Using Statistical Moment Invariants and Entropy in Image Retrieval

TL;DR

This paper introduces a new image retrieval method combining statistical moment invariants and entropy, demonstrating scalability and efficiency for matching images based on example queries.

Contribution

The paper proposes a novel image retrieval technique that integrates moment invariants and entropy, enhancing matching accuracy and efficiency over existing methods.

Findings

Method is scalable to large image databases

Technique achieves efficient retrieval performance

Effective in finding semi or perfect matches

Abstract

Although content-based image retrieval (CBIR) is not a new subject, it keeps attracting more and more attention, as the amount of images grow tremendously due to internet, inexpensive hardware and automation of image acquisition. One of the applications of CBIR is fetching images from a database. This paper presents a new method for automatic image retrieval using moment invariants and image entropy, our technique could be used to find semi or perfect matches based on query by example manner, experimental results demonstrate that the purposed technique is scalable and efficient.