Abstract
This article presents results of the simulation of SIFT based algorithms in the context of the identification of tattoos. The algorithms studied are the SIFT - Scale Invariant Feature Transform, ASIFT - Affine SIFT, BOV - Bag of Visual Words and FV - Fisher Vector. The use of the OPF - Optimum-Path Forest and SVM - Support Vector Machine classifiers is exploited in conjunction with SIFT and ASIFT algorithms as well as BOV and FV. The present study uses the National Institute of Standards and Technology (NIST) Tatt-C dataset in a reduced and complete version. This work uses runtime and accuracy to compare the results of the simulations.
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