Conference Paper

Hilbert-Huang Transform-based Local Regions Descriptors.

DOI: 10.5244/C.21.16 Conference: Proceedings of the British Machine Vision Conference 2007, University of Warwick, UK, September 10-13, 2007
Source: DBLP


This paper presents a new interest local regions descriptors method based on Hilbert-Huang Transform. The neighborhood of the interest local region is decomposed adaptively into oscillatory components called intrinsic mode functions (IMFs). Then the Hilbert transform is applied to each component and get the phase and amplitude information. The proposed descriptors sam- ples the phase angles information and amalgamates them into 10 overlap squares with 8-bin orientation histograms. The experiments show that the proposed descriptors are better than SIFT and other standard descriptors. Es- sentially, the Hilbert-Huang Transform based descriptors can belong to the class of phase-based descriptors. So it can provides a better way to overcome the illumination changes. Additionally, the Hilbert-Huang transform is a new tool for analyzing signals and the proposed descriptors is a new attempt to the Hilbert-Huang transform.

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