PCA

点云关键点搜索，根据曲率极值法搜索关键点(PCL:keypoint detection, used for registration and segmentation)

HOG adaboost pedestrian-detect

摄影测量的一个开源代码，内部含有后方交会、前方交会、相对定向、立体量测、像点匹配等功能源代码。(An Photogrametry open source project, including intersection, relative oriention, stereo measure, image matching source code.)

图像边缘检测，实现了几种边缘检测算法，像Roberts，Sobel，Prewitt，Canny等(Edge detection, edge detection algorithm to achieve several, such as Roberts, Sobel, Prewitt, Canny, etc.)

说明：  ：建立了碳钢渗硫表面和非渗硫表面的多球凸峰面接触模型，模型中，凸峰高度按高斯函数分布．用塑性流线 理论分析了渗硫层的摩擦系数．计算结果表明：摩擦系数随载荷的增加而增加；相同粗糙度下，磨削加工的摩擦系 数比车削加工的摩擦系数大；摩擦系数随着渗层厚度的增大而增大．从减小摩擦系数的角度来考虑，渗硫层并非 越厚越好． (the multi-asperity sphere-shape model for surface contact between sulphurized layer and unsulphurized layer is established．in which the height of sphere-shape asperities follows the Gaussian distribution．1he frictional coeficients of sulphurized layers are analyzed by using plastic flown line theory．1he results show that the frictional coeficient increases with the load．the frictional coeficient of ground surface is higher than that of tumed surface in case of the same roughness．1he thicker the sulphuri[ed layer is．the higher the frictional coeficient is．From the viewpoint of reducing frictional coeficient，the thickness of sulphurized layer should be smaller．)

vc6.0 控制摄像头源代码，采用directxshow 效率很高，小弟参考了很多的资料才搞明白，和大家共享，希望对大家有帮助(camera control vc6.0 source code, the use of highly efficient directxshow,小弟reference a lot of information in order to engage in to understand, and share, in the hope that we have to help)

Pyramid methods in image processing

行人检测HOG+SVM进行图片中行人检测，提供训练用的pos和neg样本，效果还可以；没有SVM工具箱的，压缩包里已经提供了，安装一下即可(Pedestrian detection HOG + SVM for pedestrian detection in pictures, providing POS and neg samples for training, the effect is good; without SVM toolbox, the compression package has been provided, just install it.)

：植物种类识别方法主要是根据叶片低维特征进行自动化鉴定。然而，低维特征不能全面描述叶片信息，识别准确率低，本文提 出一种基于多特征降维的植物叶片识别方法。首先通过数字图像处理技术对植物叶片彩色样本图像进行预处理，获得去除颜色、虫洞、 叶柄和背景的叶片二值图像、灰度图像和纹理图像。然后对二值图像提取几何特征和结构特征，对灰度图像提取 Hu不变矩特征、灰 度共生矩阵特征、局部二值模式特征和 Gabor 特征，对纹理图像提取分形维数，共得到 2183 维特征参数。再采用主成分分析与线性 评判分析相结合的方法对叶片多特征进行特征降维，将叶片高维特征数据降到低维空间。使用降维后的训练样本特征数据对支持向量 机分类器进行训练(plant species identification method is mainly based on blade automatic identification of low dimensional characteristics.However, can not fully describe blade low-dimensional feature information, identification accuracy is low, in this paper A kind of plant leaves recognition method based on multiple feature dimension reduction.First by digital image processing technology to the plant leaf color sample image preprocessing, obtain background color removal, wormhole, petioles, and the blades of a binary image, gray image and texture image.Then the binary image to extract the geometric characteristics and characteristics of structure and characteristics of gray image extraction Hu moment invariants, gray co-occurrence matrix feature, local binary pattern features and Gabor, to extract the fractal dimension of texture image, get 2183 d characteristic parameters.By principal component analysis and linear uation analysis method of combining the characteristics of blade more feature dimensi)

数字图像处理方面的常用操作 人脸识别 图像打开和保存 类似photoshop操作 (Digital image processing operations commonly used face recognition and preservation of the image to open a similar operation photoshop)