资源列表
抓取屏幕
- 用VB做的一个小程序，可以抓取当前屏幕。-VB do a small program will be able to capture the current screen.
hough transform
- perform the Hough Transform of a square binary image. Significantly faster than version 1.
houghcircle
- hough变换是检测直线＆圆的很高的工具，这里是用hough变换检测圆的程序。-Hough transform to detect linear & round of high tool used here is a round Hough Transform detection procedures.
PWL for 1D
- 1D signal:Identification of PieceWise Linear by multiple regression Detection of homogeneous zone using entropie Projection in the Hough space (1D)
pollifill
- 计算机图形学初级学者使用（教科书画法）多边形转换扫描填充算法 程序-Computer graphics beginner use (textbook method) the algorithm to draw polygon by transform ,fill and scan.
BCB_ImageProcess
- 一个利用bcb写成的影像处理程序包含(灰阶.二值化.低通.边缘.侦测旋转.侵蚀.膨胀.透明)提供初学者便于bcb上手- The image disposal procedure which wrote using bcb contains (the gray scale Two values Low pass Edge Detects revolves Corrosion Inflation Transparent) provides the beginner to be ad
LEDA3.0_src2
- 这是著名的计算几何软件leda 3.0 的源码。- This is the famous computation geometry software leda 3.0 sources codes.
在VisualC 中不依赖MATLAB环境调用其函数的方法
- 这是一个关于在VisualC中不依赖MATLAB环境调用其函数的方法,只使用VC的编程环境就能实现- This is about does not rely on the MATLAB environment in VisualC to transfer its function the method, only uses VC the programming environment to be able to realize
VC与matlab混合编程实现图像处理
- 这是一个VC和matlab混合编程在图像处理中的应用的例子,主要是两种编程语言的互相调用- This is VC and the matlab mix programming in the picture processing application example, mainly is two kind of programming languages mutually transfers
jpeg2k标准
- 这是一个关于jpeg2标准的英文原版说明,里面详细介绍了jpeg2的算法,对大家很有帮助- This is explained about the jpeg2 standard English first edition that, inside in detail introduced the jpeg2 algorithm, has very much to everybody helps
图像去躁之邻域算法
- 本程序用来实现数字图像的消除噪声，采用邻域加权求平均的算法，在原来基础上作了一点小小的优化-the procedures used to achieve the elimination of digital image noise, using Neighborhood weighted average for the algorithm, based on the original made one small Optimization
zt
- 图像高斯滤波,再边缘检测中,首先要用到高斯滤波-images Gaussian filtering, edge detection again, the first use of the Gaussian filter! !