Efficient Image Similarity Search with Quadtrees (Student Abstract)

Authors

  • Yifan Zhang Lehigh Unviersity
  • Jeff Heflin Lehigh Unviersity

DOI:

https://doi.org/10.1609/aaai.v39i28.35324

Abstract

In this paper, we present a new image similarity search algorithm designed to enhance traditional information retrieval(IR) by adding an image search capability. Our approach uses a quadtree data structure to organize image data, significantly reducing search space and improving retrieval efficiency. We describe an indexing strategy and two query algorithms that can be implemented in any IR system. We tested our method on a 70K material microscopy image dataset, achieving a 25 times improvement in retrieval speed with only a 20% reduction in ranking accuracy.

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Published

2025-04-11

How to Cite

Zhang, Y., & Heflin, J. (2025). Efficient Image Similarity Search with Quadtrees (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 39(28), 29558–29559. https://doi.org/10.1609/aaai.v39i28.35324