Watershed

做分水嶺圖像分割

C++:?void?watershed(InputArray?image, InputOutputArray?markers)

c語言形式：void cvWatershed( const CvArr* image, CvArr* markers ); image

輸入8比特3通道圖像。

markers

輸入或輸出的32比特單通道標記圖像。

markers即是輸入矩陣也是輸出矩陣，大小與image大小相同。使用該函數的時候，用戶在markers矩陣中必須粗略指定兩種以上區域，該區域為1個點以上的連通點集，并用不同的正整數(1，2，3…)標記

函數cvWatershed實現在[Meyer92]描述的變量分水嶺，基于非參數標記的分割算法中的一種。在把圖像傳給函數之前，用戶需要用正指標大致勾畫出圖像標記的感興趣區域。比如，每一個區域都表示成一個或者多個像素值1，2，3的互聯部分。這些部分將作為將來圖像區域的種子。標記中所有的其他像素，他們和勾畫出的區域關系不明并且應由算法定義，應當被置0。這個函數的輸出則是標記區域所有像素被置為某個種子部分的值，或者在區域邊界則置-1。

注：每兩個相鄰區域也不是必須有一個分水嶺邊界（-1像素）分開，例如在初始標記圖像里有這樣相切的部分。opencv例程文件夾里面有函數的視覺效果演示和用戶例程

#include<cv.h> #include<highgui.h> #include<iostream>#pragma comment(lib, "cv.lib") #pragma comment(lib, "cxcore.lib") #pragma comment(lib, "highgui.lib")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 會自動給函數傳入合適的值 {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 成員：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*)"test.png";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 );//這兩句只用將RGB轉成3通道的灰度圖即R=G=B,用來顯示用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（）也可以這樣用，不影響原img0圖像，也隨時更新cvShowImage( "image", img );}if( (char)c == 'w' || (char)c == ' ' ){CvSeq* contours = 0;CvMat* color_tab = 0;int i, j, comp_count = 0;//下面選將標記的圖像取得其輪廓, 將每種輪廓用不同的整數表示//不同的整數使用分水嶺算法時，就成為不同的種子點//算法本來就是以各個不同的種子點為中心擴張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 );//創建隨機顏色列表for( i = 0; i < comp_count; i++ ) //不同的整數標記{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的數據類型為IPL_DEPTH_32Suchar* dst = &CV_IMAGE_ELEM( wshed, uchar, i, j*3 );//BGR三個通道的數是一起的,故要j*3if( idx == -1 ) //輸出時若為-1，表示各個部分的邊界dst[0] = dst[1] = dst[2] = (uchar)255;else if( idx <= 0 || idx > comp_count ) //異常情況dst[0] = dst[1] = dst[2] = (uchar)0; // should not get hereelse //正常情況{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加權融合圖像cvShowImage( "watershed transform", wshed );cvReleaseMat( &color_tab );}}return 1; }

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