Reducing image search time by improved BOVW with wavelet decomposition

Mohammed El Amin Kourtiche (1) , Mohammed Beladgham (1) , Abdelmalik Taleb-Ahmed (2, 3)

1 Université Tahri Mohamed Bechar [Bechar]
2 COMNUM - IEMN - COMmunications NUMériques - IEMN
3 IEMN - Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520

In the last decade, the bag of visual words (BOVW) has been used widely in image classification, image retrieval and has significantly improved the performance of CBIR system. In this paper we propose a new method to enhance BOVW using features obtained from wavelet decomposition in order to reduce computational costs in vocabulary construction and training time. We apply several level of wavelet decompositions and evaluate their impact on accuracy of the BOVW. We apply our method on MURA-v1.1 dataset and the experiments results confirm the performance of our approach.

Mots clés: Bag of visual words; Image retrieval; Indexing; Wavelet decomposition

Domaines: Recherche d'information [cs.IR]; Traitement des images [eess.IV]; Informatique [cs]; Sciences de l'ingénieur [physics]; Intelligence artificielle [cs.AI]; Réseaux et télécommunications [cs.NI]; Traitement du signal et de l'image [eess.SP]; Electronique

Mohammed El Amin Kourtiche, Mohammed Beladgham, Abdelmalik Taleb-Ahmed. Reducing image search time by improved BOVW with wavelet decomposition. Indonesian Journal of Electrical Engineering and Computer Science, 2021, 21 (2), pp.1201-1208. ⟨10.11591/ijeecs.v21.i2.pp1201-1208⟩. ⟨hal-03472229⟩