学习OpenCV——Kmeans2算法并验证颜色种类（CvMat*&IplImage*指针的用法）

#include <cv.h>
#include <highgui.h>
#include <iostream>


#define MAX_CLUSTERS (8)

using namespace std;

int main( int argc, char **argv)
{
IplImage *imgA = cvLoadImage( "D:/1.jpg", CV_LOAD_IMAGE_ANYDEPTH | CV_LOAD_IMAGE_ANYCOLOR);
if(imgA ==NULL)
{
cout<<"Can't Load Image ." << endl;
exit(0);
}

cvNamedWindow("window",CV_WINDOW_AUTOSIZE);
cvShowImage("window",imgA);//加载原图

unsigned long int size;
size = imgA->width * imgA->height;//取得图片大小

CvMat *clusters;//分类后的矩阵
clusters = cvCreateMat (size, 1, CV_32SC1);//32位1通道的矩阵
CvMat *points;//分类前的样例浮点矩阵
points = cvCreateMat (size, 1, CV_32FC3); //32位3通道的矩阵

unsigned long int i; 
for (i = 0; i < size; i++) 
{
//CvMat *point的访问方式->data.*，载入图像的访问方式->imagedata[],默认都是uchar类型，转换成float型 ☆☆☆☆☆☆☆☆☆☆☆☆☆
points->data.fl[i*3] = (unsigned char) imgA->imageData[i*3];
points->data.fl[i*3 + 1] = (unsigned char) imgA->imageData[i*3 + 1];
points->data.fl[i*3 + 2] = (unsigned char) imgA->imageData[i*3 + 2]; 
} //得到三通道图像的数据
//////////////////////////////////////////////////////////////////////////////
cvKMeans2 (points, MAX_CLUSTERS, clusters,
cvTermCriteria (CV_TERMCRIT_EPS + CV_TERMCRIT_ITER, 10, 1.0));
//拆分为8类聚合，最大迭代次数是10，精度是1.0

CvMat *color = cvCreateMat (MAX_CLUSTERS, 1, CV_32FC3);//8行1列的三通道浮点矩阵
CvMat *count = cvCreateMat (MAX_CLUSTERS, 1, CV_32SC1);//8行1列的单通道整数矩阵，用作计数
cvSetZero (color);
cvSetZero (count);

for (i = 0; i < size; i++)
{
int idx = clusters->data.i[i];
int j = ++count->data.i[idx];
//CvMat *color的访问方式 ☆☆☆☆☆☆☆☆☆☆☆☆☆
color->data.fl[idx * 3 ] = color->data.fl[idx * 3 ] * (j - 1) / j + points->data.fl[i * 3 ] / j;
color->data.fl[idx * 3 + 1] = color->data.fl[idx * 3 + 1] * (j - 1) / j + points->data.fl[i * 3 + 1] / j;
color->data.fl[idx * 3 + 2] = color->data.fl[idx * 3 + 2] * (j - 1) / j + points->data.fl[i * 3 + 2] / j;
}

//把处理过的数据打回imgA
for (i = 0; i < size; i++)
{
int idx = clusters->data.i[i];
//IplImage的访问方式->imageData☆☆☆☆☆☆☆☆☆☆☆☆☆

imgA->imageData[i * 3 ] = (char) color->data.fl[idx * 3 ];
imgA->imageData[i * 3 + 1] = (char) color->data.fl[idx * 3 + 1];
imgA->imageData[i * 3 + 2] = (char) color->data.fl[idx * 3 + 2];
}
IplImage* imgB=cvCreateImage(cvGetSize(imgA),8,1);
cvCvtColor(imgA,imgB,CV_RGB2GRAY);
map<int,int>ColorNum;
for (i = 0; i < size; i++)
{
	ColorNum[imgB->imageData[i]]++;
}
cout<<"ColorNum: "<<ColorNum.size()<<endl;

cvNamedWindow("window2",CV_WINDOW_AUTOSIZE);

cvShowImage("window2",imgA);

cvWaitKey(0);

cvReleaseImage( &imgA );

cvDestroyWindow("window");
cvDestroyWindow("window2");
return 0;
}

原图颜色减少到8种，视觉效果还可以。