Face-Eye-Detection

基于半色调图像的数据隐藏即加数字水印，针对半色调图像，所以使用的是DHSPT算法，算法较容易理解，简单，嵌入效果相对较好(Hidden based on the halftone image data plus digital watermark for halftone images, use DHSPT algorithm, the algorithm is easy to understand, simple, embedded effect is relatively good)

说明：  本算法是matlab代码，通过icp点云匹配算法实现三维点云的配准(The algorithm is matlab code, and the registration of three-dimensional point cloud is realized by ICP point cloud matching algorithm.)

基于特征匹配的英文印刷字符识别，里面有实验所需的图片和具体的代码(English printed character recognition based on feature matching, which contains the pictures and specific code needed for the experiment)

利用梯度插值算法实现图像的去马赛克，图像质量大大提高(Using gradient interpolation algorithm to achieve image mosaic, image quality is greatly improved)

对ecg信号进行预处理，并检测ecg的r波，并进行特征提取，并在图中进行标注(On ecg signal preprocessing and detection of r ecg wave, and feature extraction, and marked on the drawing)

利用V4L2协议进行图像处理的编程框架结构(The utilization the V4L2 protocol for image processing programming framework structure)

自己毕业设计做的改进的基于某vc视频处理框架代码的重心多目标跟踪代码(The center of gravity of a vc video processing framework code-based target tracking code own graduation design improvements do)

1．用Matlab产生正弦波,矩形波,以及白噪声信号，并显示各自时域波形图 2．进行FFT变换，显示各自频谱图，其中采样率，频率、数据长度自选 3．做出上述三种信号的均方根图谱,功率图谱,以及对数均方根图谱 4．用IFFT傅立叶反变换恢复信号，并显示恢复的正弦信号时域波形图( 1. Using Matlab generated sine wave, square wave, and the white noise signal, and displays the respective time-domain waveform 2. The FFT transform, showing each spectrum, where the sampling rate, frequency, data length choice 3. Rms signal to make the three maps, power spectra, as well as the number of rms spectra 4. With the inverse Fourier transform IFFT restore the signal and displays the recovered time-domain waveform sinusoidal signal)

很好的流形学习，处理高维数据，降维操作，里面含有LLE，PCA，Dijstra,Iosmap等等(Good manifold learning, processing high dimensional data, dimensionality reduction operations, including LLE, PCA, Dijstra, Iosmap, etc.)

TV正则化去卷积the Iteratively Reweighted Norm algorithm for solving the generalized TV functional, which includes the L2-TV and and L1-TV problems(An Iteratively Reweighted Norm Algorithm for Minimization of Total Variation Functionals)