OpenCV 实现分水岭算法

时间:2022-10-27 01:19:45

种子点的标记没有太搞懂,这个算法的速度还是很快的

OpenCV 实现分水岭算法

// 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 <stdio.h>
#include <stdlib.h>
#include <iostream>
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:

OpenCV 实现分水岭算法