Distributed Content-Based Image Retrieval of Satellite Images on Hadoop

Title:Distributed Content-Based Image Retrieval of Satellite Images on Hadoop

Volume: 14 Issue: 3

Author(s): Tapan Sharma*, Vinod Shokeen and Sunil Mathur

Affiliation:

• Amity School of Engineering & Technology, Amity University, Noida, Uttar Pradesh,India

Keywords: Distributed computing, image retrieval, MapReduce, satellite images, hadoop, spark, Neo4J, HBase.

Abstract:

Background: Owing to increased growth in satellite imagery, the development of an architecture that rapidly and efficiently identifies similar images has become crucial. Hadoop has become a de-facto platform for storing large amounts of data. Apache Spark and MapReduce have also become key frameworks for distributed processing of big data.

Objective: This paper proposes a novel Distributed Content-Based Image Retrieval (DCBIR) architecture that leverages the qualities of these engines, which were not utilized in previous studies.

Methods: Features of 40 satellite images with sizes greater than 500 MB were indexed, on a 15-node Hadoop cluster with two different databases viz. Neo4J, a graph database, and HBase, a columnar database.

Results: Performance and Scalability of both indexing and query phases, along with precision and recall were observed for both databases.

Conclusion: Experimental results show that the proposed system can efficiently perform image retrieval on large remote sensing images.

Cite this article as:

Sharma Tapan *, Shokeen Vinod and Mathur Sunil , Distributed Content-Based Image Retrieval of Satellite Images on Hadoop, Recent Advances in Computer Science and Communications 2021; 14 (3) . https://dx.doi.org/10.2174/2666255813666191126095114