提取輪廓在OpenCV里有一個(gè)函數(shù)?cvFindContours：

int cvFindContours( CvArr* image, CvMemStorage* storage, CvSeq** first_contour,int header_size=sizeof(CvContour),int mode=CV_RETR_LIST,int method=CV_CHAIN_APPROX_SIMPLE, CvPoint offset=cvPoint(0,0) );這個(gè)函數(shù)用起來很方便，但是隨著你使用的深入，你會(huì)發(fā)現(xiàn)有一些迷惑在這里。比如當(dāng)你提取輪廓時(shí)只需要最外圍的一個(gè)輪廓，但是你會(huì)發(fā)現(xiàn)當(dāng)輪廓畫出來時(shí)是好幾個(gè)；當(dāng)你需要找一個(gè)最大輪廓時(shí)卻發(fā)現(xiàn)找出來的卻根本就不是你想要的那個(gè)。帶著這樣問題我們再來仔細(xì)看看cvFindContours這個(gè)函數(shù)。下邊的是一位仁兄寫的測試程序和測試圖片，說明提取輪廓的兩種方法及繪制輪廓中最大等級分析的問題，非常感謝他的分享，原文戳這里：/************************************************************************/??? /* 提取輪廓兩種方法對比及繪制輪廓'最大等級'分析???????????????????????? */??? /************************************************************************/??? #include "stdafx.h"??? #include "cv.h"??? #include "highgui.h"??? ??? int main()??? {??? ??? IplImage* img = cvLoadImage("lena.jpg", CV_LOAD_IMAGE_GRAYSCALE);??? ??? IplImage* img_temp = cvCreateImage(cvGetSize(img), 8, 1);??? ??? cvThreshold(img, img, 128, 255, CV_THRESH_BINARY);??? ??? CvMemStorage* mem_storage = cvCreateMemStorage(0);??? ??? CvSeq *first_contour = NULL, *c = NULL;??? ??? //??? ??? // 1、??? ??? cvNamedWindow("contour1");??? ??? cvCopyImage(img, img_temp);??? ??? double t = (double)cvGetTickCount();? ??? cvFindContours(img_temp, mem_storage, &first_contour);??? ??? cvZero(img_temp);??? ??? cvDrawContours(??? ??????? img_temp,???? ??????? first_contour,??? ??????? cvScalar(100),??? ??????? cvScalar(100),??? ??????? 1??? ??????? );??? ??? t = (double)cvGetTickCount() - t;?? ??? cvShowImage("contour1", img_temp);??? ??? printf("run1 = %gms\n", t/(cvGetTickFrequency()*1000.));??? ??? cvClearMemStorage(mem_storage);??? ??? //??? ??? // 2、??? ??? cvNamedWindow("contour2");??? ??? cvCopyImage(img, img_temp);??? ??? t = (double)cvGetTickCount();? ??? CvContourScanner scanner = cvStartFindContours(img_temp, mem_storage);??? ??? while (cvFindNextContour(scanner));??? ??? first_contour = cvEndFindContours(&scanner);??? ??????? ??? cvZero(img_temp);??? ??? cvDrawContours(??? ??????? img_temp,???? ??????? first_contour,??? ??????? cvScalar(100),??? ??????? cvScalar(100),??? ??????? 1??? ??????? );??? ??? t = (double)cvGetTickCount() - t;?? ??? cvShowImage("contour2", img_temp);??? ????? ??? printf("run2 = %gms\n", t/(cvGetTickFrequency()*1000.));??? ??????? ??? cvClearMemStorage(mem_storage);??? ??? cvReleaseImage(&img);??? ??? cvReleaseImage(&img_temp);??? ??? ??? cvWaitKey();??? ? ??? /************************************************************************/??? ??? /* 經(jīng)測試 run1 = 16.1431ms run2 = 15.8677ms (參考) ?????? 