exp4

利用Mean-shift进行平滑处理，主要是对图像进行平滑的界面，MFC和OpenCV进行混合编程……(Mean-shift smoothing, image smooth interface, the MFC and OpenCV mixed programming ...)

图像增强的C++源程序，效果非常好，彩图ok(Image enhancement of the C++ source code, the effect is very good, Wallpapers ok)

功能很全的车牌识别系统，图像与处理，车牌定位，字符分割和字符识别等(Full license plate recognition system, image processing, license plate location, character segmentation and character recognition.)

图像变换,处理图片的变换及反走样处理，包含ＶＢ和ＶＣ的源文件(Image transformation, to deal with the change of image and anti-aliasing processing, VB and VC contains source files)

中值滤波，取出奇数个数据进行排序，用排序后的中值取代要处理的数据即可(median filtering.rar)

主成分分析PCA源代码（C++，matlab）主成分分析PCA源代码（C++，matlab）(Principal Component Analysis PCA source code (C++, Matlab), principal component analysis PCA source code (C++, Matlab))

本程序可以使用图像处理算法对图片进行处理，对于一个含有各种物体的图片，如米粒，可以计算物体的个数。使用前请配置好opencv环境。希望对大家学习图像处理和opencv有所帮助...(This procedure can use the image processing algorithm for processing images for a picture with a variety of objects, such as a grain of rice, can calculate the number of objects. Configured before use opencv environment. We would like to learn opencv image processing and help ...)

说明：  vc++调用matlab函数混合编程实现二值图像的区域标记。(vc++ call matlab function Matlab binary image of the regional markers.)

vb6 project photo see edit

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)