poshecai

本代码主要给出了激光粒度仪颗粒散射光强分布以及4种粒度反演算法，以及4种算法之间的比较。四种反演算法为：TSVD、Chaine、Tikhonov和l1正则化。(The code gives the Zetasizer particle scattering intensity distribution, and four kinds of particle inversion algorithm, as well as a comparison between the four algorithms. Four kinds of inversion algorithm is: TSVD, Chaine, Tikhonov and l1 regularization.)

采用近邻插值和双线性插值两种插值方法，对图像进行放大处理。(Neighbor interpolation and bilinear interpolation using two kinds of interpolation methods to enlarge the image processing.)

hausdorff距离，用于图像处理中比较两幅图像的差异的方法。其鲁棒性较好。(hausdorff distance, for the image processing of the images compared two different methods. Its robustness better.)

用lbp实现纹理特征提取，并分类说明: 一共有三个m文件，一个是lbp.m, 存放主要的lbp算法， 一个是getmapping,用以做算法的辅助函数， 一个是lbptest.m,存放着测试代码。 这三个文件需要放到同一个文件夹，并在文件夹中添加相应的图片， 具体的图片名字见lbptest.m的代码，运行lbptest.m可以查看结果。代码最后给出效果图 这三个文件是最传统的LBP方法，有256种。(With lbp achieve texture feature extraction and classification Description: A total of three m files, one is lbp.m, store the main lbp algorithm, One is getmapping, helper functions for doing arithmetic, One is lbptest.m, kept the test code. These three documents need to put the same folder, and add the appropriate folder, pictures, See lbptest.m specific name of the picture of the code, run lbptest.m can view the results. Finally renderings code These three documents are the most traditional LBP method, there are 256 kinds.)

TurboPixels超像素生成算法，matlab运行，(TurboPixels super pixel generation algorithm)

【实例简介】 云信开源的电子白板，有web、android、ios、qml

pca+fisher 人脸识别MATLAB程序，附加图像数据库，适合简单的人脸识别。 (pca+ fisher face recognition program using MATLAB , adding image database for easy recognition.)

捷宇 高拍仪 demo SDK

说明：  针对输入180个波束数据，通过使用抛物线插值法进行插值，最终得到720个波束的数据，用于图像显示(For 180 beam data input, 720 beam data are obtained by parabola interpolation method for image display)

一种基于otsu的二维灰度图像分割算法，包括注释和源代码，适合初学者使用。(A two-dimensional gray image segmentation algorithm based on Otsu, including annotation and source code, which is suitable for beginners.)