OpenCV實現拼接圖像的簡單方法

//讀取圖像
Mat leftImg=imread("left.jpg");
Mat rightImg=imread("right.jpg");
if(leftImg.data==NULL||rightImg.data==NULL)
 return;
 
//轉化成灰度圖
Mat leftGray;
Mat rightGray;
cvtColor(leftImg,leftGray,CV_BGR2GRAY);
cvtColor(rightImg,rightGray,CV_BGR2GRAY);
 
//獲取兩幅圖像的共同特征點
int minHessian=400;
SurfFeatureDetector detector(minHessian);
vector<KeyPoint> leftKeyPoints,rightKeyPoints;
detector.detect(leftGray,leftKeyPoints);
detector.detect(rightGray,rightKeyPoints);
SurfDescriptorExtractor extractor;
Mat leftDescriptor,rightDescriptor;
extractor.compute(leftGray,leftKeyPoints,leftDescriptor);
extractor.compute(rightGray,rightKeyPoints,rightDescriptor);
FlannBasedMatcher matcher;
vector<DMatch> matches;
matcher.match(leftDescriptor,rightDescriptor,matches); 
int matchCount=leftDescriptor.rows;
if(matchCount>15)
{
 matchCount=15;
 sort(matches.begin(),matches.begin()+leftDescriptor.rows,DistanceLessThan);
} 
vector<Point2f> leftPoints;
vector<Point2f> rightPoints;
for(int i=0; i<matchCount; i++)
{
 leftPoints.push_back(leftKeyPoints[matches[i].queryIdx].pt);
 rightPoints.push_back(rightKeyPoints[matches[i].trainIdx].pt);
}
 
//獲取左邊圖像到右邊圖像的投影映射關系
Mat homo=findHomography(leftPoints,rightPoints);
Mat shftMat=(Mat_<double>(3,3)<<1.0,0,leftImg.cols, 0,1.0,0, 0,0,1.0);
 
//拼接圖像
Mat tiledImg;
warpPerspective(leftImg,tiledImg,shftMat*homo,Size(leftImg.cols+rightImg.cols,rightImg.rows));
rightImg.copyTo(Mat(tiledImg,Rect(leftImg.cols,0,rightImg.cols,rightImg.rows)));
 
//保存圖像
imwrite("tiled.jpg",tiledImg);
 
//顯示拼接的圖像
imshow("tiled image",tiledImg);
waitKey(0);