bris's profile - activity

My question is similar to the image comparison one but I need to be more specific...

I have two images:

• One is a computer drawing (a map) with no texture and about 5 colors:
• The other image is a photo of the paper version of the computer drawing:

(It could be at any orientation too like this:)

I'm trying to match the images so that the photo of the paper version can be found in the large image with a box around the area it matches. Or just have the descriptors properly matched up like I've seen in similar examples online (like this one from a SURF Tutorial:)

My attempts using SURF have clearly failed (this was from a demo using SURF/FLANN and homography):

I even tried template matching but this was the result:

It seems this could be done using SURF, but being new to computer vision, I'm not sure if some pre-processing on the photo of the computer drawing should be done.

My questions are:

1. Is there some pre-processing I need to/should do on the photo of the computer drawing before the features are found...will this help with finding more of the same features that are in the original computer drawing?
2. Is there a specific Extractor (other than SURF) or Matching technique (I've used brute force and FLANN) that would help get better results?
3. Is there something special about matching images like these with little to no textures?
4. I know SURF/SIFT are scale invariant, but will it affect the features found if the computer drawing image is very large / high resolution (2517 x 3046) compared to a smaller version (say 529 x 640)