将多个凸包连接起来形成一个大凸包找到最接近的轮廓
2024-06-04 05:06:19
目的:对于很暗很暗的图像 用普通方法不好一下找到轮廓 现在需要找到其最接近的轮廓
像这样的图像 拍的是一块完整的石头 蓝色部分只是石头的反光部分而已 现在是要找到这个石头的轮廓 最终得到它的面积。
#include<opencv2/opencv.hpp>
#include<opencv2/imgproc/imgproc.hpp>
#include<opencv2/highgui/highgui.hpp>
#include <afxwin.h>
#include<fstream>
using namespace std;
using namespace cv;Mat my_contour(IplImage* dst, IplImage bimgipl)
{cvZero(dst);CvMemStorage *storage = cvCreateMemStorage();CvSeq *contour = NULL, *hull = NULL;vector<CvPoint> allpoints;CvContourScanner scanner = cvStartFindContours(&bimgipl, storage);while ((contour = cvFindNextContour(scanner)) != NULL){cvDrawContours(dst, contour, cv::Scalar(255), cv::Scalar(255), 0);hull = cvConvexHull2(contour, 0, CV_CLOCKWISE, 0);CvPoint pt0 = **(CvPoint**)cvGetSeqElem(hull, hull->total - 1);allpoints.push_back(pt0);for (int i = 0; i < hull->total; ++i){CvPoint pt1 = **(CvPoint**)cvGetSeqElem(hull, i);allpoints.push_back(pt1);cvLine(dst, pt0, pt1, cv::Scalar(255));pt0 = pt1;}}//上面是第一次寻找 可能找到了多个轮廓即有多个凸包 下面存储每个凸包的凸点到容器中 然后将这些点连接起来 这样就有凹陷的地方了 就可以在此基础上寻找最后的凸包了 Mat dstmat(dst, 0);std::vector<std::vector<cv::Point>> myown_contours;cv::findContours(dstmat, myown_contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);//判断也许本来就只有一个凸包 就不用存点画线再寻一次凸包了if (myown_contours.size() > 1){for (int i = 0; i < allpoints.size() - 1; i++){CvPoint firstdot = allpoints[i];CvPoint secdot = allpoints[i + 1];cvLine(dst, firstdot, secdot, cv::Scalar(255), 2);}CvContourScanner scanner2 = cvStartFindContours(dst, storage);while ((contour = cvFindNextContour(scanner2)) != NULL){cvDrawContours(dst, contour, cv::Scalar(255), cv::Scalar(255), 0);hull = cvConvexHull2(contour, 0, CV_CLOCKWISE, 0);CvPoint pt0 = **(CvPoint**)cvGetSeqElem(hull, hull->total - 1);for (int i = 0; i < hull->total; ++i){CvPoint pt1 = **(CvPoint**)cvGetSeqElem(hull, i);cvLine(dst, pt0, pt1, cv::Scalar(255));pt0 = pt1;}}}Mat bimgdst(dst, 0);std::vector<std::vector<cv::Point>> contours;cv::findContours(bimgdst, contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);Mat contoursimg(bimgdst.size(), CV_8UC1, cv::Scalar(0));drawContours(contoursimg, contours, -1, Scalar(255), CV_FILLED);return contoursimg;
}char filename[100];
char savename[100];void main()
{TickMeter tm;tm.start();vector<Mat> bgrimgs;for (int i = 1; i <= 1657; i++){sprintf(filename, "正常图_压缩\\%d.bmp", i);sprintf(savename, "my_result3\\%d.bmp", i);Mat img = imread(filename);//split(img, bgrimgs);Mat bimg(img.size(), CV_8UC1, cv::Scalar(0));bgrimgs[0].copyTo(bimg);// threshold(bimg, bimg, 12, 255, CV_THRESH_BINARY/*|CV_THRESH_OTSU*/);//imshow("thresh result", bimg);//Mat element(4, 4, CV_8U, cv::Scalar(1));morphologyEx(bimg, bimg, cv::MORPH_OPEN, element);//imshow("dilate result", bimg);//前20行置0 去除上部分的水滴噪声 后20行也置0 去除下面的噪声/* //这个置0没有下面写的置0好 用下面的IplImage bimgipl = bimg;cvSetImageROI(&bimgipl, cvRect(0, 0, bimg.size().width,20));IplImage* bimg_front = cvCreateImage(cvSize(bimg.size().width, 20), IPL_DEPTH_8U, 1);cvCopy(&bimgipl, bimg_front, 