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Ultra-Fast Zernike Moments using FFT and GPU

arXiv 2304.14492 ↗First posted 6 Apr 2023cs.CVcited by 0

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Abstract (arXiv)

Zernike moments can be used to generate invariant features that are applied in various machine vision applications. They, however, suffer from slow implementation and numerical stability problems. We propose a novel method for computing Zernike using Fast Fourier Transform (FFT) and GPU computing. The method can be used to generate accurate moments up to high orders, and can compute Zernike moments of 4K resolution images in real-time. Numerical accuracies of Zernike moments computed with the proposed FFT approach have been analyzed using the orthogonality property and the results show that they beat other methods in numerical stability. The proposed method is simple and fast and can make use of the huge GPU-FFT libraries that are available in several programming frameworks.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 1 of its 14 references that are in the map. First posted on arXiv 6 Apr 2023.

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  1. 2014A comparison of dense region detectors for image search and fine-grained classificationcited by 3

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