points-clouds-

图像处理系列之边缘检测篇 涵盖内容： 1>Roberts算子 2>Prewitt算子 3>Sobel算子 4>Laplacian算子(Edge Detection)

基于图像纹理的特征提取，使用灰度共生矩阵方法。(Texture feature extraction based on the use of gray level co-occurrence matrix method.)

这是二维图像去噪算法，C++版本，需自行配置工程使用(Image Denoising Method)

基于颜色特征的图像检索系统，，做 了GUI节目，直观(Color-based Image Retrieval System, made a GUI program, intuitive)

一种红外图像自适应对比度增强方法的仿真，绝对的真实，看到那些骗下载分的人恶心。需要自适应修改阈值T和A1，A2的值(An adaptive contrast enhancement method of infrared image simulation, absolutely true, see those who cheat download points. Need adaptive modified threshold T and A1, A2)

本文件为一个可以实现自适应滤波算法的函数。在去噪等方面有这较好应用。(This document is an adaptive filtering algorithms to achieve the function. This application has a good de-noising and so on.)

基于YCgCr色彩空间与几何信息的人眼定位方法(YCgCr color space and geometry based on the information the human eye location methods)

目标跟踪程序,使用matlab编写,采用CV模型,卡尔曼跟踪,有轨迹模拟,给出了跟踪的误差 目标跟踪,采用CV模型,卡尔曼滤波,给出模拟结果和跟踪结果,给出误差分析(Target tracking program, using matlab prepared, using the CV model, Kalman tracking, trajectory simulations have given a tracking error target tracking, using the CV model, Kalman filter, and track the results of the simulation results are given, error analysis is given)

基于互相关的图像配准程序，能实现亚像素级的配准(Sub pixel level registration based on cross correlation image registration process)

说明：  该课题为基于MATLAB平台的PCA的人脸识别图像考勤系统。传统的人脸识别都是直接人头和人头的对比，现实意义不大，这块都做烂了，不易通过毕设答辩，而且论文不好写。该课题识别原理为：从一副生活照中寻找到人脸，并且分割人脸图象，利用PCA算法进行降维，和库里图片进行对比，输出目标人脸以及记录识别的时间，可以统计人脸打卡的当月次数，从而统计出勤率。该课题还可以继续二次开发，做成库内外人脸的识别，如果是库外人脸则实现报警。GUI界面有清除数据功能，统计工资等功能。(This project is based on the MATLAB platform PCA face recognition image attendance system. The traditional face recognition is the comparison of direct head and head, which is of little practical significance. This part is not easy to pass the final defense, and the paper is not easy to write. The recognition principle of this subject is: find the face from a living picture, segment the face image, reduce the dimension by PCA algorithm, compare with the library picture, output the target face and record the recognition time, and then count the number of times in the month when the face is punched, so as to count the attendance rate. The subject can also be further developed to make face recognition inside and outside the database. If it is outside the database, the alarm can be realized. The GUI interface has the functions of data clearing and salary statistics.)