-
twain_vb
twain_vb源码,图像设备与计算机软件接口程序(twain_vb)
- 2010-05-13 13:43:52下载
- 积分：1
-
facereganization
人脸识别的实例，其中含有项目题目，解决方案以及实现程序和工具箱(Examples of face recognition, which contains the project topic, the solution as well as the implementation procedures and toolbox)
- 2009-02-23 20:15:23下载
- 积分：1
-
weipingmian
将一个灰度图像分解成为八个位平面 然后再合并起来 可以对每一个位平面实现不同的处理(A gray level image is decomposed into eight bit plane and then combined to each bit plane to achieve different treatment)
- 2013-12-16 21:02:05下载
- 积分：1
-
GenerateOneDimensionalGrating
使用Matlab生成一维光栅条纹，可用于结构光三维重建。(Matlab Generate One Dimensional Grating)
- 2018-08-06 17:57:35下载
- 积分：1
-
bridge
压缩包里面为2个程序，一个是悬链线模拟索的程序，一个是抛物线法模拟的索的程序(Compressed inside of two programs, one cable catenary simulation program, a parabolic law analog cable programs)
- 2021-06-08 15:30:07下载
- 积分：1
-
daqituanliu
对灰阶图像进行大气湍流滤波，使图像达到需要达到的效果(The atmospheric turbulence filtering is applied to the gray scale image to achieve the desired effect)
- 2019-05-19 14:24:00下载
- 积分：1
-
sowdy
说明： Legendary server controller for game enthusiasts to study, can
- 2019-04-21 04:21:19下载
- 积分：1
-
nsct_toolbox
非下采样contourlet变换用于图像降噪，多尺度几何分析的应用。
(Contourlet transform non-down-sampling for image noise reduction, multi-scale analysis of the application of geometry.)
- 2009-04-12 18:08:10下载
- 积分：1
-
OSTU
这是一个阈值分割算法，主要用来对图像进行二值化，提取感兴趣区域~~(This is a threshold segmentation algorithm, mainly used for binary images, extract region of interest ~ ~
)
- 2009-05-21 15:00:16下载
- 积分：1
-
PCA
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.)
- 2021-01-28 21:48:40下载
- 积分：1
