cs

本代码主要是基于HSV的阴影检测及消除，分别提取前景及背景图像，进行色彩空间转换。HSV空间类似人类感觉色彩的方式，可以更加准确地识别阴影，并保持在计算上简单。(This code is mainly based on the HSV shadow detection and elimination, extract the foreground and the background image, respectively, for color space conversion. HSV space is similar to the ways the human feel color, can more accurately identify the shadow, and keep it simple in calculation. )

对图像进行小波分解,可以调整层数,效率较高,精确度较高(The image wavelet decomposition, you can adjust the number of layers, higher efficiency, higher precision)

高斯平滑滤波实例，高斯滤波实质上是一种信号的滤波器，其用途是信号的平滑处理，我们知道数字图像用于后期应用，其噪声是最大的问题，，由于误差会累计传递等原因，很多图像处理教材会在很早的时候介绍Gauss滤波器，用于得到信噪比SNR较高的图像（反应真实信号）。 (Instance of the Gaussian smoothing filter, Gaussian filter is essentially a signal filter, its purpose is to smooth processing of the signal, we know that the digital image for the late application, the noise is the biggest problem, the error accumulated transfer reason, a lot of image processing textbooks will be introduced at an early Gauss filter for higher SNR of the image (real response signal).)

读取图像，转化为二值，去除毛刺噪点像素，去除孤立的前景像素，膨胀，对颗粒进行计数(particle count，)

rgb to HSV，很有用，调试成功，可以应用(rgb to HSV，#include "stdafx.h" #include <iostream.h> void main(float R, float G, float B, float& H, float& S, float&V) { // r,g,b values are from 0 to 1 // h = [0,360], s = [0,1], v = [0,1] // if s == 0, then h =-1 (undefined) float min, max, delta,tmp tmp = R>G?G:R min = tmp>B?B:tmp tmp = R>G?R:G max = tmp>B?tmp:B V = max // v delta = max- min if( max != 0 ) S = delta/max // s else { // r = g = b = 0 // s = 0, v is undefined S = 0 H = 0 return } if (delta == 0){ H = 0 return } else if(R == max){ if (G >= B) H = (G- B)/delta // between yellow & magenta else H = (G- B)/delta+ 6 } else if( G == max ) H = 2+ ( B- R )/delta // between cyan & yellow else if (B == ma)

自己编写fft2和ifft2程序并进行快速傅里叶变换试验(fft2 and ifft2)

随机中点位移法matlab程序代码，生成三维山地模型(Random Midpoint Displacement Method for Mountains Generation)

使用高斯消去法的AVO参数反演程序，可以检索模型层数，十分方便实用。(Using the Gauss elimination of the AVO parameter inversion procedure, you can retrieve the model layer, very convenient and practical.)

能完成钢筋数数，图像分割，直线检测，边缘检测，很好用。(Can finish the reinforcing bar counting, image segmentation, straight line detection, edge detection and works well.)

对数字图像的处理、灰度化等，对数字图像进行基本的操作与处理(Basic digital image manipulation and processing of digital image processing, gray,)