Image Re-Ranking Based on Relevance Feedback Combining Internal and External Similarities
Ricardo Omar Chávez García, Manuel Montes-y-Gómez, Luis Enrique Sucar · 2010
We propose a novel method to re-order the list of im-ages returned by an image retrieval system (IRS). The method combines the original order obtained by an IRS, the similarity between images obtained with textual fea-tures and a relevance feedback approach, all of them with the purpose of separating relevant from irrelevant images, and thus, obtaining a more appropriate order. Experiments were conducted with resources from Im-age CLEF 2008; the proposed method improves the or-der of the original list up to 42%.