gaues_

将一幅rgb图像转换成灰度图像，并显示出灰度图像。(the functon is to make a rgb image to gray image.)

根据RBM深度网络（Hinton，2006）进行MINST手写文字的分类器的训练，利用训练得到的权值制作了这个小程序，通过这个程序可以看出训练结果对数据集内的测试样本和训练样本都能进行很好的识别，但是对其他的手写字体识别就没有那么好了。(According to RBM depth network (Hinton, 2006) conducted MINST handwritten text classifier training, using the training to get the right value to produce this small program, this program can be seen through the results of the training data set and the training sample test samples are can be well identified, but on the other handwriting recognition is not so good.)

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.)

在图像中加入椒盐噪声的源代码，编译后的可执行文件须带参数运行(the image Salt and Pepper to the noise source, the compiled executable file parameters required to bring Operation)

Abstract—Noninvasive ultrasound imaging of carotid plaques allows for the development of plaque-image analysis methods associated with the risk of stroke. This paper presents several plaqueimage analysis methods that have been developed over the past years. The paper begins with a review of clinical methods for visual classification that have led to standardized methods for image acquisition, describes methods for image segmentation and denoizing, and provides an overview of the several texture-feature extraction and classification methods that have been applied. We provide a summary of emerging trends in 3-D imaging methods and plaque-motion analysis. Finally, we provide a discussion of the emerging trends and future directions in our concluding remarks.

VIBE用于视频背景建模，经典算法，C++和matlab代码都有，文件是全的。(VIBE for video background modeling, classical algorithms, C++ and matlab code has a file is complete.)

Canny边缘检测算法,已经试过，可以用。能较好的检测边缘。(Canny edge detection algorithm, has been tried, you can use. To better edge detection.)

一种改进的基于蚁群算法的图像边缘检测文献，前沿论文(ant colony system,matlab)

三维激光点云配准是点云三维建模的关键问题之一。经典的 ICP 算法对点云初始位置要求较高且配准 效率较低，提出了一种改进的 ICP 点云配准算法。该算法首先利用主成分分析法实现点云的初始配准，获得较好 的点云初始位置，然后在经典 ICP 算法的基础上，采用 k － d tree 结构实现加速搜索，并利用方向向量夹角阈值去除 错误点对，提高算法的效率。实验表明，本算法流程在保证配准精度的前提下，显著提高了配准效率。 (Three-dimensional laser point cloud registration is one of the key three-dimensional point cloud model. High classical ICP algorithm to the initial position of the point cloud registration requirements and low efficiency, proposed an improved ICP point cloud registration algorithm. Firstly, the use of principal component analysis of the initial point cloud registration, get a better initial position of the point cloud, then the basis of classical ICP algorithm using k- d tree structure to achieve speed up the search, and using the direction vector angle the removal of the threshold point error and improve the efficiency of the algorithm. Experiments show that the algorithm processes to ensure the accuracy of registration under the premise, significantly improve the efficiency of registration.)

LK 和HS光流代码，初学者可用，带有误差分析(LK optical flow and the HS code is available for beginners, error analysis with)