Semantic based Query Approach For Web Image Search Through reranking algorithm

Abstract

Image search re ranking is an effective technique to filter the text-based image search result. Most existing re
ranking approaches are based on low level visual features. In this project, we implement to exploit semantic attributes
for image search re ranking. Based on the classifiers for all the pre defined attributes, each image is represented by an
attribute feature consisting of the responses from these classifiers. A hypergraph is then used to model the relationship
between images by integrating low-level visual features and attribute features. Hypergraph ranking is then performed to
order the images.