不過可以肯定這兩中算法時(shí)間復(fù)雜度是相同的???????????????????????????????????? */??? ??? /************************************************************************/??? ??????? ??? //??? ??? // 上述兩種方法完成了對輪廓的提取,如想繪制輪廓都得配合cvDrawContours來使用??? ??? // 而cvDrawContours 函數(shù)第5個(gè)參數(shù)為 max_level 經(jīng)查ICVL含義如下:??? ??? //??? ??? // 繪制輪廓的最大等級。如果等級為0，繪制單獨(dú)的輪廓。如果為1，繪制輪廓及在其后的相同的級別下輪廓。??? ??? // 如果值為2，所有的輪廓。如果等級為2，繪制所有同級輪廓及所有低一級輪廓，諸此種種。如果值為負(fù)數(shù)，??? ??? // 函數(shù)不繪制同級輪廓，但會(huì)升序繪制直到級別為abs(max_level)-1的子輪廓。??? ??? //??? ??? // 相信好多讀者初次都無法理解等級的含義,而且測試時(shí)候輸入>=1 的整數(shù)效果幾乎一樣??? ??? // 只有提取輪廓時(shí)候的提取模式設(shè)為 CV_RETR_CCOMP CV_RETR_TREE 時(shí)這個(gè)參數(shù)才有意義??? ??? //??? ??? // 經(jīng)查FindContours 函數(shù)里面這樣介紹提取模式(mode)的這兩個(gè)參數(shù):??? ??? // CV_RETR_CCOMP - 提取所有輪廓，并且將其組織為兩層的 hierarchy: 頂層為連通域的外圍邊界，次層為洞的內(nèi)層邊界。???? ??? // CV_RETR_TREE - 提取所有輪廓，并且重構(gòu)嵌套輪廓的全部 hierarchy???? ??? //???? ??? // 下面用第一種方法進(jìn)行測試??? ??? ??? cvNamedWindow("contour_test");??? ??? cvNamedWindow("contour_raw");??? ??? img = cvLoadImage("contour.jpg", CV_LOAD_IMAGE_GRAYSCALE);??? ??? cvShowImage("contour_raw", img);??? ??? cvThreshold(img, img, 128, 255, CV_THRESH_BINARY);??? ??? img_temp = cvCloneImage(img);??? ??? cvFindContours(??? ??????? img_temp,???? ??????? mem_storage,???? ??????? &first_contour,??? ??????? sizeof(CvContour),??? ??????? CV_RETR_CCOMP?????????? //#1 需更改區(qū)域??? ??????? );??? ??? ??? cvZero(img_temp);??? ??? cvDrawContours(??? ??????? img_temp,???? ??????? first_contour,??? ??????? cvScalar(100),??? ??????? cvScalar(100),??? ??????? 1?????????????????????? //#2 需更改區(qū)域??? ??????? );??? ??? cvShowImage("contour_test", img_temp);??? ??? /************************************************************************/??? ??? /* (1, 2) = (CV_RETR_CCOMP, 1)? 如圖1? ?????? (1, 2) = (CV_RETR_CCOMP, 2)? 如圖2? ?????? (1, 2) = (CV_RETR_TREE, 1)?? 如圖3? ?????? (1, 2) = (CV_RETR_TREE, 2)?? 如圖4? ?????? (1, 2) = (CV_RETR_TREE, 6)?? 如圖5? ?????? 經(jīng)分析CV_RETR_CCOMP 只把圖像分為兩個(gè)層次,頂層和次層,一等級輪廓只匹配與其最接近? ?????? 的內(nèi)側(cè)輪廓即2等級? ?????? CV_RETR_TREE 則從輪廓外到內(nèi)按等級1 - n 全部分配????????? ?????? CV_RETR_LIST 全部輪廓均為1級??????????????????????? */??? ??? /************************************************************************/??? ??? ??? cvWaitKey();??? ??? cvReleaseImage(&img);??? ??? cvReleaseImage(&img_temp);??? ??? cvReleaseMemStorage(&mem_storage);??? ??? cvDestroyAllWindows();??? ??? return 0;??? }

