Bubble Tag Identification Using an Invariant–Under–Perspective Signature

We have at our disposal a large database containing images of various configurations of coplanar circles, randomly laid-out, called “Bubble Tags”. The images are taken from different viewpoints. Given a new image (query image), the goal is to find in the database the image containing the same bubble tag as the query image. We propose representing the images through projective invariant signatures which allow identifying the bubble tag without passing through an Euclidean reconstruction step. This is justified by the size of the database, which imposes the use of queries in 1D/vectorial form, i.e. not in 2D/matrix form. The experiments carried out confirm the efficiency of our approach, in terms of precision and complexity.