MeanShiftcode

用matlab编写的harris角点检测与匹配程序，适用于matlab图像处理与编程(Matlab prepared with harris corner detection and matching procedures, applicable to matlab image processing and programming)

转：https://blog.csdn.net/jinshengtao/article/details/26278725 混合高斯背景建模是基于像素样本统计信息的背景表示方法，利用像素在较长时间内大量样本值的概率密度等统计信息(如模式数量、每个模式的均值和标准差)表示背景，然后使用统计差分(如3σ原则)进行目标像素判断，可以对复杂动态背景进行建模，计算量较大。 在混合高斯背景模型中，认为像素之间的颜色信息互不相关，对各像素点的处理都是相互独立的。对于视频图像中的每一个像素点，其值在序列图像中的变化可看作是不断产生像素值的随机过程，即用高斯分布来描述每个像素点的颜色呈现规律单模态(单峰)，多模态(多峰)(Gaussian mixture background modeling is a background representation method based on the statistical information of pixel samples. Statistical information such as the number of patterns, the mean and standard deviation of each pattern are used to represent the background. Statistical difference (such as 3_principle) is used to judge the target pixel. Complex dynamic background modeling has a large amount of computation. In the Gaussian mixture background model, it is considered that the color information between pixels is uncorrelated and the processing of each pixel is independent of each other. For each pixel in a video image, the change of its value in a sequential image can be seen as a random process that produces pixel values continuously, i.e. Gaussian distribution is used to describe the regularity of color rendering of each pixel in single mode (single peak) and multi-mode (multi-peak).)

图像畸变校正技术的matlab源代码，涉及到图像的空间变换和灰度插值等技术。(Matlab source code of the image distortion correction technology related to space transformation and grayscale image interpolation technology.)

说明：  使用matlab工具箱进行的图像配准，需提取特征点来实现配准(Using matlab toolbox for image registration, extraction of feature points needed to achieve alignment)

叠加平均去噪过程的实现，信号产生，加噪，去噪效果的显示(Average denoising, signal generation, noise addition, display the denoising effects)

【实例简介】

gmkl算法源码，广义多核学习，可用图像多类分类。(gmkl algorithm source, the a generalized multicore learning, free image multi-class classification.)

说明：  图像处理，运动放大，视频代码展示，以及输出结果(steerable pyramid algorithm)

标准Hough检测圆，在数字图像中检测圆形目标，需要先边缘提取，在二值图像中检测圆。(circle detection using standard hough transform )

SSD: Single Shot MultiBox Object Detector, in PyTorch A PyTorch implementation of Single Shot MultiBox Detector from the 2016 paper by Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang, and Alexander C. Berg. The official and original Caffe code can be found here. Table of Contents Installation Datasets Train Evaluate Performance Demos Future Work Reference