# A Kind of Affine Weighted Moment Invariants

## TL;DR

This paper introduces affine weighted moment invariants (AWMI), a new geometric feature extraction method that improves stability, distinguishability, and retrieval performance in images by combining local invariants with a global integral framework.

## Contribution

The paper proposes a novel affine weighted moment invariant method that enhances feature extraction efficiency and effectiveness compared to traditional invariants.

## Key findings

- AWMIs have good stability and distinguishability
- AWMIs outperform traditional moment invariants in image retrieval
- Extension to 3D is straightforward

## Abstract

A new kind of geometric invariants is proposed in this paper, which is called affine weighted moment invariant (AWMI). By combination of local affine differential invariants and a framework of global integral, they can more effectively extract features of images and help to increase the number of low-order invariants and to decrease the calculating cost. The experimental results show that AWMIs have good stability and distinguishability and achieve better results in image retrieval than traditional moment invariants. An extension to 3D is straightforward.