Content based Image Retrieval with Rocchio Algorithm for Relevance Feedback Using 2D Image Feature Representation

Abstract

This paper presents Content based Image Retrieval with Relevance Feedback to retrieve relevant images based on an image query. Three main steps are proposed, first, obtain 2D feature representation of an image query and image database using the Integrated Color Co-Occurrence Matrix. This feature extraction method captures two features simultaneously, they are color and texture features. Second, compute cosine similarity measurement to retrieve similar images between features of an image query and features of all images in the database. Third, update the query features using Rocchio algorithm based on the user's relevance feedback, and recalculation of the cosine similarity between the updated feature of query and features of all images in the database. Experiments are conducted using Corel Image database that consists of 1000 images from ten classes. The proposed model for retrieving similar images achieved higher performance accuracy compare to the Content based Image Retrieval without Relevance feedback.