【OpenCV学习】Kmean均值聚类对图片进行减色处理
作者:gnuhpc
出处:http://www.cnblogs.com/gnuhpc/
#include <cv.h> #include <highgui.h> #include <iostream> #define MAX_CLUSTERS (8) using namespace std; int main( int argc, char **argv) { IplImage *imgA = cvLoadImage( "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++) { 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]; 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]; 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]; } cvNamedWindow("window2",CV_WINDOW_AUTOSIZE); cvShowImage("window2",imgA); cvWaitKey(0); cvReleaseImage( &imgA ); cvDestroyWindow("window"); cvDestroyWindow("window2"); return 0; }