0);cvShowImage("front", bimg_front);cvSetImageROI(&bimgipl, cvRect(0, bimg.size().height-20, bimg.size().width, 20));IplImage* bimg_end = cvCreateImage(cvSize(bimg.size().width, 20), IPL_DEPTH_8U, 1);cvCopy(&bimgipl, bimg_end, 0);cvShowImage("end", bimg_end);cvZero(bimg_front);cvZero(bimg_end);*/for (int i = 0; i < 20; i++){uchar* data = bimg.ptr<uchar>(i);for (int j = 0; j < bimg.size().width; j++)data[j] = 0;}for (int i = bimg.size().height - 19; i < bimg.size().height; i++){uchar* data = bimg.ptr<uchar>(i);for (int j = 0; j < bimg.size().width; j++)data[j] = 0;}//凸包找轮廓 (我用了2次凸包 中间用线连接 方便第二次凸包 找到完整轮廓)IplImage mybimgipl = bimg;IplImage *mydst = cvCreateImage(cvGetSize(&mybimgipl), 8, 1);Mat myresult(mydst, 0);myresult = my_contour(mydst, mybimgipl);imwrite(savename, myresult);}tm.stop();cout << "count=" << tm.getCounter() << ",process time=" << tm.getTimeMilli() << " ms" << endl;}
拿一种一张图的中间结果来说：
分别是阈值化 开操作 第一次凸包 第一次凸包填充后的结果
左图就是对于第一次凸包连线后 再凸包后的结果 右边就是对左图填充后的结果 也是最终结果！
done！！！！今天星期五！好开心！！！！！！！！！！！！
关于opencv中找轮廓的 ： http://www.cnblogs.com/nktblog/p/4027137.html 写得很棒
给学校我自习室的电脑上装了opencv2.4.13 按照http://blog.csdn.net/dcrmg/article/details/51809614
看到巴卫和奈奈生就开心。。。。。。
//
我公司的同事说我这个比较慢 他在网上 https://github.com/abatilo/QuickHull 找到一个快速找凸包的叫我应用进来：于是我重新又写了个：
#include <algorithm>
#include <cmath>
#include <vector>
#include <chrono>
#include <cstdio>
#include <random>
#include <vector>#include<opencv2/opencv.hpp>
#include<opencv2/imgproc/imgproc.hpp>
#include<opencv2/highgui/highgui.hpp>
using namespace std;
using namespace cv;struct myPoint {int x;int y;bool operator<(const myPoint& pt) {if (x == pt.x) {return (y < pt.y);}return (x < pt.x);}
};// http://stackoverflow.com/questions/1560492/how-to-tell-whether-a-myPoint-is-to-the-right-or-left-side-of-a-line
// A and B are used to define a line
// C is the myPoint whose side we're trying to determine
int SideOfLine(const myPoint &P1, const myPoint &P2, const myPoint &P3) {return (P2.x - P1.x) * (P3.y - P1.y) - (P2.y - P1.y) * (P3.x - P1.x);
}// https://en.wikipedia.org/wiki/Distance_from_a_myPoint_to_a_line#Line_defined_by_two_myPoints
float DistanceFromLine(const myPoint &P1, const myPoint &P2, const myPoint &P3) {return (std::abs((P2.y - P1.y) * P3.x - (P2.x - P1.x) * P3.y + P2.x * P1.y - P2.y * P1.x)/ std::sqrt((P2.y - P1.y) * (P2.y - P1.y) + (P2.x - P1.x) * (P2.x - P1.x)));
}// http://stackoverflow.com/questions/13300904/determine-whether-myPoint-lies-inside-triangle
bool myPointInTriangle(const myPoint &p, const myPoint &p1, const myPoint &p2, const myPoint &p3) {float a = ((p2.y - p3.y) * (p.x - p3.x) + (p3.x - p2.x) * (p.y - p3.y)) / ((p2.y - p3.y) * (p1.x - p3.x) + (p3.x - p2.x) * (p1.y - p3.y));float b = ((p3.y - p1.y) * (p.x - p3.x) + (p1.x - p3.x) * (p.y - p3.y)) / ((p2.y - p3.y) * (p1.x - p3.x) + (p3.x - p2.x) * (p1.y - p3.y));float c = 1.0f - a - b;return (0.0f < a && 0.0f < b && 0.0f < c);
}// http://www.cse.yorku.ca/~aaw/Hang/quick_hull/Algorithm.html
