opencv实现c++的otsu自适应阈值分割的算法描述

1、otsu 算法选择使类间方差最大的灰度值为阈值，具有很好的效果算法具体描述见 otsu 论文，或冈萨雷斯有名的数字图像处理那本书这里给出程序流程：1、计算直方图并归一化 histogram 2、计算图像灰度均值 avgvalue.3、计算直方图的零阶 wi和一级矩 ui4、计算并找到最大的类间方差（between-class variance） variancei=(avgvalue*wi-ui)*(avgvalue*wi-ui)/(wi*(1-wi) 对应此最大方差的灰度值即为要找的阈值5、用找到的阈值二值化图像我在代码中做了一些优化，所以算法描述的某些地方跟程序并不全都otsu 代码，先找

2、阈值，继而二值化/ implementation of otsu algorithm/ author: onezeros()/ reference: rafael c. gonzalez. digital image processing using matlab void cvthresholdotsu(iplimage* src, iplimage* dst)int height=src->height; int width=src->width;/histogramfloat histogram256= 0; for(int i=0; i<height; i+)unsi

3、gned char* p=(unsigned char*)src->imagedata+src->widthstep*i; for(int j=0; j<width; j+)histogram*p+;/normalize histogram int size=height*width; for(int i=0; i<256; i+)histogrami=histogrami/size;/average pixel value float avgvalue=0;for(int i=0; i<256; i+)avgvalue+=i*histogrami;int thr

4、eshold;float maxvariance=0; float w=0,u=0;for(int i=0; i<256; i+)w+=histogrami; u+=i*histogrami;float t=avgvalue*w-u;float variance=t*t/(w*(1-w); if(variance>maxvariance)maxvariance=variance; threshold=i;cvthreshold(src,dst,threshold,255,cv_thresh_binary);更多状况下我们并不需要对每一帧都是用 otsu 查找阈值，于是可以先找到阈值

5、， 然后用找到的阈值处理后面的图像。下面这个函数重载了上面的，返回值就是阈值。只做了一点转变/ implementation of otsu algorithm/ author: onezeros()/ reference: rafael c. gonzalez. digital image processing using matlab int cvthresholdotsu(iplimage* src)int height=src->height; int width=src->width;/histogramfloat histogram256= 0; for(int i=0

6、; i<height; i+)unsigned char* p=(unsigned char*)src->imagedata+src->widthstep*i; for(int j=0; j<width; j+)histogram*p+;/normalize histogram int size=height*width; for(int i=0; i<256; i+)histogrami=histogrami/size;/average pixel value float avgvalue=0; for(int i=0; i<256; i+)avgvalu

7、e+=i*histogrami;int threshold;float maxvariance=0; float w=0,u=0;for(int i=0; i<256; i+)w+=histogrami; u+=i*histogrami;float t=avgvalue*w-u;float variance=t*t/(w*(1-w); if(variance>maxvariance)maxvariance=variance;threshold=i;return threshold;我在手的自动检测中使用这个方法，效果很好。下面是使用上述两个函数的简洁的主程序，可以试运行一下，假如处

8、理视频，要保证第一帧时，手要在图像中。#include <cv.h> #include <cxcore.h> #include <highgui.h>#pragma comment(lib,“cv210d.lib“) #pragma comment(lib,“cxcore210d.lib“) #pragma comment(lib,“highgui210d.lib“)#include <iostream> using namespace std;int main(int argc, char* argv)#ifdef video /video p

9、rocesscvcapture* capture=cvcreatecameracapture(-1); if (!capture)cout<<“failed to open camera“<<endl; exit(0);int threshold=-1;iplimage* img;while (img=cvqueryframe(capture)cvshowimage(“video“,img);cvcvtcolor(img,img,cv_rgb2ycrcb);iplimage* imgcb=cvcreateimage(cvgetsize(img),8,1); cvspli

10、t(img,null,null,imgcb,null);if (threshold<0)threshold=cvthresholdotsu(imgcb);/cvthresholdotsu(imgcb,imgcb); cvthreshold(imgcb,imgcb,threshold,255,cv_thresh_binary); cverode(imgcb,imgcb);cvdilate(imgcb,imgcb);cvshowimage(“object“,imgcb); cvreleaseimage(&imgcb);if (cvwaitkey(3)=27) /escbreak;cv

11、releasecapture(&capture);#else /single image processconst char* filename=(argc>=2?argv1:“cr.jpg“);iplimage* img=cvloadimage(filename,cv_load_image_grayscale);cvthresholdotsu(img,img); cvshowimage( “src“, img ); char buf256;sprintf_s(buf,256,“%s.otsu.jpg“,filename); cvsaveimage(buf,img);cverod

12、e(img,img); cvdilate(img,img); cvshowimage( “dst“, img );sprintf_s(buf,256,“%cessed.jpg“,filename); cvsaveimage(buf,img);cvwaitkey(0); #endifreturn 0;#include <cv.h> #include <cxcore.h> #include <highgui.h>#pragma comment(lib,“cv210d.lib“) #pragma comment(lib,“cxcore210d.

13、lib“) #pragma comment(lib,“highgui210d.lib“) #include <iostream>using namespace std;int main(int argc, char* argv)#ifdef video /video processcvcapture* capture=cvcreatecameracapture(-1); if (!capture)cout<<“failed to open camera“<<endl; exit(0);int threshold=-1;iplimage* img;while

14、(img=cvqueryframe(capture)cvshowimage(“video“,img); cvcvtcolor(img,img,cv_rgb2ycrcb);iplimage* imgcb=cvcreateimage(cvgetsize(img),8,1); cvsplit(img,null,null,imgcb,null);if (threshold<0)threshold=cvthresholdotsu(imgcb);/cvthresholdotsu(imgcb,imgcb); cvthreshold(imgcb,imgcb,threshold,255,cv_thresh

15、_binary); cverode(imgcb,imgcb);cvdilate(imgcb,imgcb);cvshowimage(“object“,imgcb); cvreleaseimage(&imgcb);if (cvwaitkey(3)=27) /escbreak;cvreleasecapture(&capture);#else /single image processconst char* filename=(argc>=2?argv1:“cr.jpg“);iplimage* img=cvloadimage(filename,cv_load_image_grayscale); cvthresholdotsu(img,img);cvshowimage( “src“, img ); ch