Re-weighting relevance feedback image retrieval algorithm based on particle swarm optimization
Aiming at the inflexible re-weighting problem of relevance feedback (RF) in image retrieval, a re-weighting relevance feedback method utilizing particle swarm optimization (PSORW-RF) is proposed. Firstly, initialize feature weightings randomly, then use the variances of the positive and negative feedback samples' features as study principle, utilize particle swarm optimization (PSO) algorithm to optimize weightings according to user's retrieval requirement, and obtain retrieval results at last. Experiments show that the proposed algorithm is validity.