void FindHull(const std::vector<myPoint> &Sk, const myPoint P, const myPoint Q, std::vector<myPoint> &hullmyPoints) {// If Sk has no myPoint, then returnif (Sk.size() == 0) return;std::vector<myPoint> S0;std::vector<myPoint> S1;std::vector<myPoint> S2;// From the given set of myPoints in Sk, find farthest myPoint, say C, from segment PQ float furthestDistance = 0.0f;myPoint C;for (const auto &pt : Sk) {float distance = DistanceFromLine(P, Q, pt);if (distance > furthestDistance) {furthestDistance = distance;C = pt;}}// Add myPoint C to convex hull at the location between P and Q hullmyPoints.push_back(C);/** Three myPoints P, Q, and C partition the remaining myPoints of Sk into 3 subsets: S0, S1, and S2* where S0 are myPoints inside triangle PCQ, S1are myPoints on the right side of the oriented* line from P to C, and S2 are myPoints on the right side of the oriented line from C to Q.*/for (const auto &pt : Sk) {if (myPointInTriangle(pt, P, C, Q)) {S0.push_back(pt);}else if (0 < SideOfLine(P, C, pt)) {S1.push_back(pt);}else if (0 < SideOfLine(C, Q, pt)) {S2.push_back(pt);}}FindHull(S1, P, C, hullmyPoints);FindHull(S2, C, Q, hullmyPoints);
}// http://www.cse.yorku.ca/~aaw/Hang/quick_hull/Algorithm.html
void QuickHull(const std::vector<myPoint> &s, std::vector<myPoint> &hullmyPoints) {// Find left and right most myPoints, say A & B, and add A & B to convex hull myPoint A = s[0];myPoint B = s[s.size() - 1];hullmyPoints.push_back(A);hullmyPoints.push_back(B);std::vector<myPoint> S1;std::vector<myPoint> S2;/** Segment AB divides the remaining (n-2) myPoints into 2 groups S1 and S2* where S1 are myPoints in S that are on the right side of the oriented line from A to B,* and S2 are myPoints in S that are on the right side of the oriented line from B to A*/for (auto it = s.begin() + 1; it != s.end() - 1; ++it) {const myPoint pt = *it;const int s1 = SideOfLine(A, B, pt);const int s2 = SideOfLine(B, A, pt);if (0 < s1) {S1.push_back(pt);}else if (0 < s2) {S2.push_back(pt);}}FindHull(S1, A, B, hullmyPoints);FindHull(S2, B, A, hullmyPoints);
}Mat mypredone(IplImage* srcipl, vector<Mat> bgrimgs)
{预处理Mat img(srcipl, 0);split(img, bgrimgs);Mat bimg(img.size(), CV_8UC1, cv::Scalar(0));bgrimgs[0].copyTo(bimg);threshold(bimg, bimg, 12, 255, CV_THRESH_BINARY/*|CV_THRESH_OTSU*/);Mat element(4, 4, CV_8U, cv::Scalar(1));morphologyEx(bimg, bimg, cv::MORPH_OPEN, element);for (int i = 0; i < 20; i++){uchar* data = bimg.ptr<uchar>(i);for (int j = 0; j < bimg.size().width; j++)data[j] = 0;}//for (int i = bimg.size().height - 19; i < bimg.size().height; i++)//{// uchar* data = bimg.ptr<uchar>(i);// for (int j = 0; j < bimg.size().width; j++)// data[j] = 0;//}return bimg;
}IplImage* luobin_findcontour(Mat bimg)
