bgggussi

产生一个验证码，有四个数字组成，有噪音，椒盐噪声等(failed to translate)

均值方差与协方差 协方差矩阵、特征值与特征向量的提取、PCA原理 人脸识别算法之EigenFace、LBPH 人脸识别应用开发案例(Mean Variance and Covariance Covariance Matrix, Extraction of Eigenvalues and Eigenvectors, PCA Principle EigenFace and LBPH of Face Recognition Algorithms Case Study of Face Recognition Application Development)

说明：  用平方根算法进行矩阵的优化，以便使用卡尔曼滤波获得精确的值(kalman filter and pingfanggen method ，using it can obtain accurate value )

非下采样轮廓波变换，NSCT变换，主要用于图像去噪(Non - down sampling contourlet transform and NSCT transform are mainly used for image denoising.)

利用matlab的DCT2函数，对图像做变换并压缩。并用8*8对图像分块，对每一块计算均方值作为阈值。(DCT2 use the matlab function, and transform the image so compressed. And 8* 8 image block, a calculation of each mean square value as a threshold.)

主成分分析 （ Principal Component Analysis ， PCA ）或者主元分析。是一种掌握事物主要矛盾的统计分析方法，它可以从多元事物中解析出主要影响因素，揭示事物的本质，简化复杂的问题。计算主成分的目的是将高维数据投影到较低维空间。给定 n 个变量的 m 个观察值，形成一个 n ′ m 的数据矩阵， n 通常比较大。对于一个由多个变量描述的复杂事物，人们难以认识，那么是否可以抓住事物主要方面进行重点分析呢？如果事物的主要方面刚好体现在几个主要变量上，我们只需要将这几个变量分离出来，进行详细分析。但是，在一般情况下，并不能直接找出这样的关键变量。这时我们可以用原有变量的线性组合来表示事物的主要方面， PCA 就是这样一种分析方法。(Principal component analysis (Principal Component Analysis, PCA) or PCA. Is a statistical method to grasp the principal contradiction of things, it can be resolved diverse things out the main factors, revealing the essence of things, simplifying complex problems. The purpose of calculating the main component of high-dimensional data is projected to a lower dimensional space. Given n variables of m observations, forming an n ' m of the data matrix, n is usually large. For a complex matters described by several variables, it is difficult to know, so if you can grab something to focus on key aspects of analysis? If the main aspects of things just reflected on several key variables, we only need to separate out these few variables, for detailed analysis. However, in general, does not directly identify this critical variables. Then we can represent the major aspects of things with a linear combination of the original variables, PCA is one such analysis.)

This is an example of radar system simulation implemented in SIMULINK on MATLAB. The user can set the target distance, direction and other parameters by himself.

基于SVM与人工神经网络的车牌识别算法，使用了OpenCV的图像处理函数，在VS2013 + OpenCV 2.4.9平台上实现(SVM algorithm based on license plate recognition and artificial neural network, using OpenCV image processing function, implemented on VS2013+ OpenCV 2.4.9 platform)

基于灰度共生矩阵的纹理特征提取，输出为图像四个方向共十六个特征值(Gray-level co-occurrence matrix based texture feature extraction, the output image in four directions for a total of 16 eigenvalues)

质心定位算法，代码在matlab2013b下调试通过，希望对下载君有所帮助。(Centroid positioning algorithm, the code in matlab2013b debugging through, and I hope to download Jun help.)