Optimization of Log Gabor Filters Using Genetic Algorithm for Query by Image Content Systems

Query By Image Content (QBIC) system permits the user to extract similar images from the large database by specifying the query image. In this paper, a new hybrid QBIC system is proposed, which effectively utilizes the color, texture, and shape features by sequential process of three pipe stages which gives good retrieval performance and also reduces computational complexity. In first pipe stage, color features are extracted with histograms based on HSV color space. In second pipe stage, texture information is obtained by optimizing log Gabor filters using genetic algorithm. Finally, in third pipe stage, shape features are extracted with signature functions using polygonal algorithm. Simulation results show that the proposed hybrid sequential pipe stage combination gives good performance metrics in terms of mean recall and mean precision and also reduces the number of filters compared to the existing algorithms.