{IplImage mybimgipl = bimg;CvMemStorage *storage = cvCreateMemStorage();CvSeq *contour = NULL, *hull = NULL;vector<CvPoint> allpoints;vector<myPoint> myallpoints;CvContourScanner scanner = cvStartFindContours(&mybimgipl, storage);while ((contour = cvFindNextContour(scanner)) != NULL){hull = cvConvexHull2(contour, 0, CV_CLOCKWISE, 0);CvPoint pt0 = **(CvPoint**)cvGetSeqElem(hull, hull->total - 1);myPoint mypt0;mypt0.x = (float)pt0.x;mypt0.y = (float)pt0.y;mypt0.operator<(mypt0); allpoints.push_back(pt0);myallpoints.push_back(mypt0);for (int i = 0; i < hull->total; ++i){CvPoint pt1 = **(CvPoint**)cvGetSeqElem(hull, i);allpoints.push_back(pt1);//cvLine(mydst, pt0, pt1, cv::Scalar(255));//pt0 = pt1;myPoint mypt1;mypt1.x = (float)pt1.x;mypt1.y = (float)pt1.y;mypt1.operator<(mypt1); //myallpoints.push_back(mypt1);}}std::sort(myallpoints.begin(), myallpoints.end());std::vector<myPoint> myhullPoints;QuickHull(myallpoints, myhullPoints);CvSeq *hull2 = NULL;CvSeq* ptseq = cvCreateSeq(CV_SEQ_KIND_GENERIC | CV_32SC2, sizeof(CvContour), sizeof(CvPoint), storage);for (int i = 0; i < myhullPoints.size(); ++i){myPoint pt1 = myhullPoints[i];CvPoint myfinalpot1;myfinalpot1.x = pt1.x;myfinalpot1.y = pt1.y;cvSeqPush(ptseq, &myfinalpot1);}hull2 = cvConvexHull2(ptseq, 0, CV_CLOCKWISE, 1);IplImage *mydst3 = cvCreateImage(cvGetSize(&mybimgipl), 8, 1);cvZero(mydst3);cvDrawContours(mydst3, hull2, CV_RGB(255, 255, 255), CV_RGB(255, 255, 255), -1, CV_FILLED, 8);return mydst3;
}char filename[100];
char newcontour[100];void main()
{IplImage* src_ipl = cvLoadImage("12.bmp");cvShowImage("srcimage", src_ipl);vector<Mat> bgrimgs;Mat bimg = mypredone(src_ipl, bgrimgs);IplImage* luobin_result = luobin_findcontour(bimg);cvShowImage("luobin result2", luobin_result);waitKey(0);/*TickMeter tm;tm.start();for (int i = 55124; i <= 56460; i++){int newi = i - 55123;sprintf(filename, "背面图\\%d.bmp", i);sprintf(newcontour, "罗彬背面轮廓\\%d.bmp", newi);IplImage* src_ipl = cvLoadImage(filename);vector<Mat> bgrimgs;Mat bimg = mypredone(src_ipl, bgrimgs);IplImage* luobin_result = luobin_findcontour(bimg);cvSaveImage(newcontour, luobin_result);}tm.stop();cout << "count=" << tm.getCounter() << ",process time=" << tm.getTimeMilli() << endl;*/
}和上面我自己的算法是同一张原图 的确比我的快了将近一倍！
但对带噪声的图，直接用上面这个快速凸包寻找轮廓的办法就不行：
我把原图、灰度图、上面这个快速凸包找轮廓的图、我后一篇自己写的结果图 对比了一下：
char filename[100];
char newcontour[100];
char grayimg[100];
char myback[100];
char contrast[100];void main()
{TickMeter tm;tm.start();CvSize mysize = cvSize(484 * 4, 364);for (int i = 1; i <= 1337; i++){sprintf(filename, "背面图\\%d.bmp", i);sprintf(newcontour, "罗彬背面轮廓\\%d.bmp", i);sprintf(grayimg, "背面灰度\\%d.bmp", i);sprintf(myback, "我的背面轮廓\\%d.bmp", i); sprintf(contrast, "背面对比图\\%d.bmp", i);IplImage* left = cvLoadImage(filename);IplImage* combine = cvCreateImage(mysize, left->depth, left->nChannels);cvZero(combine); cvSetImageROI(combine, cvRect(0, 0, left->width, left->height)); cvCopy(left, combine);cvResetImageROI(combine);IplImage* right = cvLoadImage(grayimg);cvSetImageROI(combine, cvRect(483, 0, right->width, right->height));cvCopy(right, combine);cvResetImageROI(combine);IplImage* right2 = cvLoadImage(newcontour);cvSetImageROI(combine, cvRect(484*2-1, 0, right2->width, right2->height));cvCopy(right2, combine);cvResetImageROI(combine);IplImage* right3 = cvLoadImage(myback);cvSetImageROI(combine, cvRect(484 * 3 - 1, 0, right3->width, right3->height));cvCopy(right3, combine);cvResetImageROI(combine);cvSaveImage(contrast, combine);}tm.stop();cout << "count=" << tm.getCounter() << ",process time=" << tm.getTimeMilli() << endl;
