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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.)

对图像进行分块处理，可以设置分块比例，该程序设置的是8*8的比例，将图像分成64块(The image processing block, you can set the ratio of the block, the program is set proportion of 8* 8, the image is divided into 64)

Gerchberg-Saxton算法实现对图像相位的恢复，输入两张图片其中一张作为目标振幅。是对GS算法很好理解的一个程序。(Gerchberg- Saxton, algorithm of image recovery phase, one input two pictures as the target of amplitude.Is a program of GS algorithm is easy to understand.)

镜头指纹识别，提取镜头特征，对其他照片进行识别，判断是否来源同一相机。(Image Source Detection)

采用SVD方法进行人脸特征提取,希望对大家有用(SVD method using facial feature extraction, in the hope that useful to everybody)

提取人脸表情库中的图像数据,可提取任一种表情、任一个人或任一复本(extract the image data of facial expression database:JAFFE database。it is able to extract any expression, subject and copy of JAFFE database)

利用L1范数TV正则化对影像进行超分辨率重建(Super resolution reconstruction of images using L1 norm TV regularization)

说明：  广义灰度数学形态学滤波，输入信号，结构元素的长度，类型(Generalized gray-scale mathematical morphology filter, the input signal, the length of structural elements, type)

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)

houph变换，通过梯度函数得到图像的梯度矩阵，通过检测圆检测眼睛位置。(houph transform, through the gradient function to be the image gradient matrix, circle detection by detecting the location of the eyes.)