使用OpenCV实现分水岭算法

代码:

#include<cv.h>#include<highgui.h>#include<iostream>using namespace  std;IplImage* marker_mask = 0;IplImage* markers = 0;IplImage* img0 = 0, *img = 0, *img_gray = 0, *wshed = 0;CvPoint prev_pt = {-1,-1};void on_mouse( int event, int x, int y, int flags, void* param )//opencv 会自动给函数传入合适的值{if( !img )return;if( event == CV_EVENT_LBUTTONUP || !(flags & CV_EVENT_FLAG_LBUTTON) )prev_pt = cvPoint(-1,-1);else if( event == CV_EVENT_LBUTTONDOWN )prev_pt = cvPoint(x,y);else if( event == CV_EVENT_MOUSEMOVE && (flags & CV_EVENT_FLAG_LBUTTON) ){CvPoint pt = cvPoint(x,y);if( prev_pt.x < 0 )prev_pt = pt;cvLine( marker_mask, prev_pt, pt, cvScalarAll(255), 5, 8, 0 );//CvScalar 成员：double val[4] RGBA值A=alphacvLine( img, prev_pt, pt, cvScalarAll(255), 5, 8, 0 );prev_pt = pt;cvShowImage( "image", img);}}int main( int argc, char** argv ){char* filename = argc >= 2 ? argv[1] : (char*)"fruits.jpg";CvMemStorage* storage = cvCreateMemStorage(0);CvRNG rng = cvRNG(-1);if( (img0 = cvLoadImage(filename,1)) == 0 )return 0;printf( "Hot keys: \n""\tESC - quit the program\n""\tr - restore the original image\n""\tw or SPACE - run watershed algorithm\n""\t\t(before running it, roughly mark the areas on the image)\n""\t  (before that, roughly outline several markers on the image)\n" );cvNamedWindow( "image", 1 );cvNamedWindow( "watershed transform", 1 );img = cvCloneImage( img0 );img_gray = cvCloneImage( img0 );wshed = cvCloneImage( img0 );marker_mask = cvCreateImage( cvGetSize(img), 8, 1 );markers = cvCreateImage( cvGetSize(img), IPL_DEPTH_32S, 1 );cvCvtColor( img, marker_mask, CV_BGR2GRAY );cvCvtColor( marker_mask, img_gray, CV_GRAY2BGR );//这两句只用将RGB转成3通道的灰度图即R=G=B,用来显示用cvZero( marker_mask );cvZero( wshed );cvShowImage( "image", img );cvShowImage( "watershed transform", wshed );cvSetMouseCallback( "image", on_mouse, 0 );for(;;){int c = cvWaitKey(0);if( (char)c == 27 )break;if( (char)c == 'r' ){cvZero( marker_mask );cvCopy( img0, img );//cvCopy（）也可以这样用，不影响原img0图像，也随时更新cvShowImage( "image", img );}if( (char)c == 'w' || (char)c == ' ' ){CvSeq* contours = 0;CvMat* color_tab = 0;int i, j, comp_count = 0;//下面选将标记的图像取得其轮廓, 将每种轮廓用不同的整数表示//不同的整数使用分水岭算法时，就成为不同的种子点//算法本来就是以各个不同的种子点为中心扩张cvClearMemStorage(storage);cvFindContours( marker_mask, storage, &contours, sizeof(CvContour),CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE );cvZero( markers );for( ; contours != 0; contours = contours->h_next, comp_count++ ){cvDrawContours(markers, contours, cvScalarAll(comp_count+1),cvScalarAll(comp_count+1), -1, -1, 8, cvPoint(0,0) );}//cvShowImage("image",markers);if( comp_count == 0 )continue;color_tab = cvCreateMat( 1, comp_count, CV_8UC3 );//创建随机颜色列表for( i = 0; i < comp_count; i++ )　//不同的整数标记{uchar* ptr = color_tab->data.ptr + i*3;ptr[0] = (uchar)(cvRandInt(&rng)%180 + 50);ptr[1] = (uchar)(cvRandInt(&rng)%180 + 50);ptr[2] = (uchar)(cvRandInt(&rng)%180 + 50);}{double t = (double)cvGetTickCount();cvWatershed( img0, markers );cvSave("img0.xml",markers);t = (double)cvGetTickCount() - t;printf( "exec time = %gms\n", t/(cvGetTickFrequency()*1000.) );}// paint the watershed imagefor( i = 0; i < markers->height; i++ )for( j = 0; j < markers->width; j++ ){int idx = CV_IMAGE_ELEM( markers, int, i, j );//markers的数据类型为IPL_DEPTH_32Suchar* dst = &CV_IMAGE_ELEM( wshed, uchar, i, j*3 );//BGR三个通道的数是一起的,故要j*3if( idx == -1 ) //输出时若为-1，表示各个部分的边界dst[0] = dst[1] = dst[2] = (uchar)255;else if( idx <= 0 || idx > comp_count )  //异常情况dst[0] = dst[1] = dst[2] = (uchar)0; // should not get hereelse //正常情况{uchar* ptr = color_tab->data.ptr + (idx-1)*3;dst[0] = ptr[0]; dst[1] = ptr[1]; dst[2] = ptr[2];}}cvAddWeighted( wshed, 0.5, img_gray, 0.5, 0, wshed );//wshed.x.y=0.5*wshed.x.y+0.5*img_gray+0加权融合图像cvShowImage( "watershed transform", wshed );cvReleaseMat( &color_tab );}}return 1;}

注意

需要使用如下三个库方可:

opencv_core249d.lib

opencv_highgui249d.lib
opencv_imgproc249d.lib