A signature-based bag of visual words method for image indexing and search

In this paper, we revisit SDLC, an image retrieval method that adopts a signature-based approach to identify visual words, instead of the more conventional approach that identifies them by using clustering techniques. We start by providing a formal and generalized definition of the approach adopted in SDLC, which we call Signature-Based Bag of Visual Words. After that, we present a detailed study of SDLC parameters and experiments with distinct weighting schemes used to compute the ranking of results, comparing the method to well-known cluster-based bag of visual words approaches. When compared to the initial proposal of SDLC, the choice of different parameters and a new weighting scheme allowed us to considerably reduce the size of the textual representation generated by the method, reducing also the indexing times and the query processing times in all collections adopted in the experiments. Further, the SDLC outperforms the baselines in most of these collections.