Do image descriptors work for every type of image?

asked 2020-05-25 11:42:31 -0600

I'm about to build an image search application for a large dataset. But many of the images will be very "bland" - ie with little variation in colour, or one colour with a subtle texture. However these are in addition to more complex images.

My initial thought was to dive with SIFT/SURF/ORB or regular feature descriptors, then simply do a Nearest Neighbour/distance calc on the descriptor vectors.

However, I'm not sure how well this will work for images which are very plain and have "no features".

Would be very grateful for any thoughts!

edit retag flag offensive close merge delete

Comments

build an image search application for a large dataset.

Content Based Retrieval of Images (CBIR) ? you'll find a lot on the net ...

then simply do a Nearest Neighbour/distance calc on the descriptor vectors.

if you meant -- (ab)using opencv'sbuiltin feature matching -- proven NOT TO WORK (as is). most of your features will be statistically irrellevant, nice to find a homography for parts of a given scene, but not fit for this job. that's why clustering / BOW is used

images which are very plain and have "no features".

yea ;( but again, absence of features is information, too ...

berak gravatar imageberak ( 2020-05-25 11:53:41 -0600 )edit