Reconstuction3d

图形的剪裁算法源码，visual c++源码(The graphics cut algorithm source code, visual c++ Source)

说明：  基于灰度矩的亚像素边缘检测，零件边缘提取(Subpixel edge contour extraction)

Principal Warps: Thin-Plate Splines and the Decomposition of Deformations

一种基于特征点的图像匹配算法 一种基于特征点的图像匹配算法(Feature point based image matching algorithm based on feature points matching algorithm)

说明：  VC++.NET车牌识别、字符分割与归一化处理，图像对象BMP格式，程序将读取车牌的图像信息，归一化图像大小，动态分配存储图片的像素信息的二维数组，找到图像各列，从左列开始,垂直扫描，实施图片局部分割等，有兴趣编写车牌号识别的可参考对比下。(VC ++. NET license plate recognition, character segmentation and normalization processing, image object BMP format, the program will read the license plate image information, normalize the image size, dynamically allocate a two-dimensional array of pixel information to store the picture, and find the image columns , Starting from the left column, vertical scanning, partial image segmentation, etc. If you are interested in writing the license plate number recognition, please refer to the comparison.)

直方图均衡化的实现，RGB直方图均衡化，直方图归一化。(Histogram equalization to achieve, RGB histogram equalization, histogram normalization.)

一种利用中心和结构聚类的稀疏表示图像去噪方法，有不错的效果(a image denoising method with structral clustering and sparse representation, has good effect .)

极化SAR图像处理中的目标特征矩阵分解程序(Polarization SAR image processing target characteristic matrix decomposition process)

图像分割是把图像划分成具有实际意义的互补交迭的区域的集合。在图像分割之前，图像区域的数目未知，而在分割后各个区域同时满足均匀性和连通性的条件，故图像分割是一个复杂的过程，目前大多数研究都是针对某一类型图像或者某一具体应用的分割。图像阈值化分割的基本思想是确定一个阈值，然后把每个像素点的像素值和阈值相比较，根据比较的结果把像素划分为两类，前景(1)或背景(0)。该方法的关键是确定一个最优的阈值。常用的阈值确定方法有直接门限法、类间最大方差法(otsu法)、分水岭算法、最小误差法、最大熵法等。该段代码就是图像的阈值分割。(The image segmentation is divided into the practical significance of the emerging area of complementary set. In the image segmentation, before the number of image region, the unknown, and after each area in division at the same time satisfy the uniformity and connectivity condition, so the image segmentation is a complicated process now, most research are for a certain type image or a particular application of the division. Image threshold segmentation of the basic idea is to determine a threshold, then put each pixel threshold value of the pixels and compared, according to the result of the comparison the pixel divided into two categories, the prospect (1) or background (0). This method is the key to determine an optimal threshold. Commonly used method to determine the threshold value of direct threshold method, the largest of the variance between method (otsu method), watershed algorithm, the minimum error method, the maximum entropy method, etc. When the code is image threshold segm)

HBMA为基于块的分级匹配算法，是一种典型的运动估计算法，适用于特征追踪和运动估计(HBMA classification based on block matching algorithm is a typical motion estimation algorithm for feature tracking and motion estimation)