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，或冈萨雷斯著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histogram2、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一致otsu代码，先找阈值，继而二值化/ i

2、mplementation of otsu algorithm/ author: onezeros()/ reference: Rafael C. Gonzalez. Digital Image Processing Using MATLABvoid cvThresholdOtsu(IplImage* src, IplImage* dst) int height=src-height; int width=src-width; /histogram float histogram256= 0; for(int i=0; iimageData+src-widthStep*i; f

3、or(int j=0; jwidth; j+) histogram*p+; /normalize histogram int size=height*width; for(int i=0; i256; i+) histogrami=histogrami/size; /average pixel value float avgValue=0; for(int i=0; i256; i+) avgValue+=i*histogrami; int threshold; float maxVariance=0; float w=0,u=0; for(int i=0; imaxVariance) max

4、Variance=variance; threshold=i; cvThreshold(src,dst,threshold,255,CV_THRESH_BINARY);更多情况下我们并不需要对每一帧都是用otsu寻找阈值，于是可以先找到阈值，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。只做了一点改变/ implementation of otsu algorithm/ author: onezeros()/ reference: Rafael C. Gonzalez. Digital Image Processing Using MATLABint

5、 cvThresholdOtsu(IplImage* src) int height=src-height; int width=src-width; /histogram float histogram256= 0; for(int i=0; iimageData+src-widthStep*i; for(int j=0; jwidth; j+) histogram*p+; /normalize histogram int size=height*width; for(int i=0; i256; i+) histogrami=histogrami/size; /average pixel

6、value float avgValue=0; for(int i=0; i256; i+) avgValue+=i*histogrami; int threshold; float maxVariance=0; float w=0,u=0; for(int i=0; imaxVariance) 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单的主程序，可以试运行一下，如果处理视频，要保证第一帧时，手要在图像中。#include #include #include #p

7、ragma comment(lib,cv210d.lib)#pragma comment(lib,cxcore210d.lib)#pragma comment(lib,highgui210d.lib)#include using namespace std;int main(int argc, char* argv)#ifdef VIDEO /video process CvCapture* capture=cvCreateCameraCapture(-1); if (!capture) coutfailed to open cameraendl; exit(0); int threshold

8、=-1; IplImage* img; while (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=2?argv1:cr.jpg); IplImage* img=cvLoadImage(filename,CV_LOAD_IMAGE_GRAYSCALE); cvThreshold

9、Otsu(img,img); cvShowImage( src, img ); char buf256; sprintf_s(buf,256,%s.otsu.jpg,filename); cvSaveImage(buf,img); cvErode(img,img); cvDilate(img,img); cvShowImage( dst, img ); sprintf_s(buf,256,%cessed.jpg,filename); cvSaveImage(buf,img); cvWaitKey(0);#endif return 0;#include #include #i

10、nclude #pragma comment(lib,cv210d.lib)#pragma comment(lib,cxcore210d.lib)#pragma comment(lib,highgui210d.lib)#include using namespace std;int main(int argc, char* argv)#ifdef VIDEO /video process CvCapture* capture=cvCreateCameraCapture(-1); if (!capture) coutfailed to open cameraendl; exit(0); int

11、threshold=-1; IplImage* img; while (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=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); cvSaveI