BoundaryDetectionVc++Res

说明：  基于Kmeans算法的图像分割，一般Kmeans是数据挖掘中用来聚类的，本试验利用图像中的灰度值作为Kmeans算法的原始点，进行图像分割(Kmeans algorithm based on image segmentation, data mining in general Kmeans is used to clustering, the trial use of the image gray value as the original algorithm Kmeans spots for Image Segmentation)

KMeans图像聚类分割：用K-Means聚类方法来对图像进行分割。主要是对图像的颜色进行聚类。开发环境：VC6，需要安装OpenCV。(KMeans clustering in image segmentation: with K-Means clustering approach to image segmentation. Mainly the color of the image cluster. Development Environment: VC6, need to install OpenCV.)

online random forest 在线随机森林做跟踪和分类的代码(online random forest-line tracking and classification random forest to do the code)

数字散斑相关程序，能够计算2副图片的位移，简单的例子，对初学者也许有用。(Digital speckle correlation program can calculate the displacement of two images, a simple example, may be useful for beginners.)

说明：  详细介绍了多普勒天气雷达系统建模与仿真应用 (Details of the Doppler Weather Radar System Modeling and Simulation Application)

2009年CVPR最佳论文《Single image haze removal using dark channel prior》暗原色图像去雾的算法实现。与原文不同的是本程序没有完成最后matting细化效果的部分，但仍能够达到视觉上可以接受的去雾效果。计算机视觉课程作业。工程运行于VS2008环境，需要OpenCV支持。Debug目下exe文件可以直接双击运行查看结果。(CVPR 2009 Best Paper " Single image haze removal using dark channel prior" to the dark fog of the primary image algorithm. The difference is that with the original program did not complete the final matting refinement part，yet haze-removal result is visually acceptable. Visual course work. This project runs under VS2008 with OpenCV. Double click the exe file under Debug folder to check the final result.)

图像细化注意，本程序的细化算法要应用于于含线条的黑白二值图像才可以看出细化效果。 (The thinning Note refinement algorithm of this program is to be applied to black and white binary image containing lines can be seen that the refinement effect.)

（1）在工具栏中点击“打开”功能出现文件打开窗口，用户选择一幅bmp图片后在指定区域居中显示该图片，若图片尺寸小于指定区域则按原始大小显示；若大于则按合适比例显示。 （2）鼠标指针在图片上停留时显示为十字形，同时在控件下方固定位置显示鼠标所在的图像x坐标和y坐标（如：50，100），以图片左上为坐标原点。 （3）在工具栏中可以点击控件实现在图片上绘制一次直线、矩形或圆等图形，在绘图过程中要求图片和图形一直可见，不能出现刷新痕迹，绘制的图形可以任意修改形状。 （4）可以任意选择图形线条的类型（虚线或直线）、颜色（三种）及粗细（三种），要求选择方式可以叠加，绘制过程要求可任意连续执行。 （5）在工具栏中点击“保存”功能出现文件保存窗口，用户可以选择保存路径来保存当前图片操作结果（包括图片和图形）。 （6）点击“关闭”功能，关闭当前图片，若操作结果尚未保存则必须弹出对话框提示用户进行保存。 ((1) in the tool bar, click on Open function has the file open window, the user selects a bmp image to center the picture in the designated area, if the image size is smaller than the specified area press the original size if more than press the appropriate scale display. (2) is shown as a cross when the mouse pointer over the image, while displaying an image x and y coordinates of the mouse cursor in a fixed position below the control (eg: 50,100) to image the upper left of the coordinate origin. (3) in the toolbar you can click controls to achieve a draw straight lines, rectangles or circles and other graphics on the picture, the requirements of pictures and graphics in the drawing process has been seen, it can not appear refreshed traces drawn graphics can be modified shape. (4) can choose the type of graph line (dashed or straight), color (three kinds) and thickness (three kinds), asked to choose the way can be superimposed, can arbitrarily draw process requires continuous exe)

本书系统地介绍了图像处理与识别的基本原理、典型方法和实用技术。全书共分12章，第1章～第6章是图像处理与识别的基础内容，包括图像科学综述、MATLAB语言图像编程、图像增强、图像分割、图像特征提取和图像识别；第7章～第10章是图像处理与识别的工程实例，涵盖了医学图像处理、文字识别和自导引小车路径识别等应用实例，并结合理论算法，提供了大量MATLAB代码程序，以帮助读者掌握如何使用MATLAB语言快速进行算法的仿真、调试和估计等方法。第11章～第12章，是两个综合性较强的实例，分别是Visual C++实现的基于神经网络的文字识别系统和车牌定位系统。 本书附带的光盘给出了各个章节列举的实例的源代码，同时赠送了28个常用数字图像处理算法的Visual C++代码实现。 本书讲解深入浅出，实例程序丰富，注重理论与实践相结合。本书可作为计算机应用、自动化、图像处理与模式识别、机电一体化专业的高年级本科生或研究生的参考书，也可供从事图像处理与识别的研究人员和工程技术人员阅读参考。(This book introduces the basic principles of image processing and recognition of the typical methods and practical skills . The book is divided into 12 chapters , Chapter 1- Chapter 6 is the basis of the content of image processing and recognition , including images scientific overview , MATLAB programming language images, image enhancement, image segmentation, image feature extraction and image recognition Chapter 7- Section Chapter 10 is a project example image processing and recognition , covering the medical image processing, character recognition and self- guided trolley path recognition example , the combination of theory and algorithms, for a lot of MATLAB code procedures to help readers learn how to use MATLAB language fast simulation , debugging and estimation methods algorithm. Chapter 11- Chapter 12 , are two examples of highly integrated , namely Visual C++ implementation based on neural network character recognition system and a license plate positioning system. The book)

（2001何斌+光盘）Visual c++数字图像处理（第二版），使用VC进行数字图像处理的相关资料，十分实用！((2001 Bin+ disc the) Visual c++ digital image processing (second edition), digital image processing using VC, very practical!)