Structural Similarity Measurement with Metaheuristic Algorithm for Content based Image Retrieval

Content based image retrieval (CBIR) model is highly employed for the retrieval of images that is connected to the query image (QI) from massive dataset. The feature set filtered from the existing CBIR models are less effective in case of massive dataset. In this paper, the feature extraction takes place in an efficient way where the features are hold in a feature set. This feature set contains a set of color signatures which contains the features of shape as well as color. In this instant, the feature extraction takes place from the provided QI. Based on this, similarity measurement takes place using genetic algorithm with Iterated local search. In addition, the validation takes place by the use of Structural Similarity (SSIM) measure to analyze the difference between QI and retrieved images. The values are measured and the comparative analysis is made with respect to precision and recall.