Target Dual Station location simulation C + + code

Source: Internet
Author: User
Tags cos sin

Point-position2 Preliminary Perfect version

The two stations are extracted to obtain the matching feature points of the image, and the target location is resolved by the two station position information.

//point-position2.cpp: Defines the entry point of the console application. #include"stdafx.h"#include<stdio.h>#include<iostream>#include"opencv2/core/core.hpp"#include"opencv2/features2d/features2d.hpp"#include"opencv2/highgui/highgui.hpp"#include<opencv2/nonfree/features2d.hpp>#include"opencv2/imgproc/imgproc.hpp"#include"opencv2/nonfree/nonfree.hpp"#include"opencv2/legacy/legacy.hpp"#include<math.h>using namespaceCV;intMainintargcChar**argv) {Mat img_1= Imread ("Book_in_scene.png"); Mat img_2= Imread ("Book2.png"); if(!img_1.data | |!img_2.data) {Std::cout<<" --(!) Error reading Images"<< Std::endl;return-1; } //--Step 1:detect the keypoints using SURF Detector    intMinhessian = -;    Siftfeaturedetector detector (Minhessian); //Surffeaturedetector Detector (Minhessian);Vector<KeyPoint>Keypoints_1, keypoints_2;    Detector.detect (img_1, keypoints_1);    Detector.detect (Img_2, keypoints_2); //--Step 2:calculate descriptors (feature vectors)siftdescriptorextractor Extractor; //surfdescriptorextractor Extractor;Mat descriptors_1, descriptors_2;    Extractor.compute (img_1, Keypoints_1, descriptors_1);    Extractor.compute (Img_2, keypoints_2, descriptors_2); //--Step 3:matching descriptor vectors using FLANN matcherFlannbasedmatcher Matcher; Std::vector< Dmatch >matches;    Matcher.match (Descriptors_1, descriptors_2, matches); DoubleMax_dist =0;DoubleMin_dist = -; //--Quick calculation of Max and min distances between keypoints     for(inti =0; i < descriptors_1.rows; i++ )    { DoubleDist =matches[i].distance; if(Dist < min_dist) Min_dist =Dist; if(Dist > max_dist) max_dist =Dist; }    //printf ("--Max dist:%f \ n", max_dist); //printf ("-Min dist:%f \ n", min_dist); //--Draw only "good" matches (i.e whose distance are less than 2*min_dist)//--ps.-Radiusmatch can also is used here.std::vector< Dmatch >good_matches;  for(inti =0; i < descriptors_1.rows; i++ )    { if(Matches[i].distance <2*min_dist)    {Good_matches.push_back (matches[i]);} }    //--Draw only "good" matchesMat img_matches;    Drawmatches (img_1, Keypoints_1, Img_2, Keypoints_2, Good_matches, img_matches); //--Show detected matches//imshow ("Good Matches", img_matches); //imwrite ("Lena_match_surf.jpg", img_matches); //imwrite ("Lena_match_sift.jpg", img_matches); //Good_matches[i].queryidx holds the ordinal of the first image match point, keypoints_1[good_matches[i].queryidx].pt.x the x-coordinate of the point corresponding to the ordinal. Y coordinate//Good_matches[i].trainidx holds the ordinal of the second picture match point, keypoints_2[good_matches[i].trainidx].pt.x the x-coordinate of the point corresponding to the ordinal. Y coordinateprintf"--keypoint 1:%f,%f:%d--keypoint 2:%f,%f:%d \ n", keypoints_1[good_matches[0].queryidx].pt.x,keypoints_1[good_matches[0].queryidx].pt.y,good_matches[0].queryidx, keypoints_2[good_matches[0].trainidx].pt.x,keypoints_2[good_matches[0].trainidx].pt.y,good_matches[0].trainidx); /*___________________________________________________________________________________________________________ ____________________*/    DoubleX_inimage1,y_inimage1,x_inimage2,y_inimage2,y,x,y,alpha,gamma;//Image Polygon Coordinates (x, y) and images size (x, Y) and imaging field of view (Alpha,gamma)    DoubleX1,Y1,Z1,X2,Y2,Z2;//Dual Station coordinates    DoubleALPHA1,GAMMA1;//two-station pitch angle and deflection angle    DoubleAlpha2,gamma2; //give the initial valuealpha1= $; GAMMA1= $; ALPHA2= the; Gamma2= $; X=640; Y=480; Doublefovx=Ten; Doublefovy=fovx*y/X; X1=0, y1=0, z1=0; X2=0, y2= $, z2=0;/*//Angular deviation compensation x_inimage1=keypoints_1[good_matches[0].queryidx].pt.x;//target point coordinates are matched by the resulting Y_INIMAGE1=KEYPOINTS_1[GOOD_MATC    Hes[0].queryidx].pt.y;    X_inimage2=keypoints_2[good_matches[0].queryidx].pt.x;    Y_inimage2=keypoints_2[good_matches[0].queryidx].pt.y;    Double deviation_alpha1= (X_INIMAGE1-X/2)/x*fovx;    Double deviation_alpha2= (X_INIMAGE2-X/2)/x*fovx;    Double deviation_gamma1= (Y_INIMAGE1-Y/2)/x*fovy;    Double deviation_gamma2= (Y_INIMAGE2-Y/2)/x*fovy;    ALPHA1=ALPHA1+DEVIATION_ALPHA1;    ALPHA2=ALPHA2+DEVIATION_ALPHA2;    GAMMA1=GAMMA1+DEVIATION_GAMMA1; GAMMA2=GAMMA2+DEVIATION_GAMMA2;*/    //Start Calculation    DoublePi= -* (Atan (1.0/5))-4*atan (1.0/239);//precise definition of pistd::cout<<"pi is:"<<pi<<Std::endl; Alpha1=alpha1*pi/ the;//Angle radians Conversiongamma1=gamma1*pi/ the; ALPHA2=alpha2*pi/ the; Gamma2=gamma2*pi/ the;//std::cout<< "cos (ALPHA1) for:" <<cos (ALPHA1) <<std::endl;//std::cout<< "cos (GAMMA1) for:" <<cos (GAMMA1) <<std::endl;    Doublem1= (cos (ALPHA1)) *(cos (GAMMA1)); DoubleN1= (sin (alpha1)) *(cos (GAMMA1)); Doublep1=sin (gamma1); Doublem2= (cos (ALPHA2)) *(cos (GAMMA2)); DoubleN2= (sin (alpha2)) *(cos (GAMMA2)); DoubleP2=sin (gamma2); Std::cout<<"the direction vector 1 is:"<<m1<<","<<n1<<","<<p1<<Std::endl; Std::cout<<"the direction Vector 2 is:"<<m2<<","<<n2<<","<<p2<<Std::endl; DoubleCoplane;//Common face judgmentCoplane= (x2-x1) * (N1*P2-N2*P1)-(y2-y1) * (M1*P2-M2*P1) + (Z2-Z1) * (M1*N2-M2*N1);//coplane=0 co-surface    if(coplane) {//calculate crossover direction vectors A1, B1, C1        Doublea1=n1*p2-n2*P1; Doubleb1=p1*m2-p2*M1; Doublec1=m1*n2-m2*N1; //        Doublea2=n2*c1-p2*B1; Doubleb2=p2*a1-m2*C1; Doublec2=m2*b1-n2*A1; DoubleA3=n1*c1-p1*B1; DoubleB3=p1*a1-m1*C1; DoubleC3=m1*b1-n1*A1; DoubleDelta1=n1* (B1*C2-B2*C1) +m1* (a1*c2-a2*C1); Doubledelta2=n2* (B1*C3-B3*C1) +m2* (a1*c3-a3*C1); Doubled1=a2* (x2-x1) +b2* (y2-y1) +c2* (z2-Z1); Doubled2=a3* (x1-x2) +b3* (y1-y2) +c3* (z1-z2); DoubleXg,yg,zg,xh,yh,zh,xtarget,ytarget,ztarget;//two linear perpendicular g and H point coordinates, where the target point is located. Xg=x1-(D1*M1*C1)/delta1; Yg=y1-(D1*N1*C1)/delta1; Zg=z1+d1* (A1*M1+B1*N1)/delta1; Xh=x2-(D2*M2*C1)/Delta2; Yh=y2-(D2*N2*C1)/Delta2; Zh=z2+d2* (A1*M2+B1*N2)/Delta2; Xtarget= (XG+XH)/2; Ytarget= (YG+YH)/2; Ztarget= (Zg+zh)/2; Std::cout<<"the target coordinates are:"<<Xtarget<<","<<Ytarget<<","<<Ztarget<<std::endl<<Std::endl; }    Else//two lines coplanar and intersecting, introducing parameter T    {        DoubleT; T= (p2* (y1-y2) +n2* (Z2-Z1))/(n2*p1-p2*N1); DoubleXtarget,ytarget,ztarget; Xtarget=x1+m1*T; Ytarget=y1+n1*T; Ztarget=z1+p1*T; Std::cout<<"the target coordinates are:"<<Xtarget<<","<<Ytarget<<","<<Ztarget<<std::endl<<Std::endl;    } getchar (); //waitkey (0);    return 0;}

Target Dual Station location simulation C + + code

Related Article

Contact Us

The content source of this page is from Internet, which doesn't represent Alibaba Cloud's opinion; products and services mentioned on that page don't have any relationship with Alibaba Cloud. If the content of the page makes you feel confusing, please write us an email, we will handle the problem within 5 days after receiving your email.

If you find any instances of plagiarism from the community, please send an email to: info-contact@alibabacloud.com and provide relevant evidence. A staff member will contact you within 5 working days.

A Free Trial That Lets You Build Big!

Start building with 50+ products and up to 12 months usage for Elastic Compute Service

  • Sales Support

    1 on 1 presale consultation

  • After-Sales Support

    24/7 Technical Support 6 Free Tickets per Quarter Faster Response

  • Alibaba Cloud offers highly flexible support services tailored to meet your exact needs.