// L14
//基于ORB实现线性融合
#
include
"stdafx.h"
#
include
<vector
>
#
include
<opencv2
/core.hpp
>
#
include
<opencv2
/highgui.hpp
>
#
include
<opencv2
/imgproc.hpp
>
#
include
<opencv2
/imgproc
/imgproc_c.h
>
#
include
<opencv2
/core
/core.hpp
>
#
include
<opencv2
/imgproc
/imgproc.hpp
>
#
include
<opencv2
/highgui
/highgui.hpp
>
#
include
<opencv2
/features2d
/features2d.hpp
>
#
include
<opencv2
/calib3d
/calib3d.hpp
>
using
namespace std;
using
namespace cv;
int _tmain(
int argc, _TCHAR
* argv[])
{
cv
:
:Mat image1
= cv
:
:imread(
"parliament1.bmp",
1);
cv
:
:Mat image2
= cv
:
:imread(
"parliament2.bmp",
1);
if (
!image1.data
||
!image2.data)
return
0;
std
:
:vector
<cv
:
:KeyPoint
> keypoints1, keypoints2;
//寻找ORB特针点对
Ptr
<DescriptorMatcher
> descriptorMatcher;
// Match between img1 and img2
vector
<DMatch
> matches;
// keypoint for img1 and img2
vector
<KeyPoint
> keyImg1, keyImg2;
// Descriptor for img1 and img2
Mat descImg1, descImg2;
//创建ORB对象
Ptr
<Feature2D
> b
= ORB
:
:create();
//两种方法寻找特征点
b
-
>detect(image1, keyImg1, Mat());
// and compute their descriptors with method compute
b
-
>compute(image1, keyImg1, descImg1);
// or detect and compute descriptors in one step
b
-
>detectAndCompute(image2, Mat(),keyImg2, descImg2,
false);
//匹配特征点
descriptorMatcher
= DescriptorMatcher
:
:create(
"BruteForce");
descriptorMatcher
-
>match(descImg1, descImg2, matches, Mat());
Mat index;
int nbMatch
=
int(matches.size());
Mat tab(nbMatch,
1, CV_32F);
for (
int i
=
0; i
<nbMatch; i
++)
{
tab.at
<
float
>(i,
0)
= matches[i].distance;
}
sortIdx(tab, index, cv
:
:SORT_EVERY_COLUMN
+cv
:
:SORT_ASCENDING);
vector
<DMatch
> bestMatches;
for (
int i
=
0; i
<
60; i
++)
{
bestMatches.push_back(matches[index.at
<
int
>(i,
0)]);
}
Mat result;
drawMatches(image1, keyImg1, image2, keyImg2, bestMatches, result);
std
:
:vector
<Point2f
> obj;
std
:
:vector
<Point2f
> scene;
for(
int i
=
0; i
< (
int)bestMatches.size(); i
++ )
{
obj.push_back( keyImg1[ bestMatches[i].queryIdx ].pt );
scene.push_back( keyImg2[ bestMatches[i].trainIdx ].pt );
}
//直接调用ransac,计算单应矩阵
Mat H
= findHomography( obj, scene, CV_RANSAC );
//绘制仿射结果
std
:
:vector
<Point2f
> obj_corners(
4);
std
:
:vector
<Point2f
> scene_corners(
4);
obj_corners[
0]
= Point(
0,
0);
obj_corners[
1]
= Point( image1.cols,
0 );
obj_corners[
2]
= Point( image1.cols, image1.rows );
obj_corners[
3]
= Point(
0, image1.rows );
perspectiveTransform( obj_corners, scene_corners, H);
//-- Draw lines between the corners (the mapped object in the scene - image_2 )
Point2f offset( (
float)image1.cols,
0);
line( result, scene_corners[
0]
+ offset, scene_corners[
1]
+ offset, Scalar(
0,
255,
0),
4 );
line( result, scene_corners[
1]
+ offset, scene_corners[
2]
+ offset, Scalar(
0,
255,
0),
4 );
line( result, scene_corners[
2]
+ offset, scene_corners[
3]
+ offset, Scalar(
0,
255,
0),
4 );
line( result, scene_corners[
3]
+ offset, scene_corners[
0]
+ offset, Scalar(
0,
255,
0),
4 );
imshow(
"两图比对", result);
//初步显示结果
//通过透视变换转换到一起
cv
:
:Mat resultAll;
cv
:
:warpPerspective(image1,
// input image
resultAll,
// output image
H,
// homography
cv
:
:Size(
2
*image1.cols,image1.rows));
// size of output image
cv
:
:Mat resultback;
resultAll.copyTo(resultback);
// Copy image 1 on the first half of full image
cv
:
:Mat half(resultAll,cv
:
:Rect(
0,
0,image2.cols,image2.rows));
image2.copyTo(half);
//进行liner的融合
Mat outImage;
//待输出图片
resultAll.copyTo(outImage);
//图像拷贝
double dblend
=
0.
0;
int ioffset
=image2.cols
-
100;
//col的初始定位
for (
int i
=
0;i
<
100;i
++)
{
outImage.col(ioffset
+i)
= image2.col(ioffset
+i)
*(
1
-dblend)
+ resultback.col(ioffset
+i)
*dblend;
dblend
= dblend
+
0.
01;
}
waitKey();
imshow(
"融合结果",outImage);
return
0;
}