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图像处理中的图像分割grabcut算法，经试验可以达到很高的精确度，比较难，值得研究(Image Processing Image Segmentation grabcut algorithm, the test may be achieving a high degree of accuracy, more difficult, is worth studying)

数字信号处理实验，DCT图像压缩，内含有matlab实验m文件以及实验报告，供大家参考。(Digital signal processing experiment, DCT image compression, contains matlab experiment m documents and the experiment report for your reference.)

对输入的一张彩色图像，自己写代码实现Harris Corner 检测算法： 1. 不能直接调用OpenCV 里面与Harris 角点检测相关的一些函数； 2. 只能用C/C++，不能用其他语言； 3. GUI 只能用自带的HighGUI，不能用QT 或其他的； 4. 平台可以用Windows， Linux, MacOS； 5. 显示中间的处理结果及最终的检测结果，包括最大特征值图，最小特征值图，R 图（可以考虑彩色 展示），原图上叠加检测结果等，并将这些中间结果都输出成图像文件； 6. 命令格式： “xxx.exe 图片文件 k 参数(=0.04) Aperture_size(=3)”。(The input of a color image, write your own code to achieve Harris Corner Detection Algorithm: 1. Can not be called directly inside OpenCV some functions associated with the Harris corner detection 2. To only use C/C++, can not be used in other languages 3. GUI only with their own HighGUI, can not use QT or other 4. The platform can be used Windows, Linux, MacOS 5. Display intermediate and final results of the test results, including the largest eigenvalues diagram, the minimum feature value graph , R chart (you can consider color display), picture superimposed on the test results, etc., and these intermediate results are output as an image file 6. Command Format: " xxx.exe picture file k parameters (= 0.04) Aperture_size (= 3 ). " )

使用Tensoflow实现图卷积神经网络模型(Use Tensoflow Implementation Figure convolution neural network model)

利用积分图的方式提取图像hog特征，用于人脸、行人检测。(Using the integral plot to extract the image hog feature, for human face, pedestrian detection.)

对比CPU和GPU加速，pcl::cuda的使用教程，利用随机采样一致(RANSAC)去除地平面等例子。(Compare CPU and GPU acceleration, pcl::cuda tutorial, using random sampling consistency (RANSAC) to remove ground plane and other examples.)

人脸检测：可自动检测人脸，速度还可以吧！(Face Detection : can automatically detect faces and can also speed!)

说明：  高斯混合模型实现图像分割分类，包含中文注释。(Gaussian mixture model implements image segmentation and classification, including Chinese annotation.)

IMM算法，用于机动目标的精确跟踪和定位，该模型集考虑了三种典型子模型:CV,CT,CA. (interacting multiple model (IMM) code for target tracking )

matlab 归一化相关系数，可用于模板匹配(matlab normalized correlation coefficient)