A Hybrid Approach for CBIR using SVM Classifier, Partical Swarm Optimizer with Mahalanobis Formula

The goal of content-based image retrieval is to retrieve the images that as per the user query. Mainly the Content based Image retrieval technique attempt to search through the database that finds images that are perceptually similar to a given query image. Set of low-Level visual features (Color, Shape and Texture) are used to represent an image in most modern content based image retrieval systems. Therefore, a gap exists between low-level visual features and information of high-level perception, which is the main reason that down the improvement of the image retrieval accuracy. To retrieve several features of images and shorten the semantic gap between low-level visual feature and high-level perception a Hybrid support vector machine (SVM) scheme is proposed in this paper. Image data set is taken from coral image data set.