I am trying to match images from a large dataset which exactly match the given input image.(images with deformations/transformations are treated as different)
I have tried euclidean distance but it isn't very scalable. I have also tried matching gradient magnitude and orientation pixel by pixel, but again it seems to work in approximate manner and is slow.
I believe, pixel by pixel matching wouldn't be apt for matching from such large dataset. Moreover, even if certain approximation is allowed, can the threshold be decided dynamically rather than prefixed ?