NMF_FeatureGet

Simple Shape Detection using Hough Transform 用霍夫变换做为形状检测的matlab源码,从matlab官网下载(Simple Shape Detection using Hough Transform Hough transform used as a shape detection matlab source, from the official website download matlab)

有关于求取图像相关系数的matlab M 文件；虽然很简单，但可以为你省去那么一点时间。 共享改变未来！(Correlation coefficient on the strike' s matlab M image file although very simple, but it can save you some time. Share changes in the future!)

基于SIFT的图像配准程序 SIFT特征匹配算法是目前国内外特征点匹配研究领域的热点与难点,其匹配能力较强,可以处理两幅图像之间发生平移、旋转、仿射变换情况下的匹配问题,甚至在某种程度上对任意角度拍摄的图像也具备较为稳定的特征匹配能力(Hot and difficult of the current research areas of domestic and foreign feature point matching based the SIFT image registration program SIFT feature matching algorithm is its ability to match between the two images, can handle translation, rotation, affine transformation case match problem, even in some degree images taken at any angle with more stable feature matching ability)

本算法在Matlab2008b 环境下实现。包括main,san 和ssd 三个函数。 这次实现的算法并不是比较两个已经知道的点是否匹配，而是已知一个图形中的特征点，在另外一个图像中找到与其最匹配的点，匹配度用SAD 或者SSD 来度量。 main.m 是程序的入口，包括生成和读入实验数据，调用sad 函数和ssd 函数求匹配点，最后绘 制出最后的结果。sad.m 是用sad 度量方法在另一图中求解匹配点的函数实现，有3 个参数 y=sad(x,image1,image2)。其中x 是代匹配的数据，image1 是图像1 数据，image2 是图像2 数据。 从理论上分析，ssd 比sad 算法要复杂一点，经过测试，在一幅640*480 的图像中寻找10 个匹配点数据SAD 用时25.062519 秒，SSD 用时25.291432 秒。(The algorithm Matlab2008b environment to achieve. Including the main, san, and ssd three functions. The implementation of the algorithm is not the point of comparing two matches already know, but the known feature points in a graphic, an image found in the other match with the most points, matching measured with the SAD or SSD. main.m is the entry, including the generation and reading test data, call the sad ssd function evaluation functions and matching points, and finally draw the final result. sad.m measure is sad figure in another match point in the function implementation to solve, there are three parameters y = sad (x, image1, image2). Where x is the generation of matching data, image1 is the data image 1, image2 is the image 2 data. From the theoretical analysis, ssd little more complicated than the sad algorithm, tested in a 640* 480 images of 10 match points in the search for data using time 25.062519 seconds SAD, SSD with time 25.291432 seconds. )

输入图片的一阶矩、二阶矩、三阶矩。颜色空间可以在计算前更改( the first moment, second moment and third moment of the picture)

基于轮廓波变换的图像硬阈值去噪程序，并通过等效视数、斑点噪声指数进行评价(Hard-based image thresholding wavelet transform program outline and uated by ENL, speckle noise figure)

alpha稳定分布,密度函数图形，这较少出现。(alpha-stable distribution，picture of pdf,it s very rare)

C# 实现验证码识别

用奇异值分解的方法实现图像压缩，有助于初学者了解奇异值分解的应用(Using singular value decomposition method to achieve image compression will help beginners understand the application of singular value decomposition)

在Matlab平台下实现人脸检测的一个程序(In Matlab platform to achieve a face detection process)