reduce interest area for image stitching
I’d like to do image stitching on hard samples, having repeated patterns. Let’s say, images of a wall like a chessboard with non informative background (sand).
I’m using python cv2 image stitching, but it “compress” the output. The repeated pattern, must be misleading cv2 into thinking it is an image repetition:
I’d like the image stitching algorigthm to give me the next output:
I think it is reachable, by using a parameter to:
- specify the image order sequence: [image_1.jpg, image_2.jpg, image_3.jpg]
- specify the left and right image area to be taken into account for the pattern matching: [(0%, 18%),(18%,18%), (12%,0%)]
In my case, I could have this data:
How could I solve it with opencv?
Thanks in advance
Do you want oval or flat?
you must use a mask in computeImageFeatures or in cv::Stitcher::stitch
funny, but the "current stitcher output" looks like the "minimal energy" solution
@supra56. I didn't understand what you were referring
Thanks @LBerger! I could use the mask to specify the area
But I think I have to specify also the order of the images.
Otherwise It's going to get confused with all the images.
For example, the right image could perfectly match with the left one. And the image in the middle could be in the left.
Perhaps in this conceptual example, I could work with the mask, but I'm going to have a lot of images to stitch.
Is there any way to specify the order, on even better, to give restrictions about wich images can/can't be stitched?
in stitching_detailed you can use range_width argument