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 test our method on a 70K material microscopy image dataset, achieving a 24.67 times improvement in retrieval speed with only a 20.78% reduction in ranking accuracy. Additionally, we tested our approach on larger datasets to validate its scalability and effectiveness.