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Local Image Representation and Matching Based on Gaussian-Hermite Moments

Abstract: The description of image local features has been the most important part in image#br# registration and image retrieval. In this paper, Gaussian-Hermite moments are studied and their#br# invariants are derived. Due to that the scale parameter does not affect their rotation invariants, a#br# descriptor based on multi-scale Gaussian-Hermite moments is proposed. Finally, the proposed#br# descriptor is tested in a serial experiments with the state-of-the-art methods, and the experimental#br# results show that the proposed descriptor performs much better than the others.#br# Key words: Gaussian-Hermite moments; moment invariants; feature description; GHM#br# descriptor   

  • Online:2015-06-30 Published:2015-05-05

Abstract: The description of image local features has been the most important part in image
registration and image retrieval. In this paper, Gaussian-Hermite moments are studied and their
invariants are derived. Due to that the scale parameter does not affect their rotation invariants, a
descriptor based on multi-scale Gaussian-Hermite moments is proposed. Finally, the proposed
descriptor is tested in a serial experiments with the state-of-the-art methods, and the experimental
results show that the proposed descriptor performs much better than the others.

Key words: Gaussian-Hermite moments, moment invariants, feature description, GHM
descriptor