}
所以 对有杂质的还是不能够直接用 还需要修改。
最终改成了：
#include <algorithm>
#include <cmath>
#include <vector>
#include <chrono>
#include <cstdio>
#include <random>
#include <vector>
#include<opencv2/opencv.hpp>
#include<opencv2/imgproc/imgproc.hpp>
#include<opencv2/highgui/highgui.hpp>
using namespace std;
using namespace cv;struct myPoint {int x;int y;bool operator<(const myPoint& pt) {if (x == pt.x){return (y < pt.y);}return (x < pt.x);}
};// http://stackoverflow.com/questions/1560492/how-to-tell-whether-a-myPoint-is-to-the-right-or-left-side-of-a-line
int SideOfLine(const myPoint &P1, const myPoint &P2, const myPoint &P3) {return (P2.x - P1.x) * (P3.y - P1.y) - (P2.y - P1.y) * (P3.x - P1.x);
}// https://en.wikipedia.org/wiki/Distance_from_a_myPoint_to_a_line#Line_defined_by_two_myPoints
float DistanceFromLine(const myPoint &P1, const myPoint &P2, const myPoint &P3) {return (std::abs((P2.y - P1.y) * P3.x - (P2.x - P1.x) * P3.y + P2.x * P1.y - P2.y * P1.x)/ std::sqrt((P2.y - P1.y) * (P2.y - P1.y) + (P2.x - P1.x) * (P2.x - P1.x)));
}// http://stackoverflow.com/questions/13300904/determine-whether-myPoint-lies-inside-triangle
bool myPointInTriangle(const myPoint &p, const myPoint &p1, const myPoint &p2, const myPoint &p3) {float a = ((p2.y - p3.y) * (p.x - p3.x) + (p3.x - p2.x) * (p.y - p3.y)) / ((p2.y - p3.y) * (p1.x - p3.x) + (p3.x - p2.x) * (p1.y - p3.y));float b = ((p3.y - p1.y) * (p.x - p3.x) + (p1.x - p3.x) * (p.y - p3.y)) / ((p2.y - p3.y) * (p1.x - p3.x) + (p3.x - p2.x) * (p1.y - p3.y));float c = 1.0f - a - b;return (0.0f < a && 0.0f < b && 0.0f < c);
}// http://www.cse.yorku.ca/~aaw/Hang/quick_hull/Algorithm.html
void FindHull(const std::vector<myPoint> &Sk, const myPoint P, const myPoint Q, std::vector<myPoint> &hullmyPoints) {if (Sk.size() == 0) return;std::vector<myPoint> S0;std::vector<myPoint> S1;std::vector<myPoint> S2;float furthestDistance = 0.0f;myPoint C;for (const auto &pt : Sk) {float distance = DistanceFromLine(P, Q, pt);if (distance > furthestDistance) {furthestDistance = distance;C = pt;}}hullmyPoints.push_back(C);for (const auto &pt : Sk) {if (myPointInTriangle(pt, P, C, Q)) {S0.push_back(pt);}else if (0 < SideOfLine(P, C, pt)) {S1.push_back(pt);}else if (0 < SideOfLine(C, Q, pt)) {S2.push_back(pt);}}FindHull(S1, P, C, hullmyPoints);FindHull(S2, C, Q, hullmyPoints);
}// http://www.cse.yorku.ca/~aaw/Hang/quick_hull/Algorithm.html
void QuickHull(const std::vector<myPoint> &s, std::vector<myPoint> &hullmyPoints) {myPoint A = s[0];myPoint B = s[s.size() - 1];hullmyPoints.push_back(A);hullmyPoints.push_back(B);std::vector<myPoint> S1;std::vector<myPoint> S2;for (auto it = s.begin() + 1; it != s.end() - 1; ++it) {const myPoint pt = *it;const int s1 = SideOfLine(A, B, pt);const int s2 = SideOfLine(B, A, pt);if (0 < s1) {S1.push_back(pt);}else if (0 < s2) {S2.push_back(pt);}}FindHull(S1, A, B, hullmyPoints);FindHull(S2, B, A, hullmyPoints);
