Image Retrieval System Base on EMD Similarity Measure and S-Tree

TL;DR

This paper presents an image retrieval system that uses Earth Mover's Distance to measure similarity between images and employs an S-tree data structure for efficient querying in large image databases.

Contribution

The paper introduces a novel combination of EMD-based similarity measure with an S-tree structure for fast content-based image retrieval.

Findings

Effective retrieval on a database with over 10,000 images

High accuracy in image similarity assessment

Fast query response times

Abstract

The paper approaches the binary signature for each image based on the percentage of the pixels in each color images, at the same time the paper builds a similar measure between images based on EMD (Earth Mover's Distance). Besides, the paper proceeded to create the S-tree based on the similar measure EMD to store the image's binary signatures to quickly query image signature data. From there, the paper build an image retrieval algorithm and CBIR (Content-Based Image Retrieval) based on a similar measure EMD and S-tree. Based on this theory, the paper proceeded to build application and experimental assessment of the process of querying image on the database system which have over 10,000 images.