quanjingtupinheyuchuli

halcon图像处理软件用来检检测图像的圆状物体。可直接使用。 (halcon image processing software is used to check the oblong object detection image. Can be used directly.)

本程序为图像锐化的经典程序，源码里有详细的标注。(the procedures for sharpening images of the classic procedures are detailed source of tagging.)

实现BMP文件的基本功能。用C++实现一个Class，该Class具有读写BMP文件功能；该Class还具有对图像像素进行操作的功能（针对每个像素的读、写） (BMP files to achieve the basic functions. Using C++ implementation of a Class, the Class has read and write BMP file functions the Class also features the image pixel operation function (for each pixel of the read, write))

1.打开左右两张影像2.Harris算法提取同名点3.显示提取同名点（若要进行下一步匹配则不建议显示，这里只是用于查看是否提取出）4.相关系数匹配（只在找出的同名点内匹配）5.LSM最小二乘匹配（先进行粗匹配，再精匹配）(1 Open the left and right images 2.Harris algorithm to extract two tie points 3 shows the extraction of corresponding points (not recommended to proceed to the next match show, here is used to see if extracted) 4. Correlation coefficient matching (just looking match within a point of the same name) 5.LSM least squares matching (rough first match, then fine match))

说明：  能将256色图像转换为黑白图像，程序简单易行，适合初学VC者练笔。(Able to convert 256-color image black and white images, the program is simple, suitable for beginners who Lianbi VC.)

一种快速图像阈值分割法，不是otsu或迭代法，Wellner 1993快速自适应的图像二值化方法，有具体使用方法，很详细(A fast image thresholding segmentation method, not otsu or iterative methods, Wellner 1993 fast adaptive image binarization method)

图像处理缩放，大小随意改变，平滑处理，基于vb6.0设计(Zoom image processing, size change, smooth deal, based on the design VB6.0)

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.)

一种二值图像连通区域标记方法，能用于目标跟踪，我已经应用过，效果不错。(It is a new connected componet labeling algorithm for binary image,and can be used in object tracking. It is effective to be proved.)

生成四副条纹图，进行四步相移，并且进行相位解包裹，并以图片形式输出结果(Generate four fringes, were four-step phase shift and phase unwrapping, and output as a picture)