RANSAC-for-Outlier-Rejection

基于区域阈值的图像分割方法研究，迭代阈值法分割技术(Regional threshold-based image segmentation method, iterative threshold segmentation)

一种点云数据的配准算法，可用于进一步的三维建模处理，配准效果良好。(One kind of point cloud data registration algorithm, three-dimensional modeling can be used for further processing, registration to good effect.)

一个很强大的图形计算处理软件，包括图像聚类，矩阵计算等(Scotch is a software package for graph and mesh/hypergraph partitioning, graph clustering, and sparse matrix ordering )

meanshift算法的车辆跟踪，效果非常好，改进版的，希望对大家有用(Meanshift algorithm of vehicle tracking, the effect is very good, improved version of the hope of the useful)

提取AVI格式视频文件为一帧一帧的jpg格式图片(Extraction of AVI format video files to a jpg format of a picture)

说明：  用最大相似性方法实现独立分量分析算法的matlab代码，可用于盲信号处理和图像滤波器构造。(with the greatest similarity method independent component analysis algorithm Matlab code can be used to blind signal processing and image filter structure.)

knn分类器，是数字图像处理与处理中经常使用到的一种分类方法！(KNN Classifier is the digital image processing and handling are often used as a classification method!)

快速傅里叶变换的C实现，采用新的倒序算法，程序代码只有一百多行，就要以实现千个采样点的计算(Fast Fourier Transform of C realized, the introduction of a new reverse algorithm, program code, only more than 100 lines, it is necessary to achieve the 1000 sampling points calculation)

论文介绍了一种SFS 算法的参数估计及其实现。它在考虑自遮掩影响的情况下, 有效地估计了SFS 算法中涉及的各种控制参数, 并引入亮度约束、灰度梯度约束和可积性约束, 计算出表面高度和表面向量, 实现三维重构。最后还指出了在Matlab 中实现需要注意的问题。(The paper introduced a SFS algorithm parameter estimation and its implementation. It under the condition of considering the covering effect, estimates the SFS algorithm effectively involved in all kinds of control parameters, and introduces brightness constraint, gray level gradient constraint and the integrability of constraints, calculate the surface height and surface vector, realize the three-dimensional reconstruction. Finally, points out the problems requiring attention is realized in Matlab. )

这是一个常用的基于Fcm的图像分割源程序，希望对大家有用(This is a commonly used image segmentation based on FCm source, in the hope that useful to everybody)