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arXiv · 2411.18800

Optimizing Image Retrieval with an Extended b-Metric Space

Abdelkader Belhenniche·Roman Chertovskih
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Abstract

This article provides a new approach on how to enhance data storage and retrieval in the Query By Image Content Systems (QBIC) by introducing the ${\rm NEM}_{\sigma}$ distance measure, satisfying the relaxed triangle inequality. By leveraging the concept of extended $b$-metric spaces, we address complex distance relationships, thereby improving the accuracy and efficiency of image database management. The use of ${\rm NEM}_{\sigma}$ facilitates better scalability and accuracy in large-scale image retrieval systems, optimizing both the storage and retrieval processes. The proposed method represents a significant advancement over traditional distance measures, offering enhanced flexibility and precision in the context of image content-based querying. Additionally, we take inspiration from ice flow models using ${\rm NEM}_{\sigma}$ and ${\rm NEM}_r$, adding dynamic and location-based factors to better capture details in images.

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Abdelkader Belhenniche, Roman Chertovskih. 2024-11-27. Optimizing Image Retrieval with an Extended b-Metric Space. https://arxiv.org/abs/2411.18800

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