计算机视觉
图像处理

OpenCV 实现分水岭算法

种子点的标记没有太搞懂,这个算法的速度还是很快的

// watershed_test20140801.cpp : 定义控制台应用程序的入口点。
//

#include "stdafx.h"

//
// ch9_watershed image
//   This is an exact copy of the watershed.cpp demo in the Opencv ../samples/c directory
//
// Think about using a morphologically eroded forground and background segmented image as the template
// for the watershed algorithm to segment objects by color and edges for collecting 
//
/* *************** License:**************************
   Oct. 3, 2008
   Right to use this code in any way you want without warrenty, support or any guarentee of it working.

   BOOK: It would be nice if you cited it:
   Learning OpenCV: Computer Vision with the OpenCV Library
     by Gary Bradski and Adrian Kaehler
     Published by O'Reilly Media, October 3, 2008
 
   AVAILABLE AT: 
     http://www.amazon.com/Learning-OpenCV-Computer-Vision-Library/dp/0596516134
     Or: http://oreilly.com/catalog/9780596516130/
     ISBN-10: 0596516134 or: ISBN-13: 978-0596516130    

   OTHER OPENCV SITES:
   * The source code is on sourceforge at:
     http://sourceforge.net/projects/opencvlibrary/
   * The OpenCV wiki page (As of Oct 1, 2008 this is down for changing over servers, but should come back):
     http://opencvlibrary.sourceforge.net/
   * An active user group is at:
     http://tech.groups.yahoo.com/group/OpenCV/
   * The minutes of weekly OpenCV development meetings are at:
     http://pr.willowgarage.com/wiki/OpenCV
   ************************************************** */

#include "cv.h"
#include "highgui.h"
#include 
#include 
#include 
using namespace std;
using namespace cv;


#pragma comment(lib,"opencv_core2410d.lib")      
#pragma comment(lib,"opencv_highgui2410d.lib")      
#pragma comment(lib,"opencv_imgproc2410d.lib")  

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 )
{
    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 );
        cvLine( img, prev_pt, pt, cvScalarAll(255), 5, 8, 0 );
        prev_pt = pt;
        cvShowImage( "image", img );
    }
}


int main( int argc, char** argv )
{
    cout<<"input image name:  "<<endl; string file; cin>>file;


	char* filename = (char *)file.c_str();

    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 ENTER - 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 );

    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 );
            cvShowImage( "image", img );
        }

        if( (char)c == 'w' || (char)c == '\n' )
        {
            CvMemStorage* storage = cvCreateMemStorage(0);
            CvSeq* contours = 0;
            CvMat* color_tab;
            int i, j, comp_count = 0;
            //cvSaveImage( "wshed_mask.png", marker_mask );
            //marker_mask = cvLoadImage( "wshed_mask.png", 0 );
            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) );
            }

            color_tab = cvCreateMat( 1, comp_count, CV_8UC3 );
            for( i = 0; i < comp_count; i++ ) { 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 );
            t = (double)cvGetTickCount() - t;
            printf( "exec time = %gms\n", t/(cvGetTickFrequency()*1000.) );
            }

            // paint the watershed image
            for( i = 0; i < markers->height; i++ )
                for( j = 0; j < markers->width; j++ )
                {
                    int idx = CV_IMAGE_ELEM( markers, int, i, j );
                    uchar* dst = &CV_IMAGE_ELEM( wshed, uchar, i, j*3 );
                    if( idx == -1 )
                        dst[0] = dst[1] = dst[2] = (uchar)255;
                    else if( idx <= 0 || idx > comp_count )
                        dst[0] = dst[1] = dst[2] = (uchar)0; // should not get here
                    else
                    {
                        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 );
            cvShowImage( "watershed transform", wshed );
            cvReleaseMemStorage( &storage );
            cvReleaseMat( &color_tab );
        }
    }

    return 1;
}


实现效果:

转载注明来源:CV视觉网 » OpenCV 实现分水岭算法

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