}Mat mypredone(IplImage* srcipl, vector<Mat> bgrimgs)
{预处理Mat img(srcipl, 0);split(img, bgrimgs);Mat bimg(img.size(), CV_8UC1, cv::Scalar(0));bgrimgs[0].copyTo(bimg);threshold(bimg, bimg, 10, 255, CV_THRESH_BINARY/*|CV_THRESH_OTSU*/);Mat element(4, 4, CV_8U, cv::Scalar(1));morphologyEx(bimg, bimg, cv::MORPH_OPEN, element);//for (int i = 0; i < 20; i++)//{// uchar* data = bimg.ptr<uchar>(i);// for (int j = 0; j < bimg.size().width; j++)// data[j] = 0;//}//for (int i = bimg.size().height - 19; i < bimg.size().height; i++)//{// uchar* data = bimg.ptr<uchar>(i);// for (int j = 0; j < bimg.size().width; j++)// data[j] = 0;//}return bimg;
}
//背面quickhull 去除溜槽走光点等噪声
IplImage* luobin_backcontour(Mat bimg)
{IplImage mybimgipl = bimg;CvMemStorage *storage = cvCreateMemStorage();CvSeq *contour = NULL, *hull = NULL;vector<CvPoint> allpoints;vector<myPoint> myallpoints;CvContourScanner scanner = cvStartFindContours(&mybimgipl, storage);while ((contour = cvFindNextContour(scanner)) != NULL){/去掉溜槽走光点的 想法CvMoments *moments = (CvMoments*)malloc(sizeof(CvMoments));cvMoments(contour, moments, 1);double moment10 = cvGetSpatialMoment(moments, 1, 0);double moment01 = cvGetSpatialMoment(moments, 0, 1);double area = cvGetSpatialMoment(moments, 0, 0);double posX = moment10 / area;double posY = moment01 / area;double mylenth = cvArcLength(contour);double myarea = cvContourArea(contour);//cout << "length=" << mylenth << " area=" << myarea << " 重心： " << "(" << posX << " , " << posY << ")" << " " << endl;//center lightif (posX > double(236.0) && posX<double(243.0) && posY>double(171.0) && posY<double(197.0) && myarea<double(141) && mylenth < double(71)){cvSubstituteContour(scanner, NULL);continue;}//right lightif (posX > double(384.0) && posX<double(395.0) && posY>double(90.0) && posY<double(113.0) && myarea<double(316) && mylenth < double(90)){cvSubstituteContour(scanner, NULL);continue;}//belowif (posX >160.0 && posX<331.0 && posY>295.0 && posY < 362.0 && myarea < 170 && mylenth < 100){cvSubstituteContour(scanner, NULL);continue;}if (posX >212.0 && posX<251.0 && posY>248.0 && posY < 269.0 && myarea < 21 && mylenth < 20){cvSubstituteContour(scanner, NULL);continue;}if (posX >256.0 && posX<271.0 && posY>296.0 && posY < 299.5 && myarea < 25 && mylenth < 20){cvSubstituteContour(scanner, NULL);continue;}if (posX >210.0 && posX<215.0 && posY>350.0 && posY < 358.0 && myarea < 250 && mylenth < 100){cvSubstituteContour(scanner, NULL);continue;}// special if (myarea == 0){cvSubstituteContour(scanner, NULL);continue;}///hull = cvConvexHull2(contour, 0, CV_CLOCKWISE, 0);CvPoint pt0 = **(CvPoint**)cvGetSeqElem(hull, hull->total - 1);myPoint mypt0;mypt0.x = (float)pt0.x;mypt0.y = (float)pt0.y;allpoints.push_back(pt0);myallpoints.push_back(mypt0);for (int i = 0; i < hull->total; ++i){CvPoint pt1 = **(CvPoint**)cvGetSeqElem(hull, i);allpoints.push_back(pt1);myPoint