Image Retrieval System Base on EMD Similarity Measure and S-Tree
This work addresses content-based image retrieval for large datasets, but it appears incremental as it combines existing techniques like EMD and S-trees.
The paper tackled image retrieval by developing a system that uses Earth Mover's Distance (EMD) for similarity measurement and an S-tree for efficient storage, achieving querying on a database of over 10,000 images.
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.