指纹识别程序A

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.)

IMDCT的matlab实现算法,采用递归结构，嵌套循环，作为硬件实现的Gold(IMDCT in matlab platform)

ASIFT算法实现，C++,对有仿射变换的图像匹配更加准确，想比SIFT算子匹配点数多(ASIFT algorithm, C++, affine transformation of the image matching more accurate, want to match more than SIFT operator points)

matlab 图像处理方面的经典书籍，值得初学者仔细认真的学习(matlab image processing aspects of classic books, worthy of serious study carefully beginners)

说明：  包括如何将几百个*.txt的文件读入程序，并通过快速傅立叶变换进行数据处理画出图像。(including how to hundreds*. txt file into the process, and through the fast Fourier transform data processing paint images.)

均值偏移算法，在图象的平滑和分割方面是一种很有用的处理方法(mean deviation algorithm, the image smoothing and segmentation is a very useful approach)

outlook风格的界面例子(Outlook style interface example)

应用opencv进行图像处理，改变基sobel算子操作，有利于开展下面的图像处理(Applying OpenCV to image processing and changing the operation of base Sobel operator is beneficial to the following image processing)

线性反投影算法（Linear Back Projection，简称 LBP）又称累加法，是最早使用的一种简单（ECT图像重建）成像算法。它将通过某点的所有投影射线进行累加，再反向估算出该点的密度值。从成像观点分析，它是不完全的雷登逆变换（完整的雷登逆变换包括微分、希尔伯特变换、反投影和归一化等步骤）。(Linear back projection algorithm (Linear Back Projection, referred LBP), also known as cumulative method, is the first to use a simple (ECT image reconstruction) imaging algorithms. It accumulates all projection rays through a point, then reverse the estimated density value of the point. From the image point of view analysis, it is not exactly the inverse transform Leiden (Leyden complete inverse transformation involving differential Hilbert transform backprojection and normalization steps, etc.).)

从人流统计的实际工程出发,实现了基于计算机视觉的人体运动检测及跟踪系统,采用“差影法”滤掉静止帧,使用自适应的一阶递归滤波及帧差法提取运动区域,并通过数学形态滤波的开运算和闭运算改善运动区域提取效果。实验结果证明本运动跟踪方案处理简单高效 、抗噪能力强,可以完成复杂背景下运动目标的实时性检测与跟踪。(Flow statistics from the actual project, the realization of computer vision-based human motion detection and tracking system, using )