Hough-matalab

用fibonacci变换方法对图象做置乱或逆置乱，效率极高，在信息隐藏中属常用的方法之一。调用函数为f=fibonacci_t(I,r,s)，其中参数分别为I=被置乱的图像，r=置乱密钥，s=0置乱，s=1逆置乱(Fibonacci transformation method used to do on the image or inverse Scrambling Scrambling, high efficiency in the information hidden in one of the methods are commonly used. Call the function f = fibonacci_t (I, r, s), which parameters were I = have been scrambling the image, r = scrambling key, s = 0 Scrambling, s = 1 inverse Scrambling)

matlab 写的提取图像亚像素边界的程序，和Canny算子有比较，里面有两张示例图像！(matlab write the image to extract sub-pixel border procedures, and the Canny operator have more, there are two examples of images!)

光流法的程序，利用传统光流法思想，亲测有效，效果不错(Optical flow method program, pro-test, good results)

基于opencv实时图像的2值化处理，一定要有摄像头(Opencv-based real-time image processing of two values, there must be a camera)

图像的三种分水岭分割方法，一般分水岭分割，使用梯度的两次分水岭分割及使用梯度加掩模的三次分水岭算法(images of the three watershed segmentation method, the general watershed segmentation, gradient of the two watershed segmentation and the use of the gradient increases mask the three watershed algorithm)

用于求解凸优化问题，恢复低秩密度矩阵问题(this matlab Algorithm can be used for the convey optimal problen, and also for the low-rank density matrix reconstruction)

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)

作者:J.Kittler and J.Illingworth KI阈值算法(Author：J.Kittler and J.Illingworth 1986)

说明：  Harris角点检测，关于角点的应用在图像处理上比较广泛，如图像匹配(FPM特征点匹配)、相机标定等。网上也有很多博客对Harris角点检测原理进行描述，但基本上只是描述了算法流程，而其中相关细节并未作出解释，这里我想对有些地方做出补充说明，正所谓知其然知其所以然，如有不对，还望指正。(Harris corner detection)

Image Indexing Using Color Correlogram