Kmeans

比较新的图像处理类，2010版，并且有DEMO,方便应该(Relatively new class of image processing, 2010 Edition, and has DEMO, should facilitate)

阴影检测,基于OpenCV用于对图像中阴影的检测(Shadow detection, OpenCV for image shadow detection)

摄像头的标定，作为一般图像处理的第一步，显得尤为重要(Calibration of the camera, as a first step in the general image processing, it is particularly important)

利用棋盘格对相机进行标定，加入误差判定及像素空间到实际物理空间的距离计算(The camera is calibrated by checkerboard, the error is added and the distance of pixel space to the actual physical space is calculated)

基于meanshift算法的目标跟踪，主要是基于opencv车辆跟踪！！！程序当中进行简单的图像分割(Based on the meanshift algorithm of image segmentation and target tracking.)

基于互信息的图像配准源代码，，采用粒子群优化算法可直接使用。 (Based on mutual information image registration source code, using particle swarm optimization algorithm can be used directly.)

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)

基于OpenCV实现的图像剪切，截取小软件，对学习OpenCV的朋友比较有帮助(OpenCV based on the realization of the image shear, the interception of a small software, to learning more OpenCV friends help)

这本是用VC++来实现图像处理的书藉,对于学习图像处理的来说是非常有用的.(This is VC++ to realize image processing books, for learning image processing is very useful.)

图像的平滑函数，对指定区域的图像，并有门限值和魔板大小限制。(the smooth of a bmp image)