OpenCV双目相机测距程序

发布时间：2024-12-05 11:47

使用相机的测距功能，辅助精确构图 #生活技巧# #数码产品使用技巧# #相机调焦方法#

本文主要分享一个双目测距的实现程序，用的bumblebee2相机。使用的OpenCV自带的BM算法。在OpenCV3中，StereoBM算法发生了比较大的变化，StereoBM被定义为纯虚类，因此不能直接实例化，只能用智能指针的形式实例化，也不用StereoBMState类来设置了，而是改成用bm->set...的形式。（转载请注明出处）

详细参数代码请查看链接http://www.cnblogs.com/polly333/p/5130375.html

另外，双目标定，立体匹配和测距的原理网上的已经很全啦，就不多啰嗦啦。使用的matlab自带的标定工具箱进行的标定。下面就上代码吧，废话少说。。。。

#include <opencv2/opencv.hpp>

#include <iostream>

using namespace std;

using namespace cv;

const int imageWidth = 1024;

const int imageHeight = 768;

Size imageSize = Size(imageWidth, imageHeight);

Mat rgbImageL, grayImageL;

Mat rgbImageR, grayImageR;

Mat rectifyImageL, rectifyImageR;

Rect validROIL;

Rect validROIR;

Mat mapLx, mapLy, mapRx, mapRy;

Mat Rl, Rr, Pl, Pr, Q;

Mat xyz;

Point origin;

Rect selection;

bool selectObject = false;

int blockSize = 0, uniquenessRatio = 0, numDisparities = 0;

Ptr<StereoBM> bm = StereoBM::create(16, 9);

Mat cameraMatrixL = (Mat_<double>(3, 3) << 1324.4092, 0, 521.2833,

0, 1328.0859, 392.6668,

0, 0, 1);

Mat distCoeffL = (Mat_<double>(1, 5) << -0.58627, 0.16595, 0, 0.00000, 0.00000);

Mat cameraMatrixR = (Mat_<double>(3, 3) << 1323.9, 0, 523.453,

0, 1326.88, 397.6582,

0, 0, 1);

Mat distCoeffR = (Mat_<double>(1, 5) << -0.63278, 0.47043, 0.00000, 0.00000, 0.00000);

Mat T = (Mat_<double>(3, 1) << -120.9319, 0.3701, 0.1176);

Mat rec = (Mat_<double>(3, 1) << 0.0022, 0.0113, -0.0001);

Mat R;

void F_Gray2Color(CvMat* gray_mat, CvMat* color_mat)

{

if (color_mat)

cvZero(color_mat);

int stype = CV_MAT_TYPE(gray_mat->type), dtype = CV_MAT_TYPE(color_mat->type);

int rows = gray_mat->rows, cols = gray_mat->cols;

if (CV_ARE_SIZES_EQ(gray_mat, color_mat) && stype == CV_8UC1 && dtype == CV_8UC3)

{

CvMat* red = cvCreateMat(rows, cols, CV_8U);

CvMat* green = cvCreateMat(rows, cols, CV_8U);

CvMat* blue = cvCreateMat(rows, cols, CV_8U);

CvMat* mask = cvCreateMat(rows, cols, CV_8U);

cvSubRS(gray_mat, cvScalar(255), blue);

cvCopy(gray_mat, red);

cvCopy(gray_mat, green);

cvCmpS(green, 128, mask, CV_CMP_GE);

cvSubRS(green, cvScalar(255), green, mask);

cvConvertScale(green, green, 2.0, 0.0);

cvMerge(blue, green, red, NULL, color_mat);

cvReleaseMat(&red);

cvReleaseMat(&green);

cvReleaseMat(&blue);

cvReleaseMat(&mask);

}

else cout << "大小格式不符合要求" << endl;

}

void stereo_match(int, void*)

{

bm->setBlockSize(2 * blockSize + 5);

bm->setROI1(validROIL);

bm->setROI2(validROIR);

bm->setPreFilterCap(31);

bm->setMinDisparity(0);

bm->setNumDisparities(numDisparities * 16 + 16);

bm->setTextureThreshold(10);

bm->setUniquenessRatio(uniquenessRatio);

bm->setSpeckleWindowSize(100);

bm->setSpeckleRange(32);

bm->setDisp12MaxDiff(-1);

Mat disp, disp8;

bm->compute(rectifyImageL, rectifyImageR, disp);

disp.convertTo(disp8, CV_8U, 255 / ((numDisparities * 16 + 16)*16.));

reprojectImageTo3D(disp, xyz, Q, true);

xyz = xyz * 16;

imshow("disparity", disp8);

CvMat disp8cv = disp8;

int m = disp8.rows;

int n = disp8.cols;

CvMat* vdispRGB= cvCreateMat(m, n, CV_8UC3);

F_Gray2Color(&disp8cv, vdispRGB);

CvMat* b = vdispRGB;

Mat gray2= cvarrToMat(b);

imshow("伪彩色深度图", gray2);

}

static void onMouse(int event, int x, int y, int, void*)

{

if (selectObject)