mypt1;mypt1.x = (float)pt1.x;mypt1.y = (float)pt1.y;myallpoints.push_back(mypt1);}}std::sort(myallpoints.begin(), myallpoints.end());std::vector<myPoint> myhullPoints;QuickHull(myallpoints, myhullPoints);CvSeq *hull2 = NULL;CvSeq* ptseq = cvCreateSeq(CV_SEQ_KIND_GENERIC | CV_32SC2, sizeof(CvContour), sizeof(CvPoint), storage);for (int i = 0; i < myhullPoints.size(); ++i){myPoint pt1 = myhullPoints[i];CvPoint myfinalpot1;myfinalpot1.x = pt1.x;myfinalpot1.y = pt1.y;cvSeqPush(ptseq, &myfinalpot1);}hull2 = cvConvexHull2(ptseq, 0, CV_CLOCKWISE, 1);IplImage *mydst3 = cvCreateImage(cvGetSize(&mybimgipl), 8, 1);cvZero(mydst3);cvDrawContours(mydst3, hull2, CV_RGB(255, 255, 255), CV_RGB(255, 255, 255), -1, CV_FILLED, 8);return mydst3;
}//正面quickhull
IplImage* luobin_frontcontour(Mat bimg)
{IplImage mybimgipl = bimg;CvMemStorage *storage = cvCreateMemStorage();CvSeq *contour = NULL, *hull = NULL;vector<CvPoint> allpoints;vector<myPoint> myallpoints;CvContourScanner scanner = cvStartFindContours(&mybimgipl, storage);while ((contour = cvFindNextContour(scanner)) != NULL){hull = cvConvexHull2(contour, 0, CV_CLOCKWISE, 0);CvPoint pt0 = **(CvPoint**)cvGetSeqElem(hull, hull->total - 1);myPoint mypt0;mypt0.x = (float)pt0.x;mypt0.y = (float)pt0.y;allpoints.push_back(pt0);myallpoints.push_back(mypt0);for (int i = 0; i < hull->total; ++i){CvPoint pt1 = **(CvPoint**)cvGetSeqElem(hull, i);allpoints.push_back(pt1);myPoint mypt1;mypt1.x = (float)pt1.x;mypt1.y = (float)pt1.y;myallpoints.push_back(mypt1);}}std::sort(myallpoints.begin(), myallpoints.end());std::vector<myPoint> myhullPoints;QuickHull(myallpoints, myhullPoints);CvSeq *hull2 = NULL;CvSeq* ptseq = cvCreateSeq(CV_SEQ_KIND_GENERIC | CV_32SC2, sizeof(CvContour), sizeof(CvPoint), storage);for (int i = 0; i < myhullPoints.size(); ++i){myPoint pt1 = myhullPoints[i];CvPoint myfinalpot1;myfinalpot1.x = pt1.x;myfinalpot1.y = pt1.y;cvSeqPush(ptseq, &myfinalpot1);}hull2 = cvConvexHull2(ptseq, 0, CV_CLOCKWISE, 1);IplImage *mydst3 = cvCreateImage(cvGetSize(&mybimgipl), 8, 1);cvZero(mydst3);cvDrawContours(mydst3, hull2, CV_RGB(255, 255, 255), CV_RGB(255, 255, 255), -1, CV_FILLED, 8);return mydst3;
}char filename[100];
char newcontour[100];
char grayimg[100];
char myback[100];
char contrast[100];void main()
{TickMeter tm;tm.start();for (int i = 1; i <= 1337; i++){//背面找轮廓sprintf(filename, "背面图\\%d.bmp", i);sprintf(newcontour, "罗彬背面轮廓3\\%d.bmp", i);IplImage* src_ipl = cvLoadImage(filename);vector<Mat> bgrimgs;Mat bimg = mypredone(src_ipl, bgrimgs);IplImage* luobin_result = luobin_backcontour(bimg);cvSaveImage(newcontour, luobin_result);正面找轮廓sprintf(filename, "正面图\\%d.bmp", i);sprintf(newcontour, "罗彬正面轮廓\\%d.bmp", i);IplImage* src_ipl = cvLoadImage(filename);vector<Mat> bgrimgs;Mat bimg = mypredone(src_ipl, bgrimgs);IplImage* luobin_result = luobin_frontcontour(bimg);}tm.stop();cout << "count=" << tm.getCounter() << ",process time=" << tm.getTimeMilli() << endl;
}这样就行了！
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