心动呀

说明：  一个很有用的Markov Decision Process matlab程序(a very useful Markov Decision Process procedures Matlab)

基于背景减除的单目标跟踪方法在Matlab中的实现，包含测试用avi文件(Background subtraction based on a single-target tracking method in Matlab, implementation, including test avi file)

数学形态学操作 数学形态学的基本运算 结构元素矩阵 膨胀运算 腐蚀运算 膨胀与腐蚀的对偶关系 开运算和闭运算 击中与击不中 形态学的基本应用 边缘提取 二值图像面积提取 二值图像的欧拉数 查找表操作 灰度形态学 (Mathematical morphology operations basic operations of mathematical morphology dilation operator structure element matrix erosion operator expansion and corrosion of the relationship between dual opening operation and closing operation with the strike did not hit in the basic application of morphological edge detection in binary image extracted area of binary image Euler number look-up table operation of gray-scale morphology)

PCB板检测的大概流程如下：首先存储一个标准PCB板图像作为参考标准，然后将待检测的PCB板图像进行处理，比较与标准PCB图像的差异。根据差异的情况来判断缺陷类型。(The approximate process of PCB board detection is as follows: first, a standard PCB board image is stored as a reference standard, and then the PCB board image to be detected is processed to compare the difference between the standard PCB image and the standard image. The type of defect is judged according to the difference.)

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.)

一种基于Arnold变换的图像加密技术，并且用Matlab的GUI界面设计一个用Arnold算法进行图像加密的程序。该程序实现了Arnold图像加密算法的加、解密功能，以及一些基本的图像处理功能。(A kind of image encryption technology based on Arnold transform, and use Matlab GUI interface to design a Arnold encryption algorithm. This program implements the encryption and decryption function of Arnold image encryption algorithm and some basic image processing functions.)

这是一本关于图形学实验的指导书里面有对图形学的具体讲解(tuxingxue)

这是一个用C实现7-bit的编码和解码的算法 非常有效 经过本人验证的,可用()

Harr特征的几种在matlab环境下的实现(Implementation of several Harr features in Matlab environment)

介绍了一种圆检测的方法，该方法，基于霍夫变换，并根据圆几何特征可以快速准确的提取出圆中心坐标(Introduction of a circle detection method, based on the Hough transform, and in accordance with the characteristics of circular geometry can be extracted quickly and accurately the circle center coordinates)