Image-ROI-Select

混合高斯模型使用K（基本为3到5个） 个高斯模型来表征图像中各个像素点的特征,在新一帧图像获得后更新混合高斯模型,用当前图像中的每个像素点与混合高斯模型匹配,如果成功则判定该点为背景点, 否则为前景点。通观整个高斯模型，他主要是有方差和均值两个参数决定，,对均值和方差的学习,采取不同的学习机制,将直接影响到模型的稳定性、精确性和收敛性。由于我们是对运动目标的背景提取建模，因此需要对高斯模型中方差和均值两个参数实时更新。为提高模型的学习能力,改进方法对均值和方差的更新采用不同的学习率 为提高在繁忙的场景下,大而慢的运动目标的检测效果,引入权值均值的概念,建立背景图像并实时更新,然后结合权值、权值均值和背景图像对像素点进行前景和背景的分类。(Gaussian mixture model using K (essentially 3-5) Gaussian model to characterize the features of each pixel in the image, in the image of the new frame for updated Gaussian mixture model, with each pixel in the image with a Gaussian mixture current model matching, if successful, determined that the point of the background points, otherwise the former attraction. Throughout the entire Gaussian model, he mainly has two parameters determine the variance and the mean, the mean and variance of the study, to take a different learning mechanism, will directly affect the stability, accuracy and convergence model. Since we are moving object extraction of the background modeling, so the need for the Gaussian model variance and mean two parameters real-time updates. In order to improve the learning ability of the model, an improved method for updating the mean and variance of different learning rates to improve in the busy scene, large and slow moving object detection results, the introduction of)

基于先验信息和射影几何变换的车牌图像矫正 对于图像矫正还是有帮助的(License plate image correction based on a priori information and projective geometry transform for image correction or help)

KALMAN filtering algorithm under the matlab toolbox, Shared by everybody, good source is very good

中国古代书法作品由于自然风化和人为因素导致的背景中包含大量噪声，重建背景图像，提高观赏价值。直接运行BackgroundFix.m即可(Since the background of ancient Chinese calligraphy works of natural weathering and human factors included a lot of noise, the background image reconstruction, improve the ornamental value. It can run directly BackgroundFix.m)

三自由度并联机器人工作空间求解matlab程序，用球坐标分割的空间(workspace for solution)

说明：  implementation of mser region detector

基于OPENCV的SIFT特征提取与匹配算法。包含完整的从图像高斯金字塔、DOG、空间极值点提取、关键点描述、KDtree匹配等关键步骤的全部函数实现，对全面深入理解Lowe的SIFT算法有莫大帮助。程序运行前须安装（1）OpenCV: http://opencvlibrary.sourceforge.net （2）SIFT: http://web.engr.oregonstate.edu/~hess/index.html，并配置其环境参数。(OPENCV the SIFT-based feature extraction and matching algorithm. Contains a complete Gaussian pyramid from the image, DOG, space extremum point extraction, description of key points, KDtree matching key step in the realization of the full function of the comprehensive and in-depth understanding of Lowe s SIFT algorithm of tremendous help. Program to run before the installation of (1) OpenCV: http://opencvlibrary.sourceforge.net (2) SIFT: http://web.engr.oregonstate.edu/ ~ hess/index.html, and configure the parameters of their environment.)

个人收集的一些关于小波理论在matlab中实现的文章(Personal collection of some articles on wavelet theory in matlab)

该程序是一种最小均方误差滤波算法的matlab实现，主要应用于干扰对消方面(The program is a minimum mean square error filtering algorithm matlab realize, mainly used in interference cancellation)

说明：  基于matlab的傅里叶光学仿真教程和光学原理讲解，有很多实用代码(matlab tutorial for fourier optics, containing simulation codes and basic theory)