Image Retrieval using GA Optimized Gabor Filter

Objective: A Hybrid content based image retrieval method is proposed in this paper. This method extracts color, tuned texture and shape features of the images in three successive phases. Methodology: In proposed system, color features are extracted using color histogram method in the first phase. The tuned texture features are extracted by employing GA optimized Gabor filters in second phase. Finally, shape features are extracted using the polygonal fitting algorithm. The best match output images of each phase are given as input images to the next phase to obtain ‘S’ best match images out of ‘N’ database images. Findings: The novelty of proposed system is that it employs a tunable filter that is tuned with the query image dynamically. The tuning of Gabor filter is implemented using GA in second phase. The proposed method shows improved retrieval rate in terms of average recall and average precision compared to the existing systems. The computation complexity is also found to be less than other existing methods. Applications: It can be employed in numerous fields such as medical, satellite, multimedia, and surveillance imaging systems, etc. where the retrieval of related images from huge databases is critical task for analysis.