mean-shift

说明：  掌纹识别代码，对图像预处理和特征提取及匹配(Palmprint identification code, the image preprocessing and feature extraction and matching)

图形图像处理中的平滑处理，可以实现部分的功能，但是还可以继续完善(Graphic image processing smoothing, can achieve some of the functions, but can also continue to improve)

可以将连续图片转换成视频文件，值得参考学习(Convert a continuous image into a video file)

基于FFT的配准程序，用在图像配准中的粗匹配中，对噪声、图像中物体发生运动等极为鲁棒！ (FFT-based registration procedure, used in image registration in the coarse matching, noise, motion and other image objects occur very robust!)

有关目标的匹配跟踪代码，简单易懂，里面含有丰富的测试图片，和最终的测试效果图(The target matching tracking code, easy to understand, which contains a wealth of test images, and the final test renderings)

绣花问题是连续型的填充，在不同区域的缝制过程中，缝针不能提针，因此不能用一般的离散型区 域填充方法处理。本文运用几何计算和图论理论提出了一个绣花缝针轨迹自动生成算法：先对轮廓走向进行 定义，通过轮廓铅垂方向的局部极值点的分割线将图案从上向下进行分割，采用交点的特征值比较彻底的解 决了分割时的重点问题，将图案区域准确的划分成缝针能一次完成的若干个节点。在此基础上根据节点的邻 接关系建立节点的邻接“图”，通过图论中半哈密尔顿路径或深度遍历方法找到节点的遍历（缝制）序列和每 个节点的缝制方向，最后可对设定的起点、终点和缝针间隔的条件自动提供缝针的走向轨迹。(In the process of embroidering, needle can not hang up for changing to a different area. Therefore, Embroider problem could be abstract as a continuous area-filling work. Considering disperse area-filling methods can not process this problem well. Based on geometry computing and graph theory, an algorithm of finding path of embroidering needle are proposed in this paper. First, outline orientations are defined, and finding all local extreme points of inner outline on their gravitational orientation to build sectioning lines so as to divide the picture. By using intersection point character the overlap point problem was solved perfectly. Therefore, the picture is divided into some nodes which can be finished alone. Then, based on connections of these nodes, an adjacency graph of nodes was built. Using half-Hamilton path or depth-first search method, both embroidering sequence and direction of these nodes could be got from the graph. Finally, from a defined start-point, end-point)

图像修复中基于一幅图像的改进的Criminisi方法的近，算法的时间大大提高，修改效果也不错。(Time based on the improved image Criminisi near algorithm greatly improve image repair, modify the effect is also good.)

本程序采用pca提取人脸特征，采用人工神经网络识别人脸。(This procedure using pca face feature extraction, using artificial neural network recognition face. )

图像的自动拼接和缝补，采用sift算法作为匹配，是学习全景图像拼接的基础，大家可以下载下来看看(Automatic image stitching and sewing, using sift algorithm as a match, is the basis for learning panoramic image mosaic, you can download to see)

说明：  基础SAD算法代码，最基本的图像匹配处理方法，也是最常用的基本法，有助于新手理解(Basic sad algorithm code)