Mag_Color_Snake

在人脸数据库中应用PCA，以及重建误差分析(Applying PCA in human face dataset and doing analysis on reconstruction differences )

这是基于图像处理，用MATLAB编程，对指定的图像进行缺陷检测和边缘提取的程序(This is based on image processing, using MATLAB programming, the images on the specified defect detection and edge extraction procedures)

读取avi视频，并进行帧间差分法运算，检测运动目标(Read the avi video, and make inter-frame difference method for computing, moving target detection)

SSIM是衡量图像质量的另一个标准，比PSNR略好。此为计算图像SSIM的代码(SSIM is another measure of image quality, slightly better than PSNR. The code is to calculate SSIM.)

说明：  用Visual C++实现模糊图像恢复处理程序实例(Using Visual C++ fuzzy image restoration processing examples)

图像分割，双峰法.显示直方图，根据直方图确定阈值，并根据次阈值进行图像的风格(segmation)

1、对观测数据进行中心化，； 2、使它的均值为0，对数据进行白化—>Z； 3、选择需要估计的分量的个数m，设置迭代次数p<-1 4、选择一个初始权矢量（随机的W，使其维数为Z的行向量个数）； 5、利用迭代W(i,p)=mean(z(i,:).*(tanh((temp) *z)))-(mean(1-(tanh((temp)) *z).^2)).*temp(i,1)来学习W （这个公式是用来逼近负熵的） 6、用对称正交法处理下W 7、归一化W(:,p)=W(:,p)/norm(W(:,p)) 8、若W不收敛，返回第5步 9、令p=p+1，若p小于等于m,返回第4步 剩下的应该都能看懂了 基本就是基于负熵最大的快速独立分量分析算法(1, on the center of the observation data, 2, making a mean of 0, the data to whitening-> Z 3, select the number of components to be estimated m, setting the number of iterations p < -1 4, select an initial weight vector (random W, so that the Z dimension of the row vectors of numbers) 5, the use of iteration W (i, p) = mean (z (i, :).* (tanh ((temp) ' * z)))- (mean (1- (tanh ((temp)) ' * z). ^ 2)).* temp (i, 1) to learn W (This formula is used to approximate the negative entropy) 6 with symmetric orthogonal treatments W 7, normalized W (:, p) = W (:, p)/norm (W (:, p)) 8, if W does not converge, return to step 5 9 , so that p = p+1, if p less than or equal m, return to step 4 should be able to read the rest of the basic is based on negative entropy of the largest fast independent component analysis algorithm)

这是本智能图像处理的书教你如何读取BMP图像二值化中值滤波还有灰度变换图像匹配，检索(This is the intelligent image processing book teaches you how to read the BMP image binarization there are gray-scale transformation in the value of the filter image matching, retrieval)

高斯列主元消去法，用来解多元线性方程组，从而解决相关的方程组问题(Principal component Gaussian column elimination method used to solve a multivariate linear equations to solve the equations)

信息检索和自然语言处理中经常会使用这些参数:准确率（Precision）、召回率（Recall）以及综合评价指标（F1-Measure ） (These parameters are often used in information retri and natural language processing (Precision), recall rate (Recall), and comprehensive uation index (F1-Measure). )