|
|
|
@ -38,13 +38,13 @@ best matches. There is also **cv.drawMatchesKnn** which draws all the k best mat |
|
|
|
|
will draw two match-lines for each keypoint. So we have to pass a mask if we want to selectively |
|
|
|
|
draw it. |
|
|
|
|
|
|
|
|
|
Let's see one example for each of SURF and ORB (Both use different distance measurements). |
|
|
|
|
Let's see one example for each of SIFT and ORB (Both use different distance measurements). |
|
|
|
|
|
|
|
|
|
### Brute-Force Matching with ORB Descriptors |
|
|
|
|
|
|
|
|
|
Here, we will see a simple example on how to match features between two images. In this case, I have |
|
|
|
|
a queryImage and a trainImage. We will try to find the queryImage in trainImage using feature |
|
|
|
|
matching. ( The images are /samples/c/box.png and /samples/c/box_in_scene.png) |
|
|
|
|
matching. ( The images are /samples/data/box.png and /samples/data/box_in_scene.png) |
|
|
|
|
|
|
|
|
|
We are using ORB descriptors to match features. So let's start with loading images, finding |
|
|
|
|
descriptors etc. |
|
|
|
|