then, based on connections of these nodes, an adjacency graph of nodes was built. Using half-Hamilton path or depth-first search method, both embroidering sequence and direction of these nodes could be got from the graph. Finally, from a defined start-point, end-point)

是关于图像的基础操作，包括图像倾斜矫正，图像增强，去除噪声，图像压缩等技术(It is on the image on the basis of operations, including image tilt correction, image enhancement, noise removal, image compression technology)

一幅大小为256×256的256级灰度图像（每像素8bit） 如果图像的各个像素之间是统计独立的，求该图像的信息熵 -离散无记忆信源 如果图像的各个像素之间不是统计独立的，求该图像的信息熵 -图像像素的概率分布模型(A 256 gray scale image (8bit per pixel) with a size of 256 x 256 If each pixel of the image is statistically independent, the information entropy of the image is calculated Discrete memoryless source If each pixel of the image is not statistically independent, the information entropy of the image is calculated Probability distribution model of image pixels)