原圖

圖一

圖二

圖三

圖四

圖五

這是OpenCV的經(jīng)典一個(gè)例子：

#include "cv.h"#include "cxcore.h"#include "highgui.h"#include <math.h>#endif?#pragma?? comment(lib,"cv.lib")? #pragma?? comment(lib,"highgui.lib")? #pragma?? comment(lib,"cxcore.lib")#define w 500int levels = 3;CvSeq* contours = 0;?void on_trackbar(int pos){??? IplImage* cnt_img = cvCreateImage( cvSize(w,w), 8, 3 );??? CvSeq* _contours = contours;??? int _levels = levels - 3;??? if( _levels <= 0 ) // get to the nearest face to make it look more funny??????? _contours = _contours->h_next->h_next->h_next->h_next->h_next->h_next->h_next->v_next->h_next->h_next;//_contours = _contours->v_next;??? cvZero( cnt_img );??? cvDrawContours( cnt_img, _contours, CV_RGB(255,0,0), CV_RGB(0,255,0), _levels);//, 3, CV_AA, cvPoint(0,0) );??? /*_levels:3，所有外輪廓及包含的內(nèi)輪廓及里面的內(nèi)輪廓2：所有外輪廓及包含的內(nèi)輪廓1:所有外輪廓0，第一個(gè)外輪廓-1：第一個(gè)外輪廓及包含的內(nèi)輪廓-2：第一個(gè)外輪廓及包含的內(nèi)輪廓及里面的內(nèi)輪廓?? _contours->h_next:同級的下一個(gè)輪廓_contours->v_next父級下的下層區(qū)域；*/cvShowImage( "contours", cnt_img );??? cvReleaseImage( &cnt_img );}?int main( int argc, char** argv ){??? int i, j;??? CvMemStorage* storage = cvCreateMemStorage(0);??? IplImage* img = cvCreateImage( cvSize(w,w), 8, 1 );???? cvZero( img );???? for( i=0; i < 6; i++ )??? {??????? int dx = (i%2)*250 - 30;//0%2=0;??????? int dy = (i/2)*150;??????? CvScalar white = cvRealScalar(255);??????? CvScalar black = cvRealScalar(0);???????? if( i == 0 )??????? {??????????? for( j = 0; j <= 10; j++ )??????????? {??????????????? double angle = (j+5)*CV_PI/21;??????????????? cvLine(img, cvPoint(cvRound(dx+100+j*10-80*cos(angle)),??????????????????? cvRound(dy+100-90*sin(angle))),??????????????????? cvPoint(cvRound(dx+100+j*10-30*cos(angle)),??????????????????? cvRound(dy+100-30*sin(angle))), white, 1, 8, 0);??????????? }??????? }???????? cvEllipse( img, cvPoint(dx+150, dy+100), cvSize(100,70), 0, 0, 360, white, -1, 8, 0 );??????? cvEllipse( img, cvPoint(dx+115, dy+70), cvSize(30,20), 0, 0, 360, black, -1, 8, 0 );??????? cvEllipse( img, cvPoint(dx+185, dy+70), cvSize(30,20), 0, 0, 360, black, -1, 8, 0 );??????? cvEllipse( img, cvPoint(dx+115, dy+70), cvSize(15,15), 0, 0, 360, white, -1, 8, 0 );??????? cvEllipse( img, cvPoint(dx+185, dy+70), cvSize(15,15), 0, 0, 360, white, -1, 8, 0 );??????? cvEllipse( img, cvPoint(dx+115, dy+70), cvSize(5,5), 0, 0, 360, black, -1, 8, 0 );??????? cvEllipse( img, cvPoint(dx+185, dy+70), cvSize(5,5), 0, 0, 360, black, -1, 8, 0 );??????? cvEllipse( img, cvPoint(dx+150, dy+100), cvSize(10,5), 0, 0, 360, black, -1, 8, 0 );??????? cvEllipse( img, cvPoint(dx+150, dy+150), cvSize(40,10), 0, 0, 360, black, -1, 8, 0 );??????? cvEllipse( img, cvPoint(dx+27, dy+100), cvSize(20,35), 0, 0, 360, white, -1, 8, 0 );??????? cvEllipse( img, cvPoint(dx+273, dy+100), cvSize(20,35), 0, 0, 360, white, -1, 8, 0 );??? }???? cvNamedWindow( "image", 1 );??? cvShowImage( "image", img );???? cvFindContours( img, storage, &contours, sizeof(CvContour),??????????????????? 2, CV_CHAIN_APPROX_SIMPLE, cvPoint(0,0) );???? // comment this out if you do not want approximation??? contours = cvApproxPoly( contours, sizeof(CvContour), storage, CV_POLY_APPROX_DP, 3, 1 );?//cvApproxPoly:???????????????????????????????????????????????? 逼近方法???? 精度 逼近曲線是否封閉??? cvNamedWindow( "contours", 1 );??? cvCreateTrackbar( "levels+3", "contours", &levels, 7, on_trackbar );???? on_trackbar(0);??? cvWaitKey(0);??? cvReleaseMemStorage( &storage );??? cvReleaseImage( &img );???? return 0;}

主要還是理解下int mode=CV_RETR_LIST,int method=CV_CHAIN_APPROX_SIMPLE,CvPoint offset=cvPoint(0,0));

當(dāng)mode?為CV_RETR_CCOMP?只把圖像分為兩個(gè)層次,頂層和次層,一等級輪廓只匹配與其最接近??；

cvDrawContours?函數(shù)第5個(gè)參數(shù)為?max_level=0時(shí)，笑臉圖像會(huì)顯示第一個(gè)找到的輪廓，左邊的白色耳朵一只；

max_level=1時(shí)，所有白色區(qū)域的輪廓都會(huì)被顯示出來，因?yàn)樗麄兌紝儆诘燃?；

max_level=2時(shí)；每個(gè)白色區(qū)域里面的黑色區(qū)域會(huì)被顯示出來，可能一個(gè)白色區(qū)域下面有多個(gè)黑色區(qū)域，但他們都是同級的；

這里你要注意的的是每個(gè)白色區(qū)域下的黑色區(qū)域，如臉下面有4個(gè)黑色區(qū)域，白色眼珠下有一個(gè)黑色區(qū)域，這個(gè)黑色區(qū)域與臉下的那三個(gè)區(qū)域時(shí)同級的，也就是說他不屬于臉的內(nèi)區(qū)域，他是白色眼珠的內(nèi)區(qū)域；

當(dāng)mode為???????CV_RETR_LIST?全部輪廓均為1級

???????????

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