{

selection.x = MIN(x, origin.x);

selection.y = MIN(y, origin.y);

selection.width = std::abs(x - origin.x);

selection.height = std::abs(y - origin.y);

}

switch (event)

{

case EVENT_LBUTTONDOWN:

origin = Point(x, y);

selection = Rect(x, y, 0, 0);

selectObject = true;

cout << origin << "in world coordinate is: " << xyz.at<Vec3f>(origin) << endl;

break;

case EVENT_LBUTTONUP:

selectObject = false;

if (selection.width > 0 && selection.height > 0)

break;

}

int main()

{

Rodrigues(rec, R);

stereoRectify(cameraMatrixL, distCoeffL, cameraMatrixR, distCoeffR, imageSize, R, T, Rl, Rr, Pl, Pr, Q, CALIB_ZERO_DISPARITY,

0, imageSize, &validROIL, &validROIR);

initUndistortRectifyMap(cameraMatrixL, distCoeffL, Rl, Pr, imageSize, CV_32FC1, mapLx, mapLy);

initUndistortRectifyMap(cameraMatrixR, distCoeffR, Rr, Pr, imageSize, CV_32FC1, mapRx, mapRy);

rgbImageL = imread("left11.png", CV_LOAD_IMAGE_COLOR);

cvtColor(rgbImageL, grayImageL, CV_BGR2GRAY);

rgbImageR = imread("right11.png", CV_LOAD_IMAGE_COLOR);

cvtColor(rgbImageR, grayImageR, CV_BGR2GRAY);

imshow("ImageL Before Rectify", grayImageL);

imshow("ImageR Before Rectify", grayImageR);

remap(grayImageL, rectifyImageL, mapLx, mapLy, INTER_LINEAR);

remap(grayImageR, rectifyImageR, mapRx, mapRy, INTER_LINEAR);

Mat rgbRectifyImageL, rgbRectifyImageR;

cvtColor(rectifyImageL, rgbRectifyImageL, CV_GRAY2BGR);

cvtColor(rectifyImageR, rgbRectifyImageR, CV_GRAY2BGR);

namedWindow("ImageL After Rectify", WINDOW_NORMAL);

imshow("ImageL After Rectify", rgbRectifyImageL);

imshow("ImageR After Rectify", rgbRectifyImageR);

Mat canvas;

double sf;

int w, h;

sf = 600. / MAX(imageSize.width, imageSize.height);

w = cvRound(imageSize.width * sf);

h = cvRound(imageSize.height * sf);

canvas.create(h, w * 2, CV_8UC3);

Mat canvasPart = canvas(Rect(w * 0, 0, w, h));

resize(rgbRectifyImageL, canvasPart, canvasPart.size(), 0, 0, INTER_AREA);

Rect vroiL(cvRound(validROIL.x*sf), cvRound(validROIL.y*sf),

cvRound(validROIL.width*sf), cvRound(validROIL.height*sf));

cout << "Painted ImageL" << endl;

canvasPart = canvas(Rect(w, 0, w, h));

resize(rgbRectifyImageR, canvasPart, canvasPart.size(), 0, 0, INTER_LINEAR);

Rect vroiR(cvRound(validROIR.x * sf), cvRound(validROIR.y*sf),

cvRound(validROIR.width * sf), cvRound(validROIR.height * sf));

cout << "Painted ImageR" << endl;

for (int i = 0; i < canvas.rows; i += 16)

line(canvas, Point(0, i), Point(canvas.cols, i), Scalar(0, 255, 0), 1, 8);

imshow("rectified", canvas);

namedWindow("disparity", CV_WINDOW_AUTOSIZE);

createTrackbar("BlockSize:\n", "disparity", &blockSize, 8, stereo_match);

createTrackbar("UniquenessRatio:\n", "disparity", &uniquenessRatio, 50, stereo_match);

createTrackbar("NumDisparities:\n", "disparity", &numDisparities, 16, stereo_match);

setMouseCallback("disparity", onMouse, 0);

namedWindow("伪彩色深度图", CV_WINDOW_AUTOSIZE);

createTrackbar("BlockSize:\n", "伪彩色深度图", &blockSize, 8, stereo_match);

createTrackbar("UniquenessRatio:\n", "伪彩色深度图", &uniquenessRatio, 50, stereo_match);

createTrackbar("NumDisparities:\n", "伪彩色深度图", &numDisparities, 16, stereo_match);

setMouseCallback("伪彩色深度图", onMouse, 0);

stereo_match(0, 0);

waitKey(0);

return 0;

}

本人菜鸟一只，代码也是参考的一篇博客上的，http://blog.csdn.net/u013316124/article/details/53856797 。。。。代码有简单的修改，增加了伪彩色深度图显示。直接使用的话需要改动图片大小，标定数据和读图地址，另外算法的参数也得微调，不然出来的图会乱七八糟。。。

下面放一些效果图。。。。（深度图的效果一般，bm算法速度快，效果确实差些，参数调的也有点着急）

本文结束。还望多多指教。。。。。（不喜勿喷）

网址：OpenCV双目相机测距程序 https://www.yuejiaxmz.com/